Systemic Game Design, Part 5: What Games Work Well With Systems?

Main ideas / lessons

• Not every game benefits from heavy systemic design.

  • Sometimes systems are invisible to the player, and a simpler approach (e.g., a randomizer) could “do the job.”
  • In other cases, system unpredictability can clash with:
    • a tight narrative
    • a strict ruleset/mechanics approach

• Some genres and mechanics reliably pair well with systems. The video highlights four recurring categories:

  1. Simulation / sim-like games
  2. Stealth games
  3. Games that use discrete/graph-like spatial thinking
  4. Open-world games

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How systems work well (by genre/mechanic)

1) Simulation games (and strategic sims)

• Core concept: simulation systems emulate real phenomena using data and algorithms.
• Where systems shine most:
  • Realistic sims (e.g., flight/truck simulators)
  • Abstract/fantastical sims (e.g., SimCity, Dwarf Fortress)
  • Strategic sims, especially at a zoomed-out scale, where patterns and interactions emerge
• Common systemic “illusion of lack of control”:
  • Players may lose control of individual units.
  • But they still influence outcomes at the organizational / system level.
  • Result: you may watch units longer (sometimes with frustration), but you observe the system in action and understand constraints (entities act “on schedule” and follow paths/limits).

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2) Stealth games (a strong match for systemic design)

• Core systemic structure: stealth levels often start with a default automated state, such as:
  • guard patrols
  • monitoring networks/security across the level
• Underlying systems typically present (at minimum):
  • Line-of-sight
  • AI detection and reaction to the player
• Player’s systemic role: players must interact with and/or manipulate those systems to achieve goals.
• Player interaction examples (in practice):
  • Avoid being seen by:
    • observing detection patterns
    • using gaps in coverage
  • Create opportunities / interfere, such as:
    • causing distractions
    • taking out sentries
    • altering the level at a larger scale
• Design note included in the explanation: the video frames systemic stealth as especially suitable because stealth inherently depends on dynamic rules (vision, alerts, patrol logic, monitoring coverage).

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3) Discrete grids / graphs (a practical system-design technique)

• Core concept: while computers can handle continuous spaces, it’s often easier to design systemic logic using discrete units.
• Method described:
  • Use grids and discrete graphs made of nodes and neighbors
  • Determine evolving effects by checking which nodes affect which neighbors
  • Commonly implemented as:
    • 2D orthogonal grids (but could use any shape)
• Player-facing benefit:
  • The boundaries between nodes and states become clearer.
  • That makes systems easier for players to recognize and appreciate.

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4) Open-world games (systems as “content multipliers”)

• Core problem in open worlds: they require a lot of content to feel alive and dynamic.
• How systems help:
  • A small number of procedural events can feel many different ways, depending on the current state of the systems.
  • The world can respond differently based on context, even if encounters are based on the same underlying scenario.
• Example given: vampire encounters
  • The encounter can change depending on system state, such as:
    • time conditions (e.g., negative day)
    • environmental factors (e.g., river nearby or buildings nearby)
• Example used to illustrate “same encounters, different feel”:
  • Breath of the Wild: Eventide Island
    • The area “turns the experience on its head” by stripping you of equipment you normally rely on.
    • You must rebuild an arsenal by using the game’s systems.
    • Even though encounters are not fundamentally new, changing the game state makes them feel significantly different.
• Modularity claim:
  • Systems can be designed as modules that you can add, remove, or manipulate.
  • This enables variety “with relative ease,” compared to authoring entirely new handcrafted content.

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Method / takeaways (actionable bullet points)

• Check fit before going “heavy systems”:
  • Ask whether systems will be:
    • noticed by players (or whether randomness could suffice)
    • compatible with your narrative tightness and mechanics constraints
• If designing in the highlighted genres, think “systems first”:
  • Simulation: model phenomena via algorithms/data; favor strategic zoomed-out patterns.
  • Stealth: build a default automated environment (patrols/security); include line-of-sight + reactive AI; ensure the player can manipulate systems to advance goals.
  • Discrete grid/graph systems: represent space/state as nodes and neighbor relationships; design for visible node/state delineation.
  • Open world: use systems to make a few events feel dynamic across different world states; support state-dependent encounter variation.
• Scope note from the creator:
  • The video intentionally does not cover procedural generation in detail, noting it is systemic but treated separately from “systemic game design” and promised for a later video.

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Speakers / sources featured

• Speaker: The video’s presenter/creator (not named in the subtitles)
• Referenced works/games (examples):
  • Dwarf Fortress
  • SimCity
  • (Referenced as examples of simulation) flight and truck simulators
  • Stealth-game examples (general category; no specific title named)
  • The Legend of Zelda: Breath of the Wild (specifically Eventide Island)