Flowtrace
Watch and steer your AI agent as a live graph
What it does
AI agents work in a black box—you get an answer, not the process, so you can't trust it or fix the one wrong step. Flowtrace turns a task into a graph your agent works through while you watch and steer. Every step writes a real file (it can't cite what isn't there), every run is git-versioned, and the next task of the same kind reuses the shape instead of starting from zero. Open source (MIT), built in Rust. Works with Claude Code, Codex, and Cursor—any LLM.
Does the same job
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FlowTracker, a Java agent that tracks data flowing through Java programs. It helps you understand where any program got its output from, what it means, and why it wrote it. Watch the video or explore the live demo yourself, and read how it works at https://github.com/coekie/flowtracker
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I think graph is a wrong abstraction for building AI agents. Just look at how incredibly hard it is to make routing using LangGraph - conditional edges are a mess. I built Laminar Flow to solve a common frustration with traditional workflow engines - the rigid need to predefine all node connections. Instead of static DAGs, Flow uses a dynamic task queue system that lets workflows evolve at runtime. Flow is built on 3 core principles: * Concurrent Execution - Tasks run in parallel automatically * Dynamic Scheduling - Tasks can schedule new tasks at runtime * Smart Dependencies - Tasks can…
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hi guys. been working on something i think is fundamentally missing in today's workflow with ai agents. vcs. i find myself struggling with questions that agents can't answer like "why did you do it?", "when did u delete this folder? why?", etc. or trying to /rewind (after a /compact...) or basically `bisect` to find when and why something was done by the agent in the current / previous session. just like git did for code, i think we are the same core capabilities with ai agents so... i developed an open source solution for that (currently supporting claude code) would love to…
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