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Saving the “soul” of an AI-assisted project means keeping its defining ideas and central logic under direct human ownership while delegating bounded, replaceable work to AI. In Oscar Hedeby’s game-development approach, an engine-agnostic /Game/ folder is the single source of truth and is marked “NO AI ALLOWED.” The game engine sees that core through a view class, while an agent can work on isolated auxiliaries such as a leaf shader or rock-generation system. This arrangement is deliberately slower than unrestricted model-driven implementation. Hedeby presents it as a personal design proposal, not as evidence that every team or project will achieve better results. Its value is a clear authorship boundary: automation can increase output without deciding what the project is.
What does “saving the soul” of an AI project mean?
“Soul” is Hedeby’s metaphor for the small set of ideas, rules and interactions that make a project recognisably itself. In a game, that might include the world model, core mechanics, progression logic, tone and the relationships between those systems. It is not a technical standard or a measurable quality score.
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The concern is not that AI-generated code is automatically bad. The concern is that delegating too much implementation can make the creator less familiar with the project and allow its defining concepts to emerge accidentally from prompts, generated patches and tool defaults. Hedeby’s response is to decide in advance which code expresses the project’s identity and which code is supporting infrastructure.
That makes this a selective-use policy rather than an anti-AI position. Humans retain authorship of the centre; AI receives work that can be isolated, inspected and replaced without changing the project’s fundamental design.
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Which parts should AI never touch?
There is no universal list of forbidden files. The boundary should follow product identity: if changing a component could alter what the project fundamentally is, its design and implementation belong with the human owner.
Core rules and game concepts
Keep the authoritative representation of game rules, state transitions, progression, economy, combat, input meaning and other defining interactions in the human-owned core. A model may explain or lint this code if the team allows it, but it should not silently rewrite the concepts that the code expresses.
Decisions that are difficult to review locally
Some code looks small but carries broad consequences. A one-line change to an event-ordering rule, save format or simulation clock can affect every feature. If a reviewer cannot understand the consequences from the changed module and its tests, treat that area as part of the protected core.
The project’s vocabulary and boundaries
Names, interfaces and invariants teach future contributors how to think about the system. Letting an agent invent those boundaries can gradually shift the design. Establish the vocabulary yourself, then expose only the contracts that an auxiliary task needs.
How does the proposed architecture separate the core from AI work?
Hedeby’s example uses an engine-agnostic /Game/ directory as the game’s single source of truth. The engine does not own the rules; it presents them through a view class. Smaller auxiliary projects connect to that representation through the interface instead of reaching into the core’s internals.
| Layer | Role | Typical ownership | Change risk |
|---|---|---|---|
/Game/ core |
Defines authoritative state, rules and concepts independently of a particular engine | Human project owner | High: changes can redefine the product |
| Engine-facing view class | Translates the core’s state into rendering, input or engine objects | Human-designed contract; implementation can be reviewed | Medium: integration errors can distort behaviour |
| Auxiliary project | Performs a bounded supporting job behind a stable interface | AI-assisted, with human review | Lower when isolated and replaceable |
For example, an agent might optimise a leaf shader or generate rocks. Those tasks can be valuable without deciding how the game’s world works. The boundary is architectural, not a special permission setting: the auxiliary code receives defined inputs, returns defined outputs and cannot become an unnoticed second source of truth.
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How can you implement this workflow step by step?
Use the following procedure before assigning an agent a substantial feature. The aim is to make ownership and integration points explicit rather than relying on good intentions.
- Write the project’s identity down. List the mechanics, rules, data and design principles that must remain coherent. Include invariants such as “one authoritative simulation state” or “all progression is deterministic.”
- Create a protected core. Put the authoritative implementation in an engine-agnostic area such as
/Game/. Mark the policy in the repository and explain what counts as a core change. - Define the view contract. Specify what the engine-facing class may read, what commands it may send and how errors are represented. Keep the contract narrow enough that an auxiliary tool cannot bypass it.
- Carve out one auxiliary task. Choose work with clear inputs and outputs, such as a shader pass, asset generator or profiling experiment. Avoid a task described only as “improve the game.”
- Give the agent local context. Supply the interface, acceptance tests, performance budget and prohibited dependencies. Do not grant broad repository access when a smaller workspace is sufficient.
- Review behaviour at the boundary. Check generated code, tests, resource use and failure handling. Then run it through the same interface that production code will use.
- Integrate deliberately. A human decides whether the auxiliary result belongs in the project, records any contract changes and rejects patches that move authority into the auxiliary layer.
- Revisit the boundary when the design changes. If a supporting system becomes central to the player experience, promote it into the protected design process instead of leaving an old delegation decision in place.
What work is a good fit for an AI-assisted auxiliary?
A task is a better candidate when it is easy to isolate, evaluate and replace. The following tests turn that idea into a practical triage tool; they are editorial guidance inferred from Hedeby’s architecture, not validated industry metrics.
| Question | Good candidate | Warning sign |
|---|---|---|
| Does it define the product’s identity? | No; it supports presentation, tooling or content production | Yes; it changes rules, progression or the project’s distinctive interaction |
| Can it sit behind a stable boundary? | Inputs, outputs and resource limits are explicit | It needs to inspect or mutate many unrelated systems |
| Can a person verify the result? | Tests, visual checks or benchmarks expose errors | Correctness depends on an undocumented design judgement |
| Is replacement affordable? | A failed experiment can be removed without data migration | Adopting it creates a new irreversible dependency |
| What is the integration cost? | One interface and a small review surface | Many core files, generated formats or manual fixes are required |
Leaf-level rendering work and procedural rock generation fit the example because their output can be judged without handing over the game’s central rules. A task that begins as tooling may still become core later; reassess it when players, designers or save data start depending on its behaviour.
What does this approach cost in speed?
It is slower than allowing a model to roam through the whole repository. Isolation requires interface design, smaller prompts, review and sometimes duplicated data. Hedeby explicitly accepts that cost. He says the constrained process leaves more room to imagine the game while an agent handles auxiliary tasks, but that benefit is his reported experience rather than a measured outcome.
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Hedeby describes this decision in his own words: “When I think about the price of implementing a feature I now think of how much touch the soul of the project and how much touch the auxiliary parts.” Read “touch” as the amount of contact a feature has with the defining core, not as a formal measurement.
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How should you decide whether a feature belongs in the core?
Ask the questions below before opening an agent task. A “yes” to the first three usually argues for human ownership; a “yes” to the last three supports an auxiliary treatment.
- Identity: Would a different implementation change the project’s signature experience or its rules?
- Authority: Does the feature create or own state that other systems must trust?
- Irreversibility: Would adopting it force save-data, content or interface commitments?
- Isolation: Can it run with a small, documented input/output contract?
- Evaluation: Can a human demonstrate correctness with tests, traces, visual inspection or a resource budget?
- Replaceability: Could you remove it and substitute another implementation without redesigning the game?
If the answers conflict, split the feature. Keep the rule or policy in the core and expose a replaceable service for expensive computation, presentation or experimentation. This preserves authorship without forbidding automation where it is genuinely useful.
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What failure modes should teams expect?
The “no AI” folder becomes symbolic
If the core is protected but its interfaces are vague, agents can still smuggle decisions into adapters, generated data or configuration. Document which layer owns each decision and reject duplicated authority during review.
An auxiliary grows into a hidden core
A generator or shader may become essential after designers build around its output. Record when that happens, move its design decisions into the human architecture process and keep automation focused on implementation details that remain replaceable.
The interface is too broad
A view class that exposes every object is only a forwarding layer, not a boundary. Narrow it to explicit queries and commands, add contract tests and make unsupported access fail loudly.
Review becomes impossible
Large generated patches defeat the purpose of human ownership. Request small commits, require tests or visual evidence and discard changes whose rationale cannot be explained in project terms.
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Speed pressure removes the boundary
When a deadline arrives, teams may grant an agent unrestricted access “just this once.” Treat that as a conscious architecture exception: record the files, review the result as core code and either restore the boundary or accept the new ownership model explicitly.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Is this a proven best practice for every AI project?
No. The source is Oscar Hedeby’s first-person account of a game project published on DEV Community on October 11, 2026. It does not compare this structure with other workflows, report controlled results or establish that it improves outcomes generally.
The proposal is still useful as a design question: which decisions must remain legible to the person responsible for the product, and which jobs can be delegated without transferring authority? A small solo experiment, a regulated system and a large multiplayer game may choose different boundaries. The architecture should follow consequences, review capacity and the cost of losing shared understanding.
How can you preserve understanding while using agents?
Keep a short human-written design record beside the core. For each protected concept, state its purpose, invariants, allowed callers and examples of valid and invalid behaviour. Link auxiliary projects to that contract rather than copying the concept into their prompts.
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What background helps with the architecture side?
Grokking Software Architecture by Matt Erman, published by Manning and distributed by Simon & Schuster, covers system structure, components, relationships and architectural tradeoffs. It is general background rather than a tutorial for Hedeby’s exact workflow, but those concepts help when deciding where a human-owned core should end and an auxiliary service should begin.
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What should you do first?
Choose one project-defining subsystem, move its authoritative rules into a clearly owned module, and write the smallest interface an engine or tool needs to observe it. Then delegate a genuinely bounded task and evaluate whether the boundary preserved your understanding. The point is not to ban AI; it is to ensure that convenience does not quietly become authorship.
Frequently Asked Questions
Does a “NO AI ALLOWED” core prohibit autocomplete and code search?
Not necessarily. Hedeby’s proposal is about who decides and changes the defining logic, so a team could permit read-only explanation, search or review while requiring a person to author and approve core edits. The policy should state whether assistive features are allowed and how their use is recorded.
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Trace every value it produces back to an explicit core-owned input or contract. Add tests that compare the auxiliary output with core invariants, and check that removing the auxiliary leaves the authoritative state and rules intact.
Can this human-core pattern work outside video games?
Yes, as an architectural analogy. A data product might protect its business rules and schemas while delegating report rendering; a robotics project might protect control policy while delegating simulation tooling. The protected area should be the decisions whose accidental change would redefine the product.
What if a core subsystem is poorly designed and needs an AI-assisted refactor?
Keep ownership of the intended behaviour with a human, then let an agent propose mechanical changes in a temporary branch or isolated workspace. Compare the result against written invariants and tests before accepting any alteration to the authoritative module.
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