#After feeding that and the one before to
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Best / easier alternatives (ranked):
1. Single canonical spec file
• One OpenSpec-style doc per project
• Updated every session
• Lowest cognitive load, highest reliability
2. Session checkpointing
• End each session with a short “state + next actions” note
• Paste it into the next session
• Very low tooling, very effective
3. Repo-embedded intent
• agents.md + README as living control surfaces
• Keeps intent next to code
• Works across tools and models
4. Lightweight auto-memory (optional)
• Graphiti / Byterover only for recall, never authority
• Treat as cache, not source of truth
If you want easiest with minimal discipline:
• Session checkpointing wins.
If you want best with moderate discipline:
• Single canonical spec + checkpoints.
Everything else adds complexity without guaranteed gains.
—-__
Because AI alone has no stable intent.
Direct AI use:
• Forgets goals between sessions
• Reinterprets constraints inconsistently
• Optimizes locally, not globally
• Loses decisions the moment context resets
Using specs / primers:
• Externalizes intent so it survives resets
• Makes constraints explicit and enforceable
• Lets you control evolution, not the model
• Turns AI into an executor, not a co-author of direction
In short:
• AI is fast but stateless
• Specs are slow but stable
The tools exist to anchor AI behavior. Without them, you are rebuilding context every time and accepting drift by default.