AI forgot what it was doing in the middle of a coding task
AI memory is recency-biased. It can remember the last error and forget the decision that made the whole refactor safe.
Why this hurts.
The model can drift away from the original goal, re-open solved questions, or miss constraints that were only stated once.
How ShardStitch solves it.
Restate the outcome being pursued
Store the task boundary outside the chat.
Recover decisions and constraints
Pin decisions, constraints, rejected paths, and known truths into the recovery packet.
Separate evidence from interpretation
Compare a remembered decision with files, notes, or command output; label unsupported conclusions as inference.
Choose a small next action
Hand the next AI a clean brief anchored to the current repo.
What the next AI receives.
- Goal
- Constraints
- Known true facts
- Rejected approaches
What stays out.
- Chatty rationale
- Temporary guesses
- Irrelevant prompts
- Old assumptions
Reconstruct the task boundary
FAQ.
Can a handoff recover intent that was never recorded?
Not reliably. Repository changes may show what happened, but they rarely prove why. Keep missing intent explicit and ask the project owner to confirm it.
How do I stop the next AI from repeating the same detour?
Carry forward the failed approach, the observed result, and why that result ruled it out. A bare list of attempts without outcomes is not enough to choose a different test.