Keep one lightweight decision log for AI-assisted work: decision, rationale, constraints, and verification note. Update it whenever scope or architecture changes. Then include that log in future prompts so the model starts from settled context instead of reopening old choices.
The Hidden Cost of No Memory
AI is fast at generating options, but it is weak at durable project memory unless you explicitly provide one. Without a record, the model treats each session as a fresh design discussion. Teams then burn time re-answering solved questions.
The result is not only slower progress. It also increases inconsistency. One day the assistant proposes DTO mapping in the route layer. Next day, with slightly different prompt context, it proposes moving the same logic into the service. Both can sound plausible. Only one aligns with your team's earlier call.
What a Decision Log Actually Is
This is not heavyweight architecture documentation. It is a compact working artifact you can update in minutes while coding.
- Decision: one sentence describing what you chose.
- Why: the key reason and tradeoff.
- Constraint: what must stay true because of this choice.
- Verification: the test or check that confirms it still holds.
- Date/owner: who decided and when.
If the log does not include a constraint, future prompts will accidentally violate the decision. If it does not include verification, the decision becomes opinion instead of operational guidance.
Decision: [What we chose.]
Why: [The reason, including the tradeoff we accepted.]
Constraint: [What future AI changes must preserve.]
Verification: [Test, command, review check, or observable behavior.]
Date/owner: [When this was decided and who can revisit it.]
When to Add an Entry
- When you choose one pattern over another (for example service-owned validation).
- When you reject a tempting refactor for now.
- When you define a risk boundary (for example no schema change in this release).
- When review uncovers a recurring class of mistake.
- When a rollback teaches you a better default.
Skip logging trivial mechanics like import order changes or typo fixes. Capture decisions that change how future prompts should behave.
Teams record decisions only after painful incidents. By then, the model has already produced multiple inconsistent diffs. Log decisions during normal flow, not just postmortems.
A Copy-Paste Prompt That Uses the Log
"Before proposing code, read the decision log below and restate constraints that apply to this task. Then propose the smallest change that satisfies the goal without violating logged decisions. If a decision appears outdated, flag it explicitly instead of silently overriding it."
This prompt does two useful things. It forces the model to acknowledge constraints up front, and it creates a safe path for challenging stale decisions without erasing them by accident.
Example: One Decision, Fewer Rewrites
Without a Log
Session A: AI moves request validation into route handlers.
Session B: another prompt asks for cleanup, AI moves validation into services.
Session C: bug fix touches both patterns, review grows messy, and tests become brittle.
With a Log
- Decision: Keep validation in route handlers for all HTTP endpoints.
- Why: Error mapping and status codes stay consistent at transport boundary.
- Constraint: Services accept validated domain inputs only.
- Verification: Route tests assert 4xx behavior for malformed payloads.
Now the next assistant can still suggest improvements, but it should not relocate validation unless it first challenges the recorded decision directly.
Keep the Log Small and Current
Large logs become ignored logs. Keep entries short and archive stale ones. A practical target is 10 to 25 active decisions for a medium-size project area.
Run a quick monthly pass:
- Delete entries that no longer matter.
- Merge duplicates that describe the same boundary.
- Mark superseded decisions instead of silently editing history.
- Reconfirm verification steps still map to real tests.
The Log Turns AI From a Debater into a Collaborator
You will still need review, tests, and judgment. But a decision log removes one avoidable source of friction: repeated debates caused by missing memory. It helps every new prompt start one level higher, with constraints already explicit.
For adjacent workflows, pair this with The AI Plan Before Code, The AI Session Resume Packet, and Writing the Context File. Together they form a simple control loop: decide, record, execute, and resume without drift.