Switching AI coding tools loses the working state
Each AI coding tool has its own context shape. Copying a chat transcript from one tool into another is usually the wrong bridge.
Why this hurts.
Tool switches often lose decisions, local edits, failed attempts, and the format the target tool expects.
How ShardStitch solves it.
Keep project state separate from chat state
Keep the core goal, changed files, tests, and constraints in a project packet instead of relying on a provider's chat history.
Choose the destination pickup path
Keep the same core packet while adapting the wrapper to the next tool.
Open the same authoritative checkout
Open the target tool against the same branch and working tree, then confirm it can see the files cited in the packet.
Verify before parallel work resumes
Before parallel work resumes, check that each tool sees the same commit, diff, and verification status.
What the next AI receives.
- Target-formatted packet
- Project facts
- Handoff file or clipboard text
- Scope and next action
What stays out.
- Source-tool UI noise
- Tool-specific assumptions
- Raw transcript history
- Irrelevant prior prompts
Move the task, not an unverified transcript
FAQ.
Does switching tools transfer my working files?
A continuation packet transfers context, not the repository itself. Open or sync the intended project through your normal workflow and verify the branch and files in the destination.
Do all supported AI tools use the same native integration?
No. Handoff formats and live integrations vary by tool. Select the documented path for the destination and verify that client actually loaded it.