Designing Games: Complete Summary of Tynan Sylvester’s Guide to Engineering Experiences for Game Design Excellence

Introduction: What This Book Is About

“Designing Games: A Guide to Engineering Experiences” by Tynan Sylvester offers a comprehensive framework for understanding and mastering the craft of game design. Sylvester, with experience ranging from indie projects to major titles like BioShock Infinite, argues that games are not merely products but “engines of experience,” designed to evoke specific emotions and thought processes in players. This book moves beyond superficial notions of “fun” to delve into the underlying mechanics, psychological triggers, and organizational processes that define truly great games.

The book is structured into three main parts: “Engines of Experience,” which explores the core concepts of game design craft; “Game Crafting,” which delves into specific design elements like skill, narrative, decisions, balance, and interface; and “Process,” which addresses the day-to-day realities of game development, including planning, iteration, knowledge creation, authority, and motivation. Sylvester challenges common assumptions borrowed from other media, emphasizing that successful game design requires a unique approach tailored to its interactive nature.

Readers will benefit from this book by gaining a systematic understanding of game design principles, learning to identify and address common pitfalls, and developing a more nuanced perspective on what makes games engaging. It is an essential guide for aspiring and professional game designers, developers, and anyone interested in the intricate art and science behind creating compelling interactive experiences. Sylvester’s insights help designers move from intuitive guessing to informed decision-making, ultimately enabling them to craft games that reach their full potential.

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Chapter 1: Engines of Experience

This chapter introduces the fundamental concept that games are “engines of experience,” focusing on how mechanics generate events that, in turn, provoke emotions in players. It emphasizes the critical distinction between authoring events directly (like in film) and designing systems that generate emergent events.

What Mechanics and Events Mean

Games are composed of mechanics, which define how the game works. A mechanic is a rule, whether it’s a jump button in a video game or a pawn’s diagonal capture rule in chess. During play, mechanics and players interact to generate events, which are specific occurrences within the game, such as Mario hitting a wall or a pawn capturing a rook. Unlike other media where events are directly authored, games create events dynamically through systemic interaction.

The Primacy of Emotion

A game’s primary goal is to provoke emotion in players. Events are only meaningful if they trigger feelings like pride, hilarity, awe, or terror. These emotions are often subtle, not just extreme passions, and constantly shift in response to in-game stimuli. Understanding these subtle emotional pulses is a crucial skill for game designers, akin to a chef deconstructing flavors. The author argues against limiting game design discussions to “fun,” as games can evoke a vast spectrum of powerful emotions, from competitive triumph to contemplative mourning.

How Emotional Triggers Work

An emotional trigger is something or an observation that causes emotion. The unconscious mind constantly analyzes situations, triggering responses when certain conditions are met, such as fear near a cliff or attraction to a potential mate. To provoke emotion, an event must signal a meaningful change in some human value. Human values are things important to people that can shift between positive, neutral, or negative states, like [life/death], [victory/defeat], or [wealth/poverty]. The more important the value and the greater the shift, the stronger the emotion. Emotions also appear in anticipation of change, as the unconscious mind scans for future threats or opportunities.

The Emotional Black Box

Humans cannot directly perceive the logic behind their emotional triggers. Emotions are automatic, unconscious calculations, meaning we can feel something without knowing precisely why. This leads to emotional misattribution, where individuals attribute their feelings to the most salient factor, even if it’s not the true cause. For example, arousal from a dangerous bridge might be misattributed as attraction to a person. Players often rationalize their feelings about a game, attributing them to visuals or controls, even when the real causes are deeper mechanical interactions. This makes understanding how games affect players particularly challenging, requiring designers to theorize and test indirectly.

Emotion Through Learning

Learning feels good, especially when it involves concepts important to human values. Humans are instinctively driven to master skills that aided ancestral reproduction, such as kinesthetic abilities, social roles, and combat. The more intricate and nonobvious a lesson, the greater the pleasure of learning it, leading to the concept of deep games that reveal lessons in layers. Players feel insight when new information causes many old pieces to suddenly make sense, creating a powerful “Aha!” moment.

Emotion Through Character Arcs

Humans are empathetic, mirroring emotions felt in others. Games can create character arcs either through predefined stories (like traditional media) or emergently from player and mechanic interactions (e.g., a simulated family in “The Sims”). This feeds a “learning hunger” about peers, as conflict reveals inner values and abilities.

Emotion Through Challenge

Tests of skill and strength create emotions like focus, capability, and dominance. While powerful and flexible, challenge is only one emotional trigger and not essential for every game. Good, flow-sparking experiences live in the “Goldilocks zone” between too hard (frustrating) and too easy (boring).

Emotion Through Social Interaction

Games can serve as pretexts for social interaction, even if their internal mechanics are simple (e.g., playing catch). Most social interaction games use specific events to drive connections, like one player defeating another or collaborating on a creation. Social interactions work when they shift social human values, such as stranger to friend, or low status to high status. Games can support a vast array of social experiences, from building trust to showing off.

Emotion Through Acquisition

Acquiring wealth or possessions creates a pulse of happiness. Games can trigger this response with real wealth (gambling) or artificial systems of wealth and acquisition (in-game currency, equipment). The fake reward still activates the brain’s reward center, as seen in action RPGs like “Diablo III” where continuous loot acquisition keeps players motivated.

Emotion Through Music

Music is a powerful and flexible tool for generating emotion, used liberally across many media to accentuate feelings like excitement, tension, or serenity. Nonmusical sounds also create emotion, such as screeching metal for tension or rain for serenity. These sounds can accentuate or contrast emotions, but overuse can lead to cheesiness.

Emotion Through Spectacle

Razzle-dazzle spectacle can provide a quick emotional rise, but its payoff is often shallow and unsustainable. While expensive to produce, it’s creatively easy, leading to overuse by studios. Spectacle works best when it reinforces existing emotions, such as accentuating relief after a difficult battle. Gratuitous spectacle without context can leave players numb.

Emotion Through Beauty

Beauty is pleasurable simply by perceiving it, whether in art, nature, or game environments. Games offer many opportunities for beauty, from character rendering to environmental composition. However, beauty isn’t free and can clash with a game’s aesthetic goals (e.g., in horror games) or add audiovisual noise that hinders understanding and interaction. It works best when channeled for a specific purpose rather than thoughtlessly applied.

Emotion Through Newfangled Technology

Shiny new technology can bring a quick emotional rise, but this benefit is often temporary. Technological advances can paradoxically lead to a temporary reduction in design quality because they take creative pressure off designers, turning games into tech demos. Sustained success requires new technology to unlock interactions and situations that couldn’t have been experienced before, rather than just being visually impressive.

Emotion Through Primal Threats

Some fears are genetically imprinted, such as revulsion to rotten food or recoil from spiders and snakes. Games can trigger these responses with gore or spiders, but this is often too easy and has been cheapened by overuse. To create genuine horror, threats must disturb players on a deeper psychological level.

Emotion Through Sexual Signals

Sexual signals are effective and easy to use due to genetic programming. However, gratuitous sexuality can harm a serious narrative’s atmosphere and believability, and irritate potential players not interested in such signals. For more serious or broadly targeted games, it’s often not worth being tasteless.

The Fiction Layer

Games often wrap mechanics in fiction to imbue them with a second layer of emotional meaning. While chess pieces are just sculptures, the rules make them “come alive” through fictional roles. Similarly, Mario is mechanically a collision cylinder, but the fictional Italian plumber adds emotional resonance. The immersive fallacy is the mistaken belief that fiction replaces or conceals mechanics; instead, fiction adds a complementary layer of meaning to emotions generated by mechanics.

Fiction Versus Mechanics

Fiction and mechanics each create different kinds of emotions. Mechanics generate tension, triumph, and the pleasure of learning, but struggle with humor, awe, or empathy. Fiction creates emotion through character, plot, and world, but cannot offer competition or skill mastery. The challenge lies in their potential to interfere with each other. Game fiction often relies on clichés (like ubiquitous crates) because they cleanly justify good mechanics, even if they make less fictional sense. This conflict often leads games to emphasize one over the other. The pinnacle of game design craft is combining perfect mechanics and compelling fiction into one seamless system of meaning.

Constructing Experiences

An experience is an arc of emotions, thoughts, and decisions inside the player’s mind, transforming through setup, payoff, expectation, and result. Game experiences are always mixed and diverse.

Pure Emotion in Experience

To maximize a single feeling, designers can combine several emotional triggers that drive the exact same emotion, boosting the experience towards a pure emotional peak. Traditional arcade games, for example, combine fast music, risky situations, violent fiction, and competitive social interaction for maximum excitement.

Juxtaposition in Experience

Juxtaposition is the combination of different, seemingly incompatible feelings, which can produce strange and valuable results. “Gears of War,” for instance, juxtaposes hyper-violence with mournful themes, creating a richer emotional texture than a pure gore-fest. Experimenting with contrasting music can reveal powerful juxtapositions.

Antagonistic Emotions in Experience

Some emotions are antagonistic and don’t coexist easily, harming each other when combined. For example, ruthless skill-based competition can harm shared social enjoyment. The line between productive juxtaposition and destructive antagonism is fine, with attempts sometimes falling flat or producing unintended, yet entertaining, mixtures.

Atmosphere in Experience

Atmosphere refers to emotions that permeate the whole experience in a spread-out haze, forming an emotional background. Some games de-emphasize individual emotional punches to focus on growing a thick atmosphere, often serene or contemplative, flavored by fiction and slow-paced interaction (e.g., “LIMBO,” “DEFCON”).

Emotional Variation in Experience

Any single emotion becomes tiring if sustained too long, requiring an experience to transform over time. Pacing variation, like the classic three-act story formula, can be found in games, either predefined or emergently generated. Games can also vary the “flavor” (valence) of emotions, sending players across their emotional spectrum from joy to anger to relief, keeping the experience fresh.

Flow in Experience

Flow is a state of concentration so focused that it amounts to total absorption in an activity, making time seem to disappear. It is pleasurable due to a continuous stream of tiny successes. Flow appears when a challenge is perfectly balanced against a player’s ability level; too hard leads to anxiety, too easy leads to boredom. It is the foundation for most good game experiences, working across various intensity levels and emotional valences.

Immersion in Experience

Immersion occurs when the mental division between the player’s real self and their in-game avatar softens, making avatar events feel personally meaningful. Immersion happens when the player’s experience mirrors the character’s experience, meaning the player thinks and feels what the character thinks and feels. This relies on the two-factor theory of emotion, which states emotions are composed of physiological arousal and a cognitive label. To create immersion:

• Create flow to strip the real world out of the player’s mind.
• Create an arousal state using threats and challenges in game mechanics.
• Use the fiction layer to label the player’s arousal to match the character’s feelings.
  This delicate mix allows mechanics-driven arousal to be relabeled by fiction, merging separate experiences into one immersive feeling.

Engines of Experience Summary

The chapter concludes by defining a game as “an artificial system for generating experiences.” Games are like special machines, made of carefully designed mechanics that interact in complex ways to provoke emotion. The metaphor of a game as an “engine of experience” is proposed as a more accurate and useful way to think about game design than traditional storytelling or movie metaphors, emphasizing dynamic interaction and emergent interactivity.

Chapter 2: Elegance

This chapter defines elegance in game design as maximizing emotional power and variety of play experiences while minimizing player comprehension burden and developer effort. It argues that elegant games resemble sculptures, where excess material is removed to reveal the form within.

Elegance from Emergence

Emergence occurs when simple mechanics interact to create complex situations. Elegant games leverage emergence, crafting mechanics that multiply into a rich universe of possibilities rather than just adding together. A simple combination of “look, shoot, and move” can generate countless unique experiences in a shooter. However, this tight interaction also makes elegant design difficult, as changes to one mechanic affect all others in complex, non-obvious ways.

Smelling Elegance in Design

Since elegance is hard to predict directly, designers can use intuition and mental heuristics to “smell” it.

• Mechanics that interact with many other mechanics smell like elegance. These are versatile tools that contribute to many different situations.
• Simple mechanics smell like elegance. They offer good results without overburdening players with complexity.
• Mechanics that can be used in multiple ways smell like elegance. Tools with offensive, defensive, tactical, and strategic roles are more elegant than single-purpose ones.
• Mechanics that don’t overlap one another’s roles smell like elegance. Each tool should have a distinct purpose that others cannot fulfill, introducing completely new kinds of play.
• Mechanics that reuse established conventions and interfaces smell like elegance. Leveraging existing player knowledge reduces comprehension burden.
• Mechanics that work on a similar scale as existing mechanics smell like elegance. Consistent scaling across elements (e.g., numbers, speeds, health) allows for natural interactions without tedious calculations.
• Mechanics that are reused a lot smell like elegance. Repetitive use of core mechanics that generate new experiences each time is essential for elegance.
• Mechanics that don’t impose restrictions on content smell like elegance. They improve the game without forcing contortions in other design elements or levels.
• Mechanics that use the full expressiveness of the available interface smell like elegance. Utilizing the full range of input (e.g., analog stick angles, button hold times) can add depth for skilled players.

Elegance Case Study: Predator versus Hellion

The chapter uses “StarCraft II: Wings of Liberty” to compare two similar units, the Predator and the Hellion, to illustrate elegance. Both are fast, mid-cost units with area-of-effect attacks.

• Predator’s circular attack offers limited tactical depth, as it’s rarely surrounded by enemies and its short range limits synergy. Its frequent attacks also prevent “shoot and scoot” tactics.
• Hellion’s long, narrow flame stream creates nuanced play, as its effectiveness varies dramatically with enemy and environmental geometry. Its ranged attack allows for cover and ledge synergy. Its slower attack speed permits advanced “shoot and scoot” tactics.
  The Hellion is mechanically no more complex than the Predator but is more elegant because it generates significantly more challenges, tactics, and situations. Elegance often comes from simple, workmanlike designs that “flower into a million experiences,” rather than flashy gimmicks.

Chapter 3: Skill

This chapter explores how games manage player skill to maintain engagement, focusing on the “Goldilocks zone” where challenges are neither too hard nor too easy.

What Depth Means

Deep games create meaningful play at high skill levels, offering enough nuance and variation to provide new lessons for a long time (e.g., chess, poker). A game’s skill ceiling is the level beyond which performance cannot improve. If this is beyond human ability, the game is limitlessly deep. Shallow games, like tic-tac-toe, have low skill ceilings and quickly become boring once mastered. Players cherish breaking skill barriers, but hate designers if they ever fully “solve” a game.

What Accessibility Means

Accessible games create meaningful play at low skill levels. A game’s skill barrier is the lower limit of skill below which it is unplayable. Many games have intimidating skill barriers (e.g., FPS controls for newcomers). Accessibility is often undervalued by designers who are already highly skilled.

What Skill Range Means

A game’s skill range is the range of skill levels at which it presents a meaningful challenge. A wide skill range means the game is easy to learn and hard to master, enjoyable for both novices and experts. Narrow skill ranges indicate games quickly mastered once learned. Games don’t need wide skill ranges to be good if they offer other forms of meaning (e.g., “BioShock” focuses on art and narrative).

Skill Without Explicit Goals

Even games without explicit goals (like “Dwarf Fortress,” “The Sims,” “Minecraft”) have skill ranges. Players must meet a minimum skill level to interact meaningfully (e.g., reading, using a mouse). Furthermore, players often invent their own goals within these “toys,” turning them into skill games. Thus, even goal-less toys benefit from expressing interesting, non-obvious properties that can be learned.

Stretching Skill Range: Reinvention

Games broaden their skill range by repeatedly reinventing themselves as the player’s skill increases. As one layer of challenge is mastered, a deeper layer of play presents itself. Games tend to go through three characteristic reinventions:

• Manual Reinvention: Focuses on simple, moment-to-moment mechanical skills and mastering the interface (e.g., aiming in a shooter, moving chess pieces). All games start here.
• Situational Reinvention: Manual skills are mostly unconscious, and the challenge shifts to situational awareness, pattern recognition, and counter-strategies (e.g., map control, tracking opponents). This is where most players and games operate.
• Mental Reinvention: Reached by expert, competitive players, this level involves predicting and manipulating opponents’ minds, concentrating on performance under pressure, and psychological trickery. This is the poker-like end state of most limitlessly deep games.

Stretching Skill Range: Elastic Challenges

Elastic challenges permit different degrees of success and failure, providing appropriate challenges across a wider skill range. Instead of simple pass/fail designs, they offer multiple levels of success (e.g., granular scoring in darts, “Silent Assassin” ratings in “Hitman”) or allow for different degrees of failure (e.g., grabbing a ledge after a missed jump). This ensures everyone has an attainable but challenging goal.

Stretching Skill Range: Training

Training systems help players get past the skill barrier quicker through tutorials, messages, and hints. Good training is invisible, threading into the narrative (“Call of Duty 4”), turning into elastic challenges (time trials), or being adaptive by providing lessons only when needed. The most invisible training is the unnecessary training that never happens.

Stretching Skill Range: Emotional Life Support

To prevent players from giving up before surmounting the skill barrier, designers can keep their experience on life support using emotional triggers that don’t require skill. This involves flooding early stages with low-skill emotional triggers like sublime art, fascinating characters, humor, or tech demos, transforming learning into a semi-interactive intro movie (“BioShock”).

Difficulty Modification

Difficulty modification means shifting a game’s challenge level as a whole.

• Explicit Difficulty Selection: Asks players how much challenge they want (e.g., easy, medium, hard). While straightforward, the choice can be confusing.
• Adaptive Difficulty: Silently adjusts the game’s difficulty based on player performance. Best when players are unaware, as experts might try to game the system. Can be combined with explicit settings.
• Implicit Difficulty Selection: Allows players to adjust their challenge level by making strategic decisions (e.g., choosing character classes in “Team Fortress 2” that match their aiming skill, or advancing quickly/slowly in “Call of Duty 4” to control enemy spawns).

Handling Failure

To create suspense, games must put human values at risk, meaning the possibility of failure must be real. However, designers should not punish the player themselves for failure. Instead, they should:

• Punish the player character through fictional consequences (e.g., being shot, impoverished).
• Deny success or create small setbacks (e.g., losing resources, an ally), allowing the game to continue on a new path without repetition (“StarCraft II” campaign).
• Make failure a rewarding experience in itself if it leads to new, interesting situations (“Dwarf Fortress”).
• Ensure flow is never broken by instant restarts (“Super Meat Boy”).

Failure Traps

A failure trap occurs when a player spends a long time locked into a situation where failure is guaranteed, like a losing sports team forced to finish a match. These can emerge unexpectedly, such as a player hitting a restart checkpoint without ammo. Solutions include elastic failure conditions (e.g., infinite-ammo fallback weapons), surrender mechanisms in competitive games, or alternative challenges in single-player games. Some traps, like the “dead-man-walking” scenario in sports, remain difficult to solve cleanly.

Chapter 4: Narrative

This chapter explores game narrative, moving beyond film-centric approaches to draw inspiration from older forms of participatory storytelling.

What Narrative Tools Mean

A narrative tool is a device used to form a piece of a story in a player’s mind. Games have a broader set of tools than other media, including predefined sequences (like film), written text (like novels), explorable spaces (like museums), and unique interactive tools that generate plot, character, and theme on the fly in response to player decisions.

Scripted Story

A game’s scripted story refers to events encoded directly into the game that always play out the same way. The most basic tool is the cutscene, which uses filmic techniques but inevitably breaks flow by disabling interactivity.

Soft Scripting

Soft scripting allows pre-authored events to play out while the player maintains some degree of interactivity. This approach preserves flow, as controls remain uninterrupted. However, it means the designer loses some control, as players might observe events from unintended angles, miss them, or even interfere. The balance between player influence and designer control is crucial, with examples ranging from “Half-Life’s” tramcar ride (limited interaction) to “Dead Space 2’s” subway car sequence (movement disabled, shooting enabled) and “Halo: Reach’s” AI tactical hints (AI follows general commands but responds autonomously to player actions).

World Narrative

World narrative is the story of a place, its past, and its people, told through the construction of the place and its objects. It allows players to explore a space like a detective, piecing together history and character through environmental cues, item placement, and hidden documents. Places carry both emotional and informational charges (e.g., a prison vs. a palace).

World Narrative Methods

World narrative works through:

• Presence or absence of features: A town wall implies past military threats.
• Cultural symbols: Roman architecture evokes empires, dark Gothic evokes evil.
• Mise-en-scène: Arranging leftovers of specific events (e.g., corpse placement indicating an execution).
• Documents: PDAs or scattered texts revealing character lives and plot details (“Deus Ex”).
• Audio logs: Conveying emotions and recordings of events (“BioShock”).
• Video logs: Showing leftover TV programs, news, or security footage.
• Straddling tools: News broadcasts, propaganda, or civilian discussions that communicate world nature.

World Narrative and Interactivity

World narrative is highly useful in games because it avoids many problems of combining scripted events with interactivity.

• Inviolate: Players cannot interfere with a story that has already happened.
• Non-linear: Content can be consumed in any order, allowing player exploration without railroading.
• Replayability: Naturally uncovers itself in layers from generalities to specifics, encouraging repeated exploration for new details.

World Coherence

World narrative strengthens when a world is coherent and expresses internal connections. A well-constructed fictional world is a “puzzle of relationships and implications,” slavishly following its own rules and exploring possibilities. This leads to implied narrative content beyond what is shown. Incoherent worlds are jumbles of disconnected details, lacking depth or elegance. Crafting coherence means every piece fits together historically, physically, and culturally. “Dead Space 2’s” Kinesis device, for example, is elegant not just mechanically but also narratively, with its presence reflected in the world’s culture, economy, and construction.

Emergent Story

Emergent story is generated during play by the interaction of game mechanics and players. It creates unique, unscripted sequences of events (e.g., a racing game comeback). Designers indirectly author emergent stories by designing mechanics that determine the types of stories capable of emerging. This is an elegant way to create original content, offloading authorship to game systems and players. The concept of emergent story helps deploy a “story-thinking tool set” to analyze dynamically generated game situations. Only emergent stories can break the barrier between fiction and reality, as seen in real-life player achievements like beating a sibling in chess.

Apophenia and Emergent Story

Apophenia is the human tendency to see imaginary patterns in complex data, especially personality in inanimate objects. This is crucial for emergent stories, as games don’t need to truly simulate human minds; they just need to do enough for the player’s mind to interpret something as an intelligent agent. The player’s unconscious then imbues moving tokens with imaginary wants, obligations, and relationships.

Labeling for Emergent Story

Designers can strengthen emergent stories by labeling existing game mechanics with fiction. Giving names to individual soldiers (“Close Combat”) or personality traits to nobles (“Medieval: Total War”) encourages players to construct deeper narratives, even if the game systems don’t simulate those relationships directly. This is elegant because the player’s mind does most of the work.

Abstraction for Emergent Story

Showing and telling players less creates more room for apophenia to fill in the gaps. More detailed graphics can reduce imaginative interpretation. Abstract, minimalistic representations allow more apophenia. “Dwarf Fortress,” with its ASCII graphics, is an extreme example where players see rich narratives in simple symbols. Any gap in representation allows the player’s mind to fill in details, making games like strategy, building, and economics sims more prone to rich emergent stories than close-in genres.

Recordkeeping for Emergent Story

Games can emphasize emergent stories by keeping records of game events to remind players of what happened. This includes time-lapsed world maps of shifting borders (“Civilization IV”), persistent corpses and blood spatter for reconstructing battles (“Myth”), or player-created photo albums of simulated families (“The Sims”).

Sportscaster Systems for Emergent Story

Similar to sports commentators, games can use systems to interpret and link together game events into coherent narratives. “Hitman: Blood Money” generates newspaper articles based on player actions, changing the story based on stealth, accuracy, and violence. These systems are difficult to do well, as it’s hard for games to systemically interpret human-important events. They often work best by kickstarting the player’s own apophenic process.

Story Ordering

Games use various devices to enforce story ordering, ensuring content is consumed in a desired sequence.

• Levels: The classic linear progression from one arena to the next.
• Quests: Self-contained mini-stories embedded in a larger, unordered world, with a fixed internal event order but flexible start/end times.
• Blockages: Physical or narrative barriers (e.g., locked doors, guards) that require players to complete certain tasks before progressing.
• Skill Gating: Soft ordering where content is technically available but requires certain skill levels or upgrades to access, gently directing new players.
• Time-based events: Events occurring at fixed times in the world (“Dead Rising”).

Story Structures

Combining story-ordering devices creates different structures:

• String of Pearls: Linear progression from level to level (“Quake,” “Super Mario Bros.”).
• Hub and Spokes: A central hub connects to self-contained content nuggets that can be tackled in any order (“Mega Man”).
• Branching Events: Attempts to model outcomes of every possible decision, but quickly leads to an explosion of possible timelines and missed content unless events are largely emergent.
• Side Quests and Story Convergence: Ways to manage branching by offering optional content (side quests) or having branched storylines later converge back to a single path.
  Hybrid structures, like “Mass Effect 2’s” linear start/end with a quest-driven middle, are popular for combining careful introductions with player freedom.

Agency Problems

Agency is the ability to make decisions and take meaningful actions that affect the game world. Game stories face “agency problems” because players can easily contradict or miss story elements, disrupting the author’s carefully crafted narrative.

Player–Character Motivation Alignment

Many agency problems arise when the player’s motivations differ from their character’s, leading to “desk jumping”—actions the character would never take (e.g., James Bond dancing on his boss’s desk). Players desk-jump to explore simulation limits, consume content, or create humor. Examples include attacking allies or systematically robbing innocents while playing a “good” character. This problem is particularly visible in “Grand Theft Auto IV,” where the character’s nuanced moral decisions clash with the player’s motivation to cause chaos.
Solutions include:

• Disallowing desk jumping: Effective but can weaken player engagement by making game mechanics feel artificial. Works well if fictionally justified (e.g., “Portal’s” contained world).
• Ignoring desk jumping: Allowing actions but not acknowledging them makes the behavior less appealing.
• Incorporating desk jumping: Embracing player actions and spinning the narrative around them (e.g., a boss’s humorous response in “Deus Ex,” “Duke Nukem Forever’s” Ego bar). Best when incorporated in a closed and complete way.
• Designing for motivation alignment: The best solution is to design the game so that players’ motivations naturally align with their character’s (e.g., “Call of Duty’s” fast-paced combat overriding impulses to act foolishly).

The Human Interaction Problem

Games struggle with rich human interaction due to limitations in input/output and AI’s inability to simulate human minds.

• Fictionally disallowing direct interaction: Characters might only speak via radio or be violently insane when confronted (“BioShock”).
• Dialogue trees: Predefine player choices and character responses, offering limited options but full designer control.
• Reusing standard game verbs: Expressing social choices through actions like shooting or walking (e.g., choosing to kill or spare an enemy in “Grand Theft Auto IV”).
• Multiplayer games using real players: In games like “Dungeons & Dragons,” a human Dungeon Master fills NPC roles, allowing for unlimited interaction. In video games, this requires motivating players to properly role-play, which is difficult with anonymous strangers.

Case Study: Fallout 3

The chapter presents a personal narrative from playing “Fallout 3” to illustrate how various narrative tools combine.

• World story: The desiccated landscape, makeshift architecture of Megaton, and character appearances (Moira Brown’s grungy coveralls) all tell a story of post-apocalyptic life and character.
• Player choice: The player’s actions in exploring the world create an emergent story alongside the backstory.
• Dialogue trees: Conversations with NPCs like Moira are hard-scripted, often looping back to a hub-and-spokes structure.
• Emergent encounters: Randomly appearing hunters fighting scripted raiders create unscripted, dynamic battles.
• Apophenia: Player interpretations of events (e.g., a hunter’s bravado before death, a final raider’s “ambush”) are constructed in the mind from simple game elements.
• Labeling: Antlers on a raider give him a distinct personality.
• Goofy undertone: Absurdities (like Moira’s enthusiasm) lighten emotional load and justify less realistic game elements.
• Content ordering: A mix of scripted progression (parking lot before store) and player freedom to leave and return to quests.
• Pacing: Irregularly spiky, with tense combat moments interspersed with dialogue, exploration, and healing, keeping players engaged without exhaustion.
• Setting: The post-apocalyptic world justifies constant combat (supporting mechanics) and low population density (accommodating technical limitations).

Chapter 5: Decisions

This chapter delves into decisions as the unique emotional trigger in games, exploring how they work and how to design systems that generate meaningful choices.

Feeling the Future through Decisions

Decisions are about choosing among multiple possible futures, and the emotions they provoke are about what might happen, not just what has happened. Players don’t just experience what happens; their minds interact with every possible outcome they can detect, running a constant simulation of the future. This internal decision process, filled with expectation, uncertainty, and consequence, is what makes games like chess fascinating. Without meaningful decisions, games can become emotionally empty, even with lots of action.

Predictability and Decisions

For decisions to be meaningful, their outcomes must be neither unknowable nor inevitable; they must be partially predictable. Without predictability, planning is impossible, and the game devolves into reactive thrashing. If the future is totally predictable, there are no meaningful decisions. Prediction relies on game systems being consistent and comprehensible. Mario’s consistent jump physics, for example, allows players to plan and feel potential outcomes. Overly smart or chaotic AI can hinder predictability, as it makes opponent actions incomprehensible. AI should often be thought of as a predictable mechanic rather than a realistic simulation.

Predictability and Predefined Decisions

The chapter distinguishes predefined plot branches (like in “Choose Your Own Adventure” books), where options and outcomes are explicitly authored, from mechanics-driven decisions, where outcomes emerge from game systems. Predefined decisions often rely on fictional reasons or players trying to guess the designer’s intent, rather than engaging with game systems.

Information Balance

The character, difficulty, and complexity of a decision depend on the information available to the player. Information balancing is the design process of providing or denying information to make a decision comprehensible without being obvious.

• Information Starvation: Too little information makes decisions confusing and random, leading to reactive flailing (e.g., playing “Battleship” blind). It can arise from hidden information (e.g., future challenges in RPGs, ambiguous fictional cues). A useful FAQ is a warning sign of an information-starved game. Information starvation is insidious because designers, with their complete knowledge, often don’t perceive it, and it’s emotionally painful to admit.
• Information Glut: Too much information erases decisions entirely, as the answer becomes obvious (e.g., a heartbeat sensor showing all enemy locations in a shooter). Solutions involve subtracting information, adding limitations, or delaying information delivery to create strategic depth.

Ways to Hide Information

Even seemingly complete information games can hide decision-relevant information:

• Hidden in complex cause and effect: The future state of a chessboard three turns ahead is hidden behind chains of interactions.
• Hidden in players’ internal states: An opponent’s planned moves or vulnerabilities are hidden, driving mind games.
• Hidden by speed: Information that arrives too quickly to be processed (e.g., milliseconds in a shooter) is effectively hidden.

Information Balance Case Study: Poker

The history of poker illustrates information balance:

• Old poker (20-card deck, one betting round) was information-starved, leading to low skill and randomness.
• Draw poker (52-card deck, multiple draw/betting rounds) added information, making it more strategic.
• Stud poker (face-up cards) swung to information glut, as winning hands were often obvious.
• Community card games (shared face-up cards) like Texas Hold’em achieved a perfect balance. The shared cards prevent obvious winners, while hidden cards and betting patterns create fascinating, nuanced decisions. The core mechanics remained similar, but changes in information structure transformed the game.

Problematic Information Sources

• Fictional Ambiguity: Information from fiction is often ambiguous because players don’t know which aspects of the fiction are implemented mechanically (e.g., what can you really do with a roast turkey in a game?). This leads to frustration when players try plausible fictional actions that aren’t mechanically simulated. Good puzzles should be based on non-obvious uses of mechanics that work in obvious ways, rather than relying on ambiguous fictional cues.
• Metagame Information: Players gather knowledge from outside the game (e.g., genre conventions, developer habits, trailers). This can create information glut by revealing what the game won’t do (e.g., expecting health packs in a “survival horror” game because games are “fair”). Designers must either accept metagame information as a constraint or deliberately break conventions to create genuine threats.

Decisions and Flow

Flow is crucial for good game experiences, as it pulls the player’s mind into the game, making the real world vanish. Maintaining flow means constantly feeding the mind decisions at just the right rate, like filling a cup with water without it overflowing or running dry.

Decision Scope

Decision scope is the amount of thought a decision takes to make.

• Nondecisions: Answers are so obvious they don’t engage the mind meaningfully (e.g., pouring milk into cereal).
• Twitch Decisions: Smallest meaningful decisions, taking less than a second of simple conscious reasoning (e.g., punch or kick?). Common in action games.
• Tactical Decisions: Require 1-5 seconds of thought, engaging the conscious mind with more information (e.g., which equipment to buy?).
• Profound Decisions: Largest decisions, taking 10+ seconds, drawing from broad knowledge and pushing players to deep self-reflection (e.g., a chess grandmaster’s long contemplation). Arise from the most elegant, subtle systems.
• Impossible Decisions: Beyond a player’s ability to understand, leading to random choices and breaking flow.
  Player skill changes the effective scope of decisions: A profound decision for a novice might be a nondecision for an expert, defining the skill ceiling.

Avoiding Flow Gaps

A flow gap is a period of time when the player’s mind has nothing to chew on, leading to boredom. These can arise from tool delays, menu transitions, or dialogue. Solutions include:

• Making other abilities available during delays.
• Introducing decisions into the gap.
• Redesigning mechanics like stun attacks to interfere with controls without completely disabling player agency (e.g., “Modern Warfare 2’s” stun grenade slows movement but allows action).

Avoiding Overflow

An overflow is a moment where the player is overwhelmed by decisions. This is more obvious than flow gaps, typically leading to stressed playtesters, and is usually corrected by reducing decision pressure. Overflows often affect less skilled players.

Turn-Based Decision Pacing

Turn-based games allow players to pace their own decisions. However, poorly scoped decisions can still cause problems:

• Micromanagement: Too many small-scoped decisions force players into tedious, thoughtless actions.
• Analysis Paralysis: Decisions are too large, leading to excessively long thinking times.

Decision Variation

To keep flow interesting, designers should vary decision densities and scope, mixing twitch, tactical, and profound decisions. The classic pacing curve (hook, rising action, climax, denouement) is one guideline. The only hard-and-fast rule is that pacing should vary, avoiding long, slow periods or exhausting fast ones. Designers can analyze decision pacing by mentally simulating gameplay second-by-second.

Decisions Case Study: Counter-Strike

“Counter-Strike” has maintained immense popularity for over 13 years due to its balance, pace, skill, and decisions, rather than its fiction.

• Initial profound decision: Players analyze the map, team composition, and enemy skills during the waiting phase to plan their strategy.
• Dynamic decision pacing: The game shifts between low-decision periods (executing a plan) and high-decision spikes (reacting to new information, like an enemy’s death).
• Information hidden by speed: Players must make rapid choices without full information, forcing intuitive judgment.
• Continuous tactical puzzles: The game constantly produces new tactical puzzles, mixing twitch shooting with tactical movement and team strategy.
• Deadly weapons: The high lethality means decisions before engagement are critical, fostering a “cat and mouse” mind game.
  “Counter-Strike” is less about shooting and more about an intricate dance of mental evaluation and counter-evaluation (yomi), which keeps players engaged for thousands of hours.

Chapter 6: Balance

This chapter defines balancing as adjusting game mechanics to change the relative power of different tools, units, strategies, teams, or characters. It highlights that balancing can involve simple number tweaks or fundamental design changes.

Goals of Balance

Balancing is a method used to achieve various goals, but fairness and depth are paramount.

• Balancing for Fairness: A game is fair when no player has an advantage at the start. This ensures competitive legitimacy. Symmetric games (e.g., hockey) are inherently fair. Asymmetric games (e.g., “StarCraft” races, chess with White going first) require careful balancing. Some games are deliberately unfair to explore history or create humor (“Cosmic Encounter”).
• Balancing for Depth: A deep game generates nuanced decisions where even experts are unsure of the best answer. The goal is not to make all tools equally powerful in isolation, but to balance the strategies among which the player chooses in any given situation. This encourages complex thinking about multiple variables and contingencies, pushing the skill ceiling.

Balancing for Other Reasons

Balance changes must also consider their impact on narrative coherence, flow, pacing, accessibility, and clarity. For example, a balanced but unrealistic weapon or a fair but tedious movement speed can harm the overall experience. Balance affects everything, so trade-offs must be carefully managed.

Degenerate Strategies

A degenerate strategy is a strategy that is obviously the best choice in a given decision, effectively removing meaningful choice (e.g., an overpowered “Chuck Norris” unit). Degenerate strategies reduce depth and can be hidden in complex emergent interactions (e.g., the “Elixir of Speed” in “Morrowind” allowing players to instantly kill dragons). Players constantly hunt for these imbalances, but paradoxically, they hate designers for allowing them to “destroy” the game when found.

The Viable Strategy-Counting Fallacy

The author argues against the idea that the goal of balance is to maximize the number of viable strategies. Once a game has more than one viable strategy, simply adding more doesn’t automatically improve depth or decision richness (e.g., “rock-paper-scissors-lizard-Spock” vs. traditional RPS). The real goal is to create a rich thought process inside the player’s mind, which is achieved by making the decision process more nuanced, not just by increasing options.

Balance and Skill

A game balanced for one skill level may be imbalanced for another because players at different skill levels have access to different strategies. What is degenerate for an expert might be a fascinating mystery for a novice. Conversely, strategies that make a game balanced at high levels (e.g., “rushes” in “StarCraft II”) may seem imbalanced to novices who lack the counter-skills.

Who to Balance For

It’s nearly impossible to make a skill-driven game balanced for players of all skill levels. Designers must target a specific skill level and accept imbalances at others.

• High-skill balance: Costly (exhaustive testing, vetoing fictional ideas, allowing low-skill imbalances), but non-negotiable for games of mastery (“StarCraft II,” “Counter-Strike”).
• Low-to-medium skill balance: Cheaper, as degenerate strategies are less likely to be found or exploited by casual players. Appropriate for narrative-driven games where meaning comes from non-skill-dependent emotional triggers (“BioShock,” “Morrowind”).

Balance Challenges and Solutions

The fundamental challenge of balance is that tuning one mechanic changes all the strategies it’s involved in, not just the intended ones. Games are complex systems where changes ripple through exponentially.

• Core Principle: Identify essential aspects of a tool, lock them in place at extreme values, then balance by adjusting non-essential properties or creating new mechanics to strengthen/weaken it. This makes tools distinct and expands the strategy space.
• Cut as deep as needed: If a tool cannot be balanced without compromising its core identity, it’s often better to remove it entirely rather than weaken it with inelegant rules (“Blizzard’s” approach to the “Thor” unit in “StarCraft II”).
• Don’t be reactive: Avoid rushing to fix single problems, as this often creates more problems elsewhere. Balance changes should solve more problems than they create, considering both explicit and implicit goals.
• Have a Nigel Tufnel moment (Turn it up to 11): Periodically push mechanics to extreme, seemingly “mad” levels to discover new opportunities and prevent the game from becoming flat and predictable.
• Use feedback to gather player experiences, not suggestions: Playtests should reveal how the design works in action, not just what players think should be changed.
• Build a mental model of how the game works as a system: Understand all possible experiences a game can generate through extensive playtesting before making balance decisions.

Chapter 7: Multiplayer

This chapter delves into the complexities of multiplayer game design, focusing on game theory, strategy interactions, and managing player behavior.

Game Theory

Game theory is a field of mathematics that analyzes the interaction between moves and countermoves in multiplayer games. It helps understand situations where players must anticipate and respond to one another’s decisions, whether competitive or cooperative. It shifts the game from pure mechanics to anticipating and deceiving other intelligent minds.

Games and Strategy Interactions

Game theorists use “game” to mean a specific interaction between strategies (e.g., one round of rock-paper-scissors), while game designers use it for an entire system of mechanics. The chapter uses the term “strategy interactions” to refer to the game-theoretic concept. Game theory is best applied to specific, short interactions rather than entire game designs.

Nash Equilibria

A Nash equilibrium is a configuration of strategies where no player can improve his own result by changing his strategy alone. Play tends to gravitate towards Nash equilibria because they are stable.

• One pure Nash equilibrium is a broken game design, as it leads to monotony; players always know what to do, eliminating strategic decision-making.
• Multiple equilibria are better, as players must anticipate others’ choices.
• The best outcome is to eliminate pure Nash equilibria entirely, forcing players into constant anticipation, deception, and psychological mind games (e.g., the castle battle example).

Rock-Paper-Scissors and Matching Pennies

Interactions without pure Nash equilibria are crucial for compelling multiplayer design.

• Rock-Paper-Scissors (RPS) pattern: A triangular counter-move structure (A beats B, B beats C, C beats A) common in symmetric games (e.g., fighting game block/punch/throw). This is the simplest way to create a symmetrical game without a pure Nash equilibrium.
• Matching Pennies pattern: Used in asymmetrical games where one player wants to match the other’s choice, and the other wants a mismatch (e.g., defender guessing attacker’s entry point). The “StarCraft II” example of Mutalisk/Marine vs. Baneling/Siege Tank interactions illustrates a complex matching pennies scenario, where no pure equilibrium exists, driving continuous strategic anticipation.

Mixed Strategies

While some games have no pure Nash equilibrium, they can have a mixed Nash equilibrium, where players randomly choose from strategies with specific probabilities. For example, in penalty kicks, a kicker’s optimal strategy is to randomly choose his strong and weak sides with certain frequencies. In equilibrium, each possible move has an equal average payoff. Players intuitively find these mixed strategies in real life, even without numerical analysis.

Yomi

Yomi is the mind game of predicting, deceiving, and outwitting an opponent to gain advantages beyond pure game theory math. It thrives where the real world is fuzzier than mathematical models, with unquantifiable payoffs and non-cleanly divided strategies.

• Smoothly blending between strategies: Games with nuanced strategies that can be combined in infinite ways (e.g., precise unit mixtures in “StarCraft II”) foster yomi, as experts can exploit minute differences.
• Complex, difficult-to-quantify payoffs: When strategy outcomes depend on multiple variables (unit costs, positioning, context, skill differences), evaluating payoffs becomes a profound logical and emotional challenge, pushing the skill ceiling.
• Psychology of randomness: Humans cannot generate perfect randomness, allowing players to exploit biases in opponents’ “random” choices.
• Manipulation of information: Players seek, deny, or plant false information (e.g., scouts, smoke grenades, phantom units) to deceive opponents. This can lead to multi-layered deception.
• Small player counts: Yomi requires mentally modeling opponents, which is difficult beyond 2-3 players. Large games can foster yomi by temporarily isolating smaller groups of players.

Yomi Case Study: Modern Warfare 2

“Modern Warfare 2” appears to be a simple shooter, but its popularity stems from its yomi-driven gameplay.

• Core interaction: Players enter a matching pennies game when out of sight, deciding which entrance to watch or take.
• Fuzzy edges: The game offers numerous options beyond simple choices, like varying watch patterns, movement within cover, or charging out.
• Information hidden by speed: Players must make rapid decisions without full information, relying on intuition.
• Lethal weapons: One or two shots kill, making pre-engagement decisions critical. Yomi thrives when players are out of sight, guessing enemy locations and intentions.
• Complex payoffs: Outcomes depend on player position, weapon types, special tools, team communication, objective goals, and individual skill, creating breathtaking complexity in decision-making.
  The game is cerebral, not mindless, as players engage in an intricate dance of mental evaluation and counter-evaluation.

Destructive Player Behavior

In multiplayer games, player-invented goals can destroy the game for everyone because they disrupt finely balanced structures.

• Divergent Goals: Players pursue goals that break others’ experiences (e.g., focusing on kills instead of objectives in “Modern Warfare,” or a player trying to “solo” a cooperative game). Griefing is deliberately destroying others’ play experiences for one’s own entertainment. Solutions include aligning divergent goals with official ones, using large player counts as a buffer, making griefing impossible (e.g., allowing players to pass through each other), or policing mechanics (voting systems, moderators).
• Skill Differentials: Large skill gaps between players cause conflicts, as unskilled players are pressured and skilled players are bored or annoyed. Solutions include:
  • Simple, elegant design: Reduces the skill barrier.
  • Matchmaking algorithms: Pair players of similar skill.
  • Structural solutions: Allow solo play for newcomers before group play (“World of Warcraft”), or offer single-player modes for practice.
  • Adaptive training: Provide on-the-spot guidance to novices (“Left 4 Dead”).
  • Reducing interdependency: Systems that permit shared victory without enforcing shared failure (e.g., optional, short-term alliances in shooters).

Chapter 8: Motivation and Fulfillment

This chapter distinguishes between dopamine-driven motivation and intrinsic fulfillment, exploring how games can effectively motivate players and the ethical implications of doing so.

Dopamine Pleasure

Historically, dopamine was thought to be the marker for pleasure, based on experiments where rats and humans self-stimulated their brains for “overwhelming euphoria.”

Dopamine Motivation

Later research revealed that dopamine is actually the marker for motivation, not pleasure. It surges before a reward, driving the pursuit of a goal. Studies show that individuals can “want” something (motivated by dopamine) without “liking” it (experiencing pleasure), and vice versa. Games leverage this by creating the anticipation of rewards, motivating players to push through obstacles.

Rewards Anticipation

Games generate dopamine motivation by creating the anticipation of rewards. While real-world rewards (food, money, safety) are powerful, virtual rewards (experience points, in-game currency, equipment, story content, high scores) also elicit dopamine, as the brain doesn’t distinguish real from virtual. These virtual rewards motivate players to keep playing despite the inconsequential nature of the game.

Reinforcement Schedules

A reinforcement schedule is a system of rules that defines when rewards are given. B.F. Skinner’s work on operant conditioning showed that different schedules drastically affect behavior.

• Fixed Ratio: Rewards are given at a fixed ratio to actions (e.g., gold every 10th orc defeated). Poor motivators, as they encourage bursts of activity followed by dips.
• Variable Ratio: Rewards are given after a randomized number of actions (e.g., 10% chance of gold per orc). The most powerful simple schedule, maintaining high, consistent activity due to constant hope for the next big payoff (e.g., gambling, slot machines).

Other Reinforcement Schedules

• Fixed Interval: Reward available after a fixed time. Leads to low motivation until reward is almost ready.
• Variable Interval: Reward available after a randomized time. Creates continuous, but lower intensity, motivation.
• Differential Reinforcement of Low/High Response Rate: Rewards for specific rates of activity.

Superimposed Reinforcement Schedules

To eliminate motivation dips, games often run several reinforcement schedules simultaneously. When one schedule has a motivation gap, others are at their peak, keeping players continuously engaged. “Grinding RPGs” use this by offering constant minor rewards (loot, levels, crafting) that always lead to another reward just minutes away. “One more turn syndrome” in strategy games like “Civilization V” results from dozens of superimposed schedules, ensuring constant motivation. The key is to prevent players from focusing on just one schedule, keeping them desynchronized.

Emergent Reinforcement Schedules

Most reinforcement schedules in games are not explicitly designed but emerge from lower-level game systems. For example, in chess, the variable pacing of piece captures creates an emergent variable ratio reward schedule. In deathmatch games, random kill counts can resemble variable ratio schedules, motivating continuous play. Players respond to emergent schedules just as they do to explicit ones.

Extrinsic and Intrinsic Motivation

Extrinsic rewards are separate from the work itself (e.g., money for completing a task). Intrinsic rewards are inseparable from the activity (e.g., enjoying fighting an orc for its own sake).

• Extrinsic rewards can displace and even destroy intrinsic motivation. Studies show that paying for an intrinsically enjoyable task can make people lose interest in it once the reward is removed. This effect is strongest for exploratory or creative tasks.
• Perverse incentives: Extrinsic rewards can create destructive competition, fear, and selfishness among developers, hindering creativity.
• Distraction: They pull minds away from the work, filling valuable headspace with reward maximization calculations.

Rewards Alignment

The key to using rewards without destroying the play experience is rewards alignment: how closely the activities encouraged by a reward system resemble those the player would have engaged in without it. Only reward things the player already wants to do.

• Easy alignment: Racing games rewarding faster times.
• Difficult alignment: Creative or social games where intrinsic goals are hard to detect and reward (e.g., making a city like one’s hometown in “SimCity”).
• Crafted alignment: “Skate 3’s” trick scoring system accurately judges impressive trick sequences, aligning perfectly with players’ intrinsic desire to perform cool tricks. The game also uses special modes for non-standard goals like racing or injuring the skater.

Player’s Remorse

Player’s remorse appears after a player spends time on a game that motivates them but does not fulfill them. This is an ethical concern, as games can exploit prehistoric dopamine triggers (like gambling) to compel irrational, self-destructive behavior (e.g., losing jobs, spouses).

• Compulsion machines: Games that prioritize maximizing motivation over fulfilling players. Ian Bogost’s “Cow Clicker” parody illustrates a game designed purely around a naked fixed interval reinforcement schedule.
• Ethical dilemma: Designers must consider their responsibility when creating games that can lead to player’s remorse, especially for vulnerable populations like children. The author suggests that building “Skinner boxes” is not the goal of designers who care about their craft; long-term sustainability requires offering new ideas, friends, and experiences.

Chapter 9: Interface

This chapter emphasizes that “that which is never communicated might as well never have occurred at all” in game design. It explores how games use screens, speakers, and other devices to structure and sequence information for players, and how players signal their intent to the game.

Metaphor

Metaphor is giving something new the appearance of something familiar to make it easier to understand. The entire fiction layer of a game acts as a giant metaphor, wrapping complex mechanics in familiar images (e.g., “folders” on a computer, “growing cities” in a city builder) to ease the learning curve.

Metaphor Sources

Metaphors leverage pre-existing common knowledge from various sources:

• Real objects: Cars, people, books, backpacks.
• Cultural archetypes and conventions: Pointy goatees signify evil, square jaws signify bravery.
• Game clichés and conventions: Food instantly heals gunshot wounds, golden armor is stronger. These are useful for communicating arbitrary systems, but can be indecipherable without prior knowledge.
• Logical systems: Newtonian physics, electricity, fire. Imitating these complex but understood systems provides an elegant, low-learning-burden foundation.
• Higher-level concepts: Economics, politics, biology, psychology (e.g., supply and demand in “Privateer”).
• Abstract mathematical systems: Numbers, time, space (e.g., chess board layout leveraging spatial reasoning).

Metaphor Vocabulary

Only a small subset of a real object’s functionality is implemented in game mechanics. Players need to know which aspects of the fiction are mechanically simulated and which are just dressing. A game must establish a metaphor vocabulary—a consistent set of visual or audio cues—that indicates which elements are interactive or mechanically relevant (e.g., specific climbable bricks in “Prince of Persia”). This prevents players from making wrong assumptions and avoids the “adventure game problem” where plausible fictional solutions don’t work in the game.

Signal and Noise

Noise is signal that fails to transmit meaningful information. When players are overwhelmed or confused, signals degrade into noise.

• Noise and Art Complexity: Complex art, whether visual or audio, introduces noise by filling the world with details unrelated to game mechanics. This makes important elements harder to discern (e.g., graybox levels becoming unintuitive with full art). It requires cooperation between designers and artists to create art that is both compelling and clear, sometimes through unique art styles that naturally minimize noise (“Team Fortress 2,” “Mirror’s Edge”).
• Overcrowded Signals: Players can only absorb a certain number of signals at a time. Adding too many signals past this limit overloads the player.

Visual Hierarchy

To manage signal density, games use a visual hierarchy, where more important pieces of information are made more visible so players notice them first. This leverages the unconscious human tendency to prioritize bigger, closer, brighter, and faster elements. It allows players of different skill levels to automatically perceive only the information useful to them, without being overwhelmed or denied crucial data. Examples include:

• Enemies being large and central.
• Distant enemies being smaller.
• Health indicators changing visibility based on criticality (red overlay at low health).
• Ammo counts being placed in corners but made more visible when low.
  Designers tune visibility (brightness, loudness) to match importance, ensuring continuous learning and engagement.

Redundancy

Since players inevitably miss important signals, redundancy means sending critical information multiple times.

• Homogenous Redundancy: Repeating the same message in the same way (e.g., same audio log in five places).
• Diverse Redundancy: Communicating the same information in different ways (e.g., companion yelling, visual wave, highlighted path, HUD objective marker). This “quadruple redundancy” increases the likelihood the message gets through.
• Passive Redundancy: Showing secondary messages only when the primary message fails.

Indirect Control

Indirect control methods guide player behavior without the player realizing they’re being guided.

• Nudging: Changing how choices are presented (e.g., default options, lit doorways) without changing the choices themselves. Players naturally follow the path of least resistance.
• Priming: Activating concepts in the player’s mind to influence future behavior (e.g., war movie ads making one more combative, politeness-related words making one more polite). In games, seeing a doctor primes for healing; combat priming can make players shoot informants. Priming shifts preferences but doesn’t fabricate motivation.
• Social Imitation: Players naturally imitate the actions of others, whether NPCs (e.g., computer-controlled cars slowing for curves) or other players (e.g., strategies in multiplayer). Companion characters are invaluable for this, guiding players to objectives or specific behaviors.

Input

The goal of input design is to achieve synchronization between a player’s intent and in-game action. Good input makes interaction a pleasure, while bad input can destroy even great games.

Control Arrangement

• Mapping: Creating a similarity between a physical control and its in-game effect (e.g., left trigger for left-hand spell). This serves as a mnemonic, reducing learning burden. Expensive physical interfaces like the Wii remote or Rock Band guitar appeal to casual players through close mapping.
• Control Exclusivity: Matching physical control limitations with in-game action exclusivity (e.g., unable to change weapons and fire simultaneously if mapped to exclusive buttons). This prevents frustration and naturally teaches game mechanics.

Control Feel

Control feel is the moment-by-moment experience of projecting intent through an interface. It involves intricate, often unrealistic, underlying rules that enhance the player’s sense of control. “Super Mario Bros.” jump mechanics, for example, involve variable gravity, midair control, and input buffering to create a joyful, responsive feel. These hidden complexities are an exception to elegance; they are expensive to design but invisible to players, making the interface “vanish.”

Input Assistance

Input assistance pre-processes raw player input to intelligently guess intent and nudge input to match it, ideally without the player noticing. Aim assist in console shooters is a prime example, using interleaved subsystems to help track targets, stop crosshairs over targets, and subtly shift aim direction. These adjustments occur in “nooks and crannies” of the input stream, imperceptible to players. Aim assist can also serve as a balancing factor, subtly weakening weapons in unintended use cases.

Control Latency

Control latency is the time delay between input and perceptible feedback. It is unavoidable due to hardware processing pipelines (typically 3-4 frames). Poorly written code can exacerbate this.

• Frame Rate: The choice between 30 fps and 60 fps (or higher) affects latency. 60 fps offers lower latency (50-67 ms vs. 100-133 ms), making games feel more responsive, but comes at a significant cost in processing power for graphics.
• Player Compensation: Players learn to anticipate latency by inputting commands slightly early. Longer latencies require more anticipation, feeling less synchronized.
• Design Choice: The ideal frame rate depends on player skill (high-skill players need 60 fps for rapid-response games like shooters/fighters), interface type, and emotional triggers. Visual- or narrative-driven games might stick to 30 fps for richer graphics.
• Political Bias: There is often internal pressure against 60 fps due to its direct impact on artists and programmers, despite its benefits being harder to perceive. Designers must advocate for it when necessary.

Designing Input

Input is hard to design because it’s hard to perceive and its complexities are deliberately hidden from players. Its importance is often underestimated, leading to underinvestment. However, input is almost always worth the investment because it fundamentally shapes the player’s moment-by-moment experience, even if it goes unnoticed.

Chapter 10: The Market

This chapter explores how market considerations profoundly influence game design, emphasizing that a game’s purpose and market positioning must affect its design.

Design Purpose

Every game is created to serve a purpose, whether profit (sales, subscriptions, microtransactions) or non-monetary goals (art, academic experiments, self-amusement). Every design decision is affected by this purpose.

• Arcade games: Designed for quick profit, using fast, visually expressive mechanics, short playtimes, simple controls, and elastic success conditions to encourage repeat plays.
• MMO games: Aim to retain players monthly, featuring massive content and deep upgrade systems, plus social/community features.
• Traditional shrink-wrapped games: Focus on sales, driven by good reviews and word of mouth, encouraging “purest” game design for great experiences.
• Noncommercial games: Focus on expressing ideas or specific concepts.
  New business models constantly emerge, each posing unique design challenges.

The Tournament Market

Game designs are nonrival goods (can be copied infinitely at near-zero cost), making the games market a winner-take-all tournament. The single best game can capture the entire market, leaving others with nothing. This creates immense rewards for winners (e.g., “Call of Duty: Black Ops” taking in billions) but hides the vast number of losers.

The Matthew Effect

The Matthew effect (the rich get richer) means popular games gain advantages:

• Antirival nature: Games get better the more people play them (stronger community, more partners, more user-made content).
• Developer advantages: Successful studios gain money, credibility, and status for future projects.
• Consumer bias: Familiar titles beat unknowns in even competition.
  Despite this, dominant franchises are regularly overturned.

The Innovator’s Dilemma

The innovator’s dilemma describes the hard choice for incumbent leaders: keep innovating by abandoning flagship products, or don’t and wait for someone else to innovate. Successful studios become hobbled by internal inertia, shareholder demands, entrenched habits, and fear of loss, losing their creative fire. This counterbalances the Matthew effect, as smaller, unburdened upstarts can take risks and innovate, eventually overthrowing the static incumbents.

Market Segments

A market segment is a group of players defined by their interests, skills, price range, culture, technology, and geography. The size of the target segment affects potential payoff (e.g., “Half-Life” appealing to a broader action-oriented segment vs. “System Shock 2’s” smaller hardcore RPG segment). Larger segments mean more competition, tending to balance profitability over time.

Underserved Market Segments

The market is not in perfect equilibrium, meaning underserved market segments offer abnormal profits to those who can find them. This is difficult and risky, as there are no established players or conventions. Will Wright’s “The Sims” is a prime example: initially rejected by focus groups and executives as “The Toilet Game,” it found a massive, unserved market segment for “family management games,” becoming the top-selling PC franchise in history. Finding empty segments requires big bets and a lot of luck.

Value Curves

A market value is an aspect of a game experience that appeals to a group of people. Games often offer multiple market values (e.g., “The Sims” offers “creative home building” and “life role-play”). A value curve is a graph that compares games by rating them on different kinds of market value. It helps identify unique, superior, and overlapping values. The important values in a game are those superior to every other market offering, especially those with no competition. “BioShock,” for example, succeeded by offering unique values like its “art deco world” and “Big Daddy/Little Sister ecology.”

Value Focus

Every value costs resources, and too many values can lead to an overcomplicated, diluted experience or even incompatibility. Great games do a few things very well.

• Resource allocation: Designers must focus resources where they can do the most good. Smaller teams must focus on fewer values.
• Spiky value curves: Successful small games often have tall, narrow value curves, relentlessly focusing on one or two values underserved by bigger games (“Garry’s Mod,” “Super Meat Boy,” “Minecraft”).
• Stump-shaped value curves: Failed games often try to do too many things, resulting in mediocre versions of bigger games with no unique value.
  Match ambition to resources: It’s better to be the best at one thing than mediocre at ten.

Nobody Knows Anything!

Market models are simplifications; the real market is immensely complex and unpredictable. Factors like celebrity endorsements, news stories, or political trends can dramatically change a game’s performance. Most of what happens in the market is outside any model. “StarCraft’s” meteoric rise in South Korea, driven by PC bangs, broadband infrastructure, and existing Go TV channels, was an unpredictable “Korean miracle.” This illustrates screenwriter William Goldman’s “Nobody knows anything!” mantra: we can only guess at the true causes of market success, even after the fact.

Confirmation Bias

Confirmation bias is the tendency for people to perceive things in a way that confirms their preexisting beliefs. Expectations, set by marketing, titles, and word of mouth, profoundly affect the play experience. A beer described as bad tastes bad, even if it’s superior. Similarly, if a game is reviewed as “satisfyingly challenging,” players will interpret frustrating losses as intentional design. Designers cannot ignore marketing, as it shapes player perception before play even begins.

Setting Expectations

Setting expectations is critical for designers, as it prepares players for the best possible experience.

• Game title: The first expectation setter (e.g., “Doom” vs. “SimCity”).
• Marketing messages: Advertisements, interviews, and articles set expectations for characters, action, mood, and themes.
• Word of mouth: The most powerful, amplified by social pressure, as players synchronize opinions and adjust memories to match consensus.
  Designers must craft titles and marketing messages to align with desired player expectations, treating marketers as core experience-crafting team members.

Chapter 11: Planning and Iteration

This chapter explores the challenges of planning in game development, contrasting overplanning and underplanning, and advocating for an iterative approach.

The Overplanner

Overplanning involves writing meticulous design documents that describe every detail months or years in advance. This approach leads to problems when the game’s reality (discovered through playtesting) inevitably deviates from the plan, forcing designers to either trash their work or ignore new discoveries.

The Underplanner

Underplanning involves diving into development with minimal prior planning. This leads to issues like wasted work (e.g., artists creating unneeded assets), poor team coordination (incompatible subsystems, incoherent design), and inability to communicate with external stakeholders (investors, marketers). The game becomes an “unfocused Frankenstein’s monster.”

Underplanning and Overplanning

Both extremes are dangerous. Underplanning leads to process disintegration, while overplanning causes plans to fall apart on contact with reality. The solution lies in iteration.

The Costs of Underplanning

• Wasted work: Doing tasks that are later found unnecessary or obsolete.
• Poor team coordination: Incompatibilities between different people’s work due to lack of a clear overall vision.
• Starving external stakeholders: Inability to provide information needed by investors, marketers, and hiring managers.

The Costs of Overplanning

• Time and effort: Writing, debating, and maintaining extensive plans is a massive burden.
• Cutting costs: It’s psychologically and politically difficult to cut ideas from a detailed plan, leading to repeated “costs of cutting.”
• False sense of certainty: Written plans are often treated as guaranteed visions, but they are laden with assumptions. When these assumptions prove false, changes cascade exponentially through the design, leading to missed deadlines and crunch (e.g., “Halo” transforming from a strategy game to an FPS, “BioShock” changing from a spaceship to an undersea city). Game design is inherently uncertain, and plans rarely survive contact with reality.

Iteration

Iteration is the practice of making short-range plans, implementing them, testing them, and repeating. Instead of a linear process, it’s a continuous loop where assumptions are checked against reality. This reduces the need for deep future prediction and provides reliable knowledge for the next loop. Iteration can apply to an entire game or individual elements like levels or tools.

Iteration Example

The author describes an iterative process for developing combat scenarios in FPS games:

• Rapid prototyping: Quickly rough in a basic fight (in graybox) to get it playable as soon as possible, even if it’s “awful.” This first version serves as a “platform from which to jump.”
• Quick cycles: Iterate rapidly, making large conceptual changes (e.g., changing a tower to a bridge) and retesting within minutes or hours.
• Refinement: As the concept solidifies, the loop lengthens, and changes become smaller (e.g., adjusting cover positions).
• Involving artists: Consult on artistic feasibility, making art-friendly adjustments.
• Playtesting with others: Once self-testing no longer yields new insights, bring in external playtesters (Kleenex testers for early reactions, dedicated testers for high-skill balance). Observe without interference.
• Expanding the loop: Incorporate other disciplines like audio, dialogue, and world narrative.
  This process exchanges deep planning for continuous reality checks, adapting to unpredictable test results.

Planning Horizon

The planning horizon is the length of time a designer plans into the future.

• Uncertainty drives short horizons: When plans are highly uncertain (e.g., original games), the horizon should be short (days or less).
• Certainty allows long horizons: Unoriginal or derivative games can be planned further ahead due to established knowledge.
• Lengthening over time: The planning horizon typically lengthens as a project progresses and core elements become more certain.
• Cost of testing: Low testing costs allow shorter horizons and more experimental approaches.
• Conceptual leaps: Deep planning (without testing) can enable radical new ideas, but is risky.

Why We Overplan

• Cultural Habit: Society indoctrinates us with the value of planning, which works well for certain tasks (e.g., building a dam) but not for inherently uncertain game design.
• Inborn Overconfidence: Humans have an optimism bias, making us overconfident in our predictions (e.g., a 90% confident estimate might only be 30% accurate). This leads to thinking we can plan things we cannot.
• Therapeutic Planning: Planning is done not to coordinate work, but to alleviate anxiety about an uncertain future, creating a false sense of certainty.
• Group Planning Bias: Groups reward confident, seemingly decisive leaders over rationally uncertain ones, even if the confident predictions are delusional.
• Hindsight Bias: Memories are silently rearranged to make past events seem more predictable than they were, preventing learning from mistakes and reinforcing the belief that deep planning is possible.

Test Protocol

The testing stage is critical for iteration, as it reveals how the game design works in action. A test protocol is a set of rules and procedures for carrying out a playtest. Poorly designed protocols can miss critical flaws or actively mislead designers.

• Self-Testing: Cheapest protocol, reveals many problems in flow, pacing, and balance, and finds technical bugs. Good for early iteration loops.
• Over-The-Shoulder Playtesting: Designer observes other players. Better than self-testing as players have less knowledge and varied reactions. Crucially, the designer must remain silent to avoid corrupting the test.
• Choosing Playtesters: Select testers based on their knowledge of the game (Kleenex testers for initial reactions, dedicated testers for high-skill balance) and demographic profile (age, gender, culture) to match the target market.
• Sample Size: Many playtests are needed to build a broad mental model of the game’s different experiences. Stop when testers consistently repeat the same experiences.
• Questioning Technique: Verbal reports are unreliable. Use memory probes (“Tell me the story of what just happened”) and indirect questions (“Why did you choose that path?”) to understand players’ internal experiences without biasing them. Maintain a professional, open tone.

Grayboxing

Grayboxing is creating low-fidelity placeholder versions of game mechanics, systems, or levels.

• Speeds iteration: Allows rapid testing and iteration without investing in costly art and audio for unproven designs.
• Fluid work: Keeps the design flexible for large conceptual changes.
• Artist involvement: Artists can consult during graybox, ensuring artistic feasibility and preventing wasted effort.
  What Not to Graybox: Less useful for audiovisual-driven experiences (e.g., “LIMBO”) where art and music are primary emotional triggers.

Premature Production

Premature production is adding art and audio to a graybox design before it is necessary to get the next round of test data.

• Short-lived benefit: Visuals create an immediate, but fleeting, emotional boost.
• Long-term cost: Slows down future iterations by requiring constant reworking of art to match changing mechanics.
• Limits quality: Hides weak mechanical cores, making them difficult to fix later without tearing off costly art.
  Discipline is required to stay in graybox until the mechanics are proven.

Graybox Evaluation Skill

Evaluating grayboxes requires a learned skill, as a good graybox doesn’t “feel” like a good finished game. Without this skill, designers (especially those without practice) may reject excellent graybox designs simply because they lack visual polish, due to the halo effect. This can lead to poor design decisions.

The Screenplay Metaphor

The author argues that the closest game design equivalent of a screenplay is a working graybox prototype, not a design document. A screenplay allows one to imagine the film by filling in audiovisual details. A design document, however, describes mechanics, requiring complex mental simulation of player choices and system interactions, which is beyond human capacity. A graybox, by handling the mechanical simulation, allows the mind to focus on imagining the visuals, similar to reading a screenplay.

The Paradox of Quality

In game design, temporarily accepting poor-quality work ultimately leads to better-quality work. An obsession with quality at every early stage slows down iteration, resulting in fewer iteration loops and ultimately a poorer final product. Everything in game design gets revised and rebuilt many times, so early work is just a “platform” for future improvements.

The Fallacy of Vision

The fallacy of vision is the idea that a mental movie of an experience is equivalent to a design for a system that generates that experience. While visions can be inspirational, they are misleading because they don’t account for the system’s trade-offs, costs, or other experiences it will generate. Visions naturally hide flaws and cherry-pick best outcomes, leading to overconfidence and overplanning. The antidote is to envision the worst possible experiences to get a balanced picture.

Serendipity

Unknown unknowns (things we don’t know we don’t know) are crucial in game design. Disasters can arise from them, but so can serendipity—positive, unexpected discoveries that are often the most valuable things in design. Many revolutionary game designs are stumbled upon, not authored (e.g., “Dungeons & Dragons” leading to “Rogue,” “SimCity” leading to “The Sims,” “Portal’s” GLaDOS voice). Iteration is robust against unknown unknowns and allows designers to capture serendipity by adapting to new discoveries. Designers must be observant and adaptable, reorganizing their thoughts around observations rather than forcing observations to fit a worldview. Game design is a process of observation and discovery, not just authorship.

Believing in Iteration

The author notes that most designers only truly believe in iteration after experiencing years of failures caused by deep planning. This often requires taking a game all the way to completion and releasing it to real players to get the incontrovertible, painful feedback that changes emotional beliefs.

Chapter 12: Knowledge Creation

This chapter frames game design as a process of inventing and refining knowledge about the design, rather than just physically implementing it. It explores various methods for creating this knowledge.

Knowledge Creation Methods

Knowledge creation methods are tools like playtesting, brainstorming, discussion, debate, and daydreaming. Mastering design process means knowing which method to use and when, reacting continuously to project conditions.

Rumination

Rumination means thinking about a problem for an extended period of time, often unconsciously (e.g., in the shower, while sleeping). It forms new connections between old ideas.

• Requires knowledge: A large store of diverse ideas (from games or unrelated fields) feeds rumination, as humans think by analogy.
• Requires relaxation: Anger, fear, and intense focus inhibit creativity at a neurological level, suppressing free association.

Research

• Targeted research: Answering specific questions (e.g., medieval architecture for a game setting).
• Semi-random research: Learning without knowing specific applications, expanding one’s general knowledge to feed rumination. To avoid cultural homogeneity, designers should cultivate unusual interests. “BioShock’s” unique world (Rapture, Objectivism) emerged from such research.

Artistic Methods

Artistic processes can create new ideas by keeping hands working while recording thoughts.

• Concept art: Explores characterization, mood, or space.
• Storyboards: Clarify framing and sequencing.
• Previsualizations: Explore communication of ideas.
• Sculpture: Creating creatures or characters.
• Writing short stories: Generates ideas for world narrative.
• Improv skits: Explores character.
• Soundscapes: Explores audio ideas.
  These methods leverage physical action and mistakes to force new ideas, much like Orson Scott Card’s map-driven world-building.

Brainstorming

A semi-formalized process to quickly produce large numbers of diverse ideas. Good for generating volume, bad for refining quality.

Written Analysis

A form of structured thought, where writing documents pushes designers to think about details in a way that informal discussion doesn’t. Deep analysis can involve formal methods and research.

Debate

Debate specifically finds flaws in ideas, akin to legal or scientific processes. It requires:

• Skilled debaters: Able to attack and defend arguments effectively.
• Diversity of thought: Participants with different knowledge, opinions, and assumptions.
• Respect: Ability to separate personal feelings from logical process.
• Absence of fear: Power imbalances can corrupt debate, as subordinates may not debate honestly.

Testing

Various types of testing provide different kinds of knowledge:

• Usability testing: Focuses on interfaces and controls.
• QA testing: Finds technical bugs.
• Focus testing: Market research on product ideas (not a working game).
• Metrics: Automatically collected data (e.g., loot, completion times) from play sessions. Invaluable for fine-tuning small patterns and finding rare edge-case situations. “Half-Life” used metrics for difficulty balancing, and “Halo: Reach” used custom buttons to track perceived lag.

Invented Methods

When established methods fail, designers must invent new ways to get the knowledge needed, going back to first principles.

The Organic Process

The chapter uses the Wright brothers’ invention of the airplane as a metaphor for game development, highlighting their mastery of knowledge creation. They didn’t just build; they iterated relentlessly, inventing new testing methods (wind tunnel, bicycle apparatus), learning from hundreds of flights, and combining diverse knowledge (mathematics, aerodynamics, engineering, rumination, debate).

• Relentless iteration: Thousands of tests, continuous modification and learning.
• Diverse knowledge sources: Lab tests, field tests, mathematical calculations, rumination.
• Focus on missing pieces: Unlike competitors focused on engines, the Wrights identified aerodynamics and control as the missing knowledge.
• Serendipitous discoveries: Wilbur’s wing-warping insight from twisting a box.
  Game design is similar: a system, not an object. The author argues that the rigid “plan-build-test” iteration loop is an oversimplification. Real game design is organic, fluid, and unfathomable, with knowledge bubbling up constantly from every developer. Leaders can only direct broad strokes, as the reality is always more complex than the conception.

Chapter 13: Dependencies

This chapter focuses on understanding dependencies in game design to manage project risk and determine what to work on first.

What Dependencies Mean

A dependency is a relationship between two parts of the design such that changes in one part would force changes in the other. Game design elements are often interdependent (e.g., level art depends on level layout, which depends on player tools). Understanding dependencies helps reduce the risk of finished work having to change due to changes in foundational elements.

The Dependency Stack

A dependency stack is a simple analysis method that identifies key dependencies among design elements. It helps visualize which elements rely on others. To build it:

1. Break the game into individual elements (mechanics, controls, interfaces, subsystems).
2. Identify strong dependencies (where changes in A almost certainly affect B).
3. Draw a graph illustrating these relationships, with foundational elements at the bottom.
   The stack is reductive, focusing on the strongest dependencies to avoid analysis paralysis. It’s a tool for decision-making, not an academic exercise.

Cascading Uncertainty

Designs are inherently uncertain; they rarely work as expected on paper. This uncertainty multiplies through dependencies.

• Uncertainty multiplies: If an element has an 80% chance of working as expected, an element five layers up the dependency stack has only a 33% chance (0.8^5) of remaining unchanged due to potential shifts in its foundational elements. For risky, original designs, this means upper elements of a dependency stack almost always need major redesign.
• The chaos of development: This cascading uncertainty is the real culprit behind the massive, unpredictable changes and chaos seen in many game development processes.
• Strategy: Start at the bottom of the dependency stack and work upward through each iteration loop. Iterate and playtest foundational elements until they are highly certain, then build dependent elements on top of this solid base.

The Design Backlog

Because upper-stack designs are so uncertain, it’s inefficient to fully detail them. The design backlog is an unordered, liquid reservoir of ideas, concepts, and impressions that aren’t being worked on and won’t be worked on soon. Most ideas should go here. Only elements to be worked on soon should be incorporated into a fixed plan. This allows the design to grow upward, one solidified piece at a time, drawing from the backlog as foundations become certain.

Core Gameplay

Core gameplay is what emerges from the irreducible mechanics of a game at the bottom of its dependency stack. It’s the minimum set of mechanics that make a game emotionally worthwhile.

• Identifying core: Cut everything that can be removed without making the game meaningless. What’s left is the core (e.g., “Civilization V” core: map, cities, settlers, warriors; “Unreal Tournament” core: map, players, gun).
• Foundation of development: Core gameplay is the proper foundation of the dependency stack. Identifying and building it first provides a testable platform for early iteration, enabling the benefits of test-driven iteration sooner.
• Genre definition: Core gameplay often defines a genre (e.g., “tower defense” core: map, defense object, towers, enemies).
  Some games may have multiple possible cores (“Fallout 3” could be a shooter, a dialogue story, or an art gallery).

Small-Scale Dependency Stacks

The dependency stack can also be used to analyze individual systems or features (e.g., a character’s abilities). This helps identify the core components of a feature and determine the optimal order of development, especially when some elements are highly uncertain. Prioritize building the core components of a feature first, then add dependent elements from the backlog.

Dependencies and External Design Needs

A caveat: marketing and business stakeholders may need design decisions long before the game is ready. Designers must negotiate to find a middle ground, as providing highly detailed, high-stack decisions too early can be costly due to cascading uncertainty. It’s important not to lock a game design into unchangeable decisions based on external pressures.

Chapter 14: Authority

This chapter explores how organizational structure, authority, and trust within a game development team profoundly impact creativity and productivity.

The Banality of Evil

Organizational personality is shaped by structure. Poor structure can make individual geniuses act like “raging fools,” wasting talent. This highlights the importance of getting the structure right for good work.

Taylorism

Frederick Taylor’s “scientific management” (Taylorism) aimed to optimize work by concentrating all decisions in the hands of a few smart people (managers) and making workers follow precise, efficient motions. This works for simple, repetitive tasks where all knowledge can be held by one mind. However, Taylorism fails in game development because it involves massive amounts of complex, non-repetitive, and often tacit knowledge (e.g., an artist’s intuition, a programmer’s optimization skill) that cannot be centralized or fully communicated.

The Distributed Mind

Game development must function like an ant colony, where no one person can understand everything. Instead, authority must be distributed, with each developer playing a role in a collective, distributed mind. The “ant colony” is smart because individual ants follow simple, local rules, coordinating actions without a central plan.

Distributed Authority

For distributed intelligence to work, authority must be spread across the team. Each developer makes decisions about the work they are closest to, within their natural authority—the sphere where they are better equipped to make decisions than anyone else.

• Leveraging local knowledge: Each developer understands their specific task (level, tech, mechanic) in a way no one else does.
• Communication is key: Developers must communicate to share knowledge relevant to interdependent decisions. Meetings serve to pool unique knowledge for collective decision-making.
• Tacit knowledge: Much relevant knowledge is tacit (skills, intuitions) and cannot be fully communicated, reinforcing the need for the person with natural authority to make the final decision.

Arrogation and Trust

Arrogation is claiming a decision that falls under someone else’s natural authority, often taking the form of micromanagement. This leads to bad decisions because it discards the subordinate’s specialized knowledge.

• “Swoop and poop”: Leaders making demands based on limited understanding of the work, often due to the WYSIATI (what you see is all there is) cognitive bias. They overestimate their knowledge.
• Root cause is lack of trust: Leaders micromanage because they don’t trust subordinates to make good decisions. However, a leader cannot possibly cover all mistakes in a complex process. Trust is non-optional; leaders must hire trustworthy people and then empower them.

Communicating Intent

Leaders still play a necessary role by communicating the higher-level intent of the work, rather than micromanaging precise actions. This is borrowed from military leadership, where a captain specifies which hill to take, not how each soldier should move.

• Purpose: Intent communicates the goals and broader context of the work, equipping subordinates with information they wouldn’t otherwise have.
• Empowerment: By sticking to generalities, leaders allow subordinates to seize opportunities and solve problems locally in a way that best serves the broader purpose.
• Leader’s role: Leaders focus on understanding and iterating on the game’s macro structure (emotional goals, market strategy, design style).
• Subordinate communication: Subordinates must communicate summaries of newly gained knowledge upward to leaders, providing condensed, high-level lessons for broader structural decisions.
  This creates a purposeful, structured development where knowledge is applied efficiently, and decisions are made by those with the most relevant knowledge.

Chapter 15: Motivation

This chapter explores the complexities of motivating game designers, arguing against traditional extrinsic rewards and advocating for intrinsic drives like meaningful work.

Extrinsic Rewards

Extrinsic rewards are separate from the work itself, typically monetary incentives for measurable performance. They fail in game design for four key reasons:

• Difficulty in judging work: Game development output is complex and hard to measure objectively, making it impossible to accurately reward performance.
• Displacing intrinsic love: Money-based incentives destroy developers’ natural desire to create great games for their own sake, making them work for money instead of passion. This effect is strongest in creative tasks.
• Creating perverse incentives: Rewards can foster political games, destructive competition, fear, and risk aversion, hindering collaboration and innovation.
• Distraction: Developers spend valuable mental energy maximizing rewards instead of solving design problems. Threat of punishment is even worse, as fear neurologically inhibits creativity.

Meaningful Work

The most effective way to motivate designers is to offer meaningful work. Creative people want to apply themselves to work that makes a tangible difference. This requires:

• Creative outlet: Opportunity to express ideas.
• Balanced challenge: Work that is engaging but not overwhelming.
• Pride and recognition: Feeling good about one’s contributions.
• Ownership and responsibility: Autonomy over their work.
• Belonging and freedom: A supportive, trusting environment.
  Self-identified commitment is the “holy grail”—when developers believe the work is part of who they are, leading to relentless, internal drive (e.g., the Wright brothers). This force is often “strangled in the crib” by typical corporate environments.

Climate

Climate is the day-to-day emotions people feel about work.

• Productive climates: Foster energy, safety, risk-taking, and focus (e.g., taking risks is rewarded with credit or consolation).
• Bad climates: Lead to anger, fear, and blame-dodging, neurologically neutering creativity. Ideas remain buried because the perceived “cost” of proposing them (e.g., being misunderstood, shot down, micromanaged) outweighs the potential benefit.
  Bad climate is a silent killer, causing good things (risky ideas, necessary debates) not to occur, leading to bland, unoriginal games.

Fear and Love

• Fear-based leadership: Uses anger, insults, or threats to push people. Works in jobs focused on maintaining standards (e.g., a chef’s kitchen) but destroys creativity, risk-taking, and self-identified commitment in game development. Fear inhibits the brain’s creative centers.
• Love-based leadership: Leads by inspiration, collaboration, and appreciation (e.g., Jim Henson). Focuses on setting others up to succeed, fostering trust, and eliminating fear. This unlocks self-identified commitment, allowing developers to draw creative power from within.

Social Motivation

Beyond meaningful work, subtler social signals can provide targeted motivational pushes:

• Playtests-Driven Motivation: The pleasure of playtest success and pain of failure are powerful, natural motivators. They feel authentic, not manipulative, and provide objective feedback, pushing developers to excel beyond a boss’s judgment.
• Expectations-Driven Motivation: Treating people as if they will do good work drives them to do so. Fostering a sense of eliteness within a team (e.g., “Imagineers” at Disney) creates a positive identity and a precedent to live up to, encouraging excellence.
• Chicken Motivators: Nonserious, non-explicit social rewards or punishments can send messages without damaging climate (e.g., a rubber chicken for breaking the build). These are ridiculous but effective, low-cost ways to encourage desired behaviors.

The Progress Principle

Teresa Amabile’s research found that the strongest contributor to good inner work life is regular, visible day-to-day progress. The frequency of small wins (solving an algorithm, finishing an animation) is more important than their size.

• Organize for small wins: Structure the process to ensure everyone gets regular, visible achievements.
• Visual indicators: Simple methods like crossing off tasks on a wall create emotional boosts.
• Direct feedback: Allow developers to see their own progress without outside help (e.g., designers seeing their own playtests, programmers seeing automated tests pass).
  This principle applies equally to game developers as it does to game players, keeping them engaged and motivated.

Chapter 16: Complex Decisions

This chapter emphasizes that game design decisions often have far-reaching effects beyond the immediate game, impacting processes, people, businesses, and markets.

Decision Effects

• Design effects: How the decision affects players and the game itself (e.g., balance, pacing, emotion). This is the primary focus of most of the book.
• Implementation costs: Resources (time, effort) needed to execute the decision (e.g., writing code, making animations).
• Immaturity burden: Costs imposed on people working with incomplete or unstable parts of the game (e.g., buggy tools, unfinished story slowing down work).
• Critical failure risks: Costs from fatal flaws in immature systems going off at inopportune times, causing chain reactions of delays and problems across the team.
• Process burden: Cost of tracking and scheduling work, increasing with team size (e.g., dedicated production staff, bug tracking systems).
• Political effects: Impacts on relationships among developers, influencing who gets what resources or opportunities (e.g., irritating a senior programmer by not prioritizing graphics).
• Cultural effects: Changes to developers’ habits, expectations, and the overall development climate (e.g., frequent story changes degrading creative investment).
• Decision cost: The cost of making the decision itself (brain time, research, analysis). Unimportant decisions should be made quickly; important ones warrant careful consideration.

Decision Effects Case Study

The chapter presents a complex scenario: a designer in a fantasy shooter RPG (“Talmirian Gods”) discovers a degenerate strategy (endlessly circling a “Walrog” enemy with an “Elixir of Speed” upgrade). This scenario highlights how various decision effects intertwine:

• Design effects: Degenerate strategy makes combat boring, causes player laughter, affects game balance.
• Implementation costs: Fixing Walrog’s turning requires new, costly animations from an overworked team. Removing Elixir is cheap but requires a new reward.
• Immaturity burden/Critical failure risk: Un-tunable animation system creates uncertainty about the fix, risking more balance problems.
• Political effects: Removing Elixir might anger the author/investor (Allan McRae) who pitched it to journalists.
• Cultural effects: McRae’s past behavior (auteur approach, resistance to narrative changes for balance) creates a climate of uncertainty.
• Decision cost: Too much uncertainty to make a snap decision.
  The recommended solution is to gather more knowledge through low-risk actions (e.g., noncommittal talks with McRae and animators, brainstorming) before committing to a fix. This demonstrates that complex design problems often require managing uncertainty and political factors as much as technical solutions.

Chapter 17: Values

This chapter concludes the book by emphasizing that beyond knowledge and skills, exemplary game design requires a set of personal values that guide a designer’s choices and actions.

What Values Mean

A value is an emotionally driven choice about who we want to be, a human quality to aspire to. Values provide immutable standards that stabilize designers amidst the political and emotional turmoil of daily work. The author presents his own core values for game design.

Openness

Openness means respectfully accepting ideas with which you disagree. It involves genuine discussion, respecting contributions, and thinking meaningfully about every idea, even if not accepting it. It stems from believing in the inherent uncertainty of one’s own ideas, leaving room for others’ better insights.

Candor

Candor is having your own ideas and being willing to present them, even when it’s easier to remain silent. It requires moral courage to voice contrary opinions, even to superiors. Candor fosters honest discussion, preventing inconsistencies from creeping into the design due to excessive agreement or fear.

Humility

Humility means accepting how little we truly know about the unfathomably complex task of game design. Many mistakes stem from overconfidence. Humility counters the WYSIATI (what you see is all there is) bias, making designers more observant, thoughtful, and open to serendipitous discoveries. It acknowledges the vast “ocean of ignorance” beyond our “small islands of understanding.”

Hunger

Hunger is the belief that no matter what we’ve done, we can do better. It’s an insatiable desire to constantly improve at maximum rate, regardless of external expectations or past successes. Hungry designers are not chained to existing standards; they push beyond them, seeking the “irreplaceable pleasure of doing something better than they did before.” This drive is internal and leads to continuous self-improvement, allowing designers to exceed expectations over years or decades.

Key Takeaways: What You Need to Remember

Most Important Insights from Designing Games

Core Principles That Drive Results

• Games are engines of experience: They are artificial systems designed to generate specific emotional and thought processes in players.
• Mechanics generate events, which provoke emotions: Events are meaningful if they cause a shift in human values.
• Elegance maximizes experience while minimizing burden: Simple mechanics that interact in complex, non-obvious ways are key to deep, replayable games.
• Decisions are unique emotional triggers in games: Players feel emotions about possible futures, not just present events. Meaningful decisions require partial predictability.
• Iteration is essential for game development: Because game design is inherently uncertain, short plan-build-test loops are crucial for learning and adapting.

Game-Changing Strategies

• Design for emergence: Craft mechanics that multiply possibilities rather than just adding them.
• Stretch skill range through reinvention: Games should offer new layers of challenge (manual, situational, mental) as players improve.
• Balance strategies, not just tools: Ensure multiple viable strategies exist in any given situation, fostering nuanced decision-making.
• Leverage yomi in multiplayer: Design for mind games of prediction, deception, and outwitting opponents, especially through fuzzy, hard-to-quantify interactions.
• Prioritize meaningful work for motivation: Intrinsic drives like autonomy, mastery, and purpose are more powerful than extrinsic rewards.

Critical Success Factors

• Understand the primacy of emotion: Games are about how they make players feel, not just what they do.
• Manage information balance: Provide enough information for meaningful decisions without causing starvation or glut.
• Align player and character motivations: Prevent “desk jumping” by making player goals align with in-game character actions.
• Cultivate a positive development climate: Foster safety, trust, and openness to maximize creativity and risk-taking.
• Focus on a few unique market values: Match ambition to resources by specializing in values underserved by competitors.

Immediate Actions to Take Today

First 24 Hours

• Identify core gameplay: Strip down a game idea to its absolute minimum set of mechanics that still create a meaningful experience.
• Sketch a dependency stack: For a current or planned project, identify the strongest dependencies between key design elements.
• Observe a playtest silently: If possible, watch someone play a game without offering any comments or guidance, focusing on their unvarnished experience.

First Week

• Practice grayboxing: For a small design idea, create a low-fidelity prototype using simple shapes or placeholders to test mechanics quickly.
• Analyze a game’s “metaphor vocabulary”: Pick a game and identify its consistent visual/audio cues that signal interactive or mechanically relevant elements.
• Reflect on a past design failure: Consciously apply hindsight bias to identify the actual root causes, avoiding the trap of thinking it was more predictable than it was.

First Month

• Experiment with decision scope: For a specific game mechanic, brainstorm ways to create twitch, tactical, and profound decisions by altering information availability or time pressure.
• Research an “underserved market segment”: Identify a niche in the game market that seems to lack compelling products, and brainstorm unique values that could appeal to it.
• Engage in semi-random research: Read a book or explore a topic completely unrelated to games, looking for analogous systems or ideas that could inspire new design concepts.

Implementation Roadmap

Phase 1: Foundation Building

• Define the game’s core purpose: Clearly articulate whether the game prioritizes profit, artistic expression, or other goals, as this shapes all design decisions.
• Establish a minimal viable prototype (MVP): Build the core gameplay first, in graybox, to get a playable, testable version as early as possible.
• Set up basic playtesting protocols: Start with self-testing and then over-the-shoulder playtesting with fresh eyes, focusing on observing player behavior.

Phase 2: Testing and Optimization

• Implement iterative loops: Plan short cycles of design, build, and test, using playtest feedback to refine assumptions and guide the next iteration.
• Balance from the bottom-up: Start balancing foundational mechanics, then move up the dependency stack, accepting that upper layers will likely change.
• Gather metrics for fine-tuning: Instrument the game to collect data on player behavior, allowing for precise adjustments that aren’t visible in manual playtests.

Phase 3: Scaling and Growth

• Integrate art and audio late: Add polished assets only when the underlying mechanics are proven in graybox, avoiding premature production costs.
• Distribute authority: Empower individual developers to make decisions within their natural authority, fostering a “distributed mind” approach.
• Communicate intent clearly: Leaders should convey the “why” behind decisions, allowing subordinates to adapt locally while serving broader goals.

Measuring Success and Progress

Daily Metrics to Track

• Iteration loop completion rate: How many design-build-test cycles are completed per day/week.
• Graybox progress: Visual indicators of new graybox elements being added and tested.
• Task completion: Simple checklists of completed tasks to show daily progress.

Weekly Review Process

• Playtest debriefs: Summarize key observations from playtests, focusing on player experiences rather than suggestions.
• Dependency stack review: Check if any foundational changes have occurred, potentially impacting dependent elements.
• Design backlog review: Identify relevant ideas from the backlog that can now be pulled into the current iteration based on solidified foundations.

Monthly Performance Analysis

• Market segment analysis: Re-evaluate the game’s target market segments and value curve against competitors.
• Balance reports: Use metrics to identify any emerging degenerate strategies or unintended imbalances.
• Team climate assessment: Gauge overall team morale, trust levels, and openness to feedback through observation and informal check-ins.

Common Challenges and Solutions

Typical Obstacles

• Overplanning: Creating overly detailed plans that become rigid and fail on contact with reality.
• Information starvation/glut: Players lacking critical information or being overwhelmed by too much.
• Divergent player goals: In multiplayer, players pursuing personal goals that disrupt others’ experiences.
• Skill differentials: Large differences in player skill causing frustration or boredom.
• Extrinsic reward pitfalls: Incentives that destroy intrinsic motivation or create perverse behaviors.

Proven Solutions

• Embrace uncertainty: Accept that game design is inherently unpredictable and build processes to adapt.
• Iterate relentlessly: Use short, frequent plan-build-test cycles to learn from reality.
• Focus on core gameplay first: Build the minimum viable experience before adding complexity.
• Distribute authority and trust: Empower individuals and teams to make decisions in their areas of expertise.
• Prioritize intrinsic motivation: Foster a climate of meaningful work, ownership, and psychological safety.

Prevention Strategies

• Challenge assumptions: Question every borrowed concept and inborn cognitive bias.
• Use grayboxing extensively: Delay polished art and audio to keep designs fluid and reduce rework.
• Design for yomi: Create complex, unpredictable interactions that foster deep mind games, especially in competitive multiplayer.
• Align rewards with intrinsic desires: Only reward activities players would naturally enjoy.
• Cultivate humility and hunger: Continuously seek to improve and learn, recognizing the vastness of what is unknown.