The problem
AI agents re-reason through every task from scratch, even ones they’ve solved before:- Inconsistency: Agents take different paths or skip steps between runs — there’s no way to verify without watching
- Cost: Each reasoning pass costs tokens — the same tokens, for the same logic, every time
- Context bloat: Loading tool schemas (especially MCP servers) consumes tokens before any work begins
How pflow helps
pflow separates planning from execution:- Your agent plans once - figures out what nodes to use and how to connect them
- pflow compiles the workflow - saves it as a reusable
.pflow.mdfile - Execution is instant - run the same workflow with different inputs, zero reasoning cost
Built for agents
The workflow format is markdown — headings, YAML, and code blocks. Agents already think in this structure, so they can write and iterate on workflows using patterns they already know. A side effect: open a.pflow.md file on GitHub and it reads like documentation. Render it in your IDE and it’s self-explanatory. The same file that executes as a workflow also serves as its own docs.

