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Peter
Peter

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Your AI workflows are live — but nobody's diagnosing when they break

Most teams ship an AI workflow and then treat it like it'll just keep working. It won't. Live workflows degrade silently — model drift, stale context, broken tool calls, undefined failure boundaries. You don't find out until output quality drops or a pipeline silently fails.

We built TryPromptFlow to diagnose and repair live working workflows — not prompts in isolation, but the actual running systems.

What it actually does

You point TryPromptFlow at a live workflow. Multiple frontier models analyze it and produce a full diagnostic:

  1. Root cause analysis — where and why the workflow breaks, with evidence and severity
  2. Failure boundaries — which steps fail silently, where retries mask underlying issues, where there's no error handling at all
  3. Repair blueprint — a concrete fix plan, sequenced with dependencies, ready to hand to engineering
  4. Risk register — what could break after the fix so you don't trade one failure for another

Three diagnostic doctors

  • Workflow Doctor — diagnoses multi-step AI workflows
  • Agentic Workflow Doctor — diagnoses autonomous agent systems
  • Workflow OS Doctor — diagnoses your entire AI operating system

Most diagnoses complete in under 10 minutes. Start with a free diagnosis — no credit card required.

Check it out

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