POES: Verification For AI Generated Code

What it does

This is a coding agent first framework that allows the coding agent to verify code that it has generated. You can get started by just trying "Use https://github.com/kurrent-io/poes/ to build and verify {prompt or spec} and then provide me with a proof-of-work (this is deterministic)" The coding agent will be able to verify the logic and provide you with a proof of work of the code generated. This is at a experimental stage, free, open source and we welcome feedback.

[Experimental] Proof-Oriented Event-Sourcing: Providing best effort formal verification guarantees to event sourcing code - kurrent-io/poes

Shorten the verification gap in AI-generated code. POES is a Python library that verifies event-sourced aggregates using property-based testing, exhaustive state exploration, and temporal property checking — no external SMT solvers or model checkers required. It's a coding-agent-first framework: an agent writes an aggregate and proves it in the same step, and the proof-of-work is for the human. Experimental, written by Claude Code — not recommended for production. Feedback and pull requests (including from coding agents) welcome. Philosophy: https://www.kurrent.io/blog/proof-oriented-event-sourcing/ A single /poes request in pi : deepseek-v4-pro writes a Counter aggregate, the poes-enforce…from github.com

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