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SDM

System Alchemist

Surface Labels

Combinatorial rules Emergence-first Trust player invention Guardrails mindset Meta expansion
SDM character

System Alchemist

A game should be a playground where fun emerges from systems and player invention, not designer-provided answers.

Core Traits

SDM sees a game less as content that delivers a right answer, and more as a rule engine that multiplies possibilities. They rate the best moments as the ones where systems interlock and unexpected outcomes burst out, not where players follow a scripted path.
So SDM designs around combinations and interactions: one system calls another, a new layer sits on top, and the strategy space expands. In short, SDM prefers sturdy rules, but wants results to explode through player combination and invention.

From an MDA (Mechanics-Dynamics-Aesthetics) lens, SDM treats Dynamics as the primary design target. Mechanics are not a device for delivering a "right answer" but a reaction system where player actions collide and create new situations; as those dynamics repeat, the strategy space expands.
SDM's fun model is that interactions keep generating new problems even without adding new content.

In practice, SDM cares most about whether players can set their own goals. Even with limited content, if the system reproduces new situations, replay stays alive and the community creates its own play culture.
If guardrails are weak, abuse and collapse arrive fast. SDM loves emergence, but they don't ignore live-ops cost or onboarding friction; they obsess over finding the threshold where a deeper rule design is still worth paying for.

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Core Values

North Star

A game should be a playground where fun emerges from systems and player invention, not designer-provided answers.

Situational Behavior

  • When requirements are vague, you look for reusable rule connections instead of adding one-off content, so players can discover new outcomes through combinations.
  • In technical trade-offs, you prioritize simulation consistency and state safety because tiny inconsistencies can amplify into exploit paths.
  • Under schedule pressure, you simplify surfaces but protect the core combinatorial axis so the strategy space does not collapse.
  • When feedback conflicts, you separate intended emergence from harmful exploits and draw a clear line for what the game should allow.

Operational Style

  • You balance with guardrails (caps, costs, cooldowns) built for combinatorial explosion, not a single perfect configuration.
  • You iterate on interaction links in small units; one connection can reshape the entire strategy space.
  • In live ops, you treat meta collapses as design outcomes; you read the collapse pattern and re-wire rules rather than only nerfing symptoms.
  • You consider monitoring and test strategy part of the product because QA cost scales non-linearly in combinatorial systems.
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Strengths

  • Build structures that last even without constant content. Player-generated goals, replayability, and community meta production emerge from inside the system.
  • Treat 'combos' as a language. You see rule blocks and connection points as design units, and structurally design interactions that multiply fun.
  • Shines in: R&D, system prototyping, core loop design for sandbox/4X/automation genres, and long-term meta design for live services.

Trade-offs

  • The entry barrier and exploit risk naturally increase. If onboarding is weak, complexity quickly becomes churn and ops cost can spike.
  • It can look directionless. Without aligned goals/guardrails, there will be moments the game feels scattered to the team.

Team Chemistry

Needs Alignment: Feel Artist (CET)

Feel Artist (CET) tends to prioritize the opposite direction, so friction appears early unless goals, success criteria, and decision order are aligned first.

Representative Games

RimWorld

RimWorld

Factorio

Factorio

Oxygen Not Included

Oxygen Not Included

Satisfactory

Satisfactory

Dyson Sphere Program

Dyson Sphere Program

Stellaris

Stellaris

References

Work Link
Hunicke, R., LeBlanc, M., & Zubek, R. (2004). MDA: A Formal Approach to Game Design and Game Research. https://aaai.org/papers/ws04-04-001-mda-a-formal-approach-to-game-design-and-game-research/
Juul, J. (2002). The Open and the Closed: Games of Emergence and Games of Progression. https://www.jesperjuul.net/text/openandtheclosed.html
Juul (DiGRA DOI record) https://dl.digra.org/index.php/dl/article/view/214
Pacini, R., & Epstein, S. (1999). The relation of rational and experiential information processing styles to personality, basic beliefs, and the ratio-bias phenomenon. https://doi.org/10.1037/0022-3514.76.6.972
Denisova, A., et al. (2024). Towards Democratisation of Games User Research. https://doi.org/10.1145/3677108
Isbister, K., & Hodent, C. (Eds.). (2018). Game Usability: Advice from the Experts for Advancing UX Strategy and Practice in Videogames. https://global.oup.com/academic/product/game-usability-9780198794844