Most work with AI is scattered across one chat after another. Once a task is done, the code may remain, but the failed attempts, evidence, and reasoning often disappear. I built Wayfinder to test a different model: keep prompts, tool activity, file changes, validation results, verdicts, and branches local, then turn them into a voyage map you can inspect and recover from without deleting abandoned paths. The first production adapters focus on AI coding across TraeCode, Claude Code, and Codex. When you return to AI-assisted work days later, what context is hardest to reconstruct: why a decision was made, which attempt failed, or how to reuse the successful path?
Wayfinder turns AI coding sessions into a branching voyage map you can revisit and reuse. It records prompts, tool calls, file changes, tests, decisions, and wrong turns locally. Restore any waypoint without deleting the abandoned route, compare alternative approaches, and see which path actually worked. The first production adapters support TraeCode, Claude Code, and Codex through an IDE sidebar, in-conversation MCP App, and terminal view. Open source, no telemetry, no Wayfinder cloud.
