Stay in the Zone.
Kill the AI rabbit hole.
AI makes it easy to move fast, but it’s even easier to move in the wrong direction. TraceFlow watches your back so you can ship code that actually matters without the weekend-long refactors.
Reclaim Your Wasted Evenings
There is nothing worse than realizing you've spent 4 hours on a Saturday refactoring code that didn't need to change. AI makes these "rabbit holes" deeper than ever. TraceFlow pulls you out before you lose the day.
Real-time Tangent Alerts: TraceFlow figures out what you're working on from the conversation itself. When the session drifts, you get a nudge. No setup required.
Automatic Intent Extraction: TraceFlow builds a rolling understanding of your session's goal from your prompts and file changes. No tickets to link, no goals to set.
Debug with Intent, Not Just Diffs
Git shows you what changed. TraceFlow shows you why. When a bug appears in production, link it directly back to the AI conversation that wrote it.
- • Link Sentry/Datadog errors to AI session IDs.
- • Search your history for architectural decisions, not just strings.
- • Never wonder "What was the AI thinking here?" again.
Your Machine Crashed. Pick Up Where You Left Off.
You had 6 tmux panes open, an SSH tunnel to staging, and a Claude session halfway through a complex refactor. Then your laptop died. Normally that context is gone forever. TraceFlow remembers the full state and resurrects it.
Full Session Recovery: Tmux layouts, PTY sessions, working directories, and AI conversation context are all restored to exactly where you left off.
AI Context Included: Not just the terminal state. TraceFlow restores the AI conversation you were in the middle of, so you don't have to re-explain what you were doing.
Search the Reasoning, Not Just the Code
Git search finds code. TraceFlow searches the conversations that produced the code. Every AI dialogue, every decision, every dead end you explored six weeks ago is archived and queryable. Ask "why did I do it that way?" and get a real answer.
Dialogue Search: Query your archived AI conversations by meaning, not keywords. "Why did I choose token-bucket over sliding window?" works.
Decision Trail: TraceFlow links the reasoning across sessions so you can trace how an architectural choice evolved over days or weeks.
Your Go prompts are specific and well-scoped. Average session time is 40% faster than team average.
Your CSS prompts are too vague. "Make it look better" led to 3 tangent sessions last week. Try specifying exact properties.
Alice's Go error-handling prompt has a 94% success rate. Want to try it?
Get Better at Prompting. Automatically.
Most developers have no idea which of their prompts work well and which waste time. TraceFlow analyzes your sessions and gives you personalized coaching to get better results from every AI interaction.
Pattern Analysis: TraceFlow identifies which of your prompting habits lead to productive sessions and which lead to tangents.
Efficiency Score: Track your prompting effectiveness over time. Your best prompts get promoted to the team's Winning Prompts library automatically.
Commit Messages That Actually Help
"update auth" tells your future self nothing. The TraceFlow desktop agent watches your commits in the background. When it spots a low-quality message, it silently amends the commit with a proper conventional message based on your full session context. No workflow interruption. You just get better git history.
Zero Friction: No prompts, no hooks, no extra steps. TraceFlow amends the commit automatically after you make it.
Team Standards: TraceFlow learns your team's commit conventions and applies them automatically.
Adds a feature-flagged bypass for mTLS verification on internal test endpoints. Guarded by INTERNAL_TEST environment variable that is never set in production.
Initially attempted to disable mTLS globally for local dev, but AI session flagged security concerns. Switched to per-route bypass with env guard.
Focus review on internal/auth/mtls.go lines 47-62. The bypass logic is intentionally verbose for clarity.
The "Instant PR" Description
Stop staring at a blank PR description. TraceFlow synthesizes your AI session history into a clear, honest explanation of what you did, what you tried, and what your reviewer should focus on.
Summarize Intent: Explain the "why" behind the logic, not just what files changed.
List Rabbit Holes: Document what you tried and why it didn't work, so your reviewer isn't guessing.
Draft the Review: Give your reviewer the context they need to approve faster.