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Products that do what POES: Verification For AI Generated Code does

Providing best effort formal verification guarantees to code

  1. 1

    Multi-agent review catching bugs early in AI-generated code

    Mar 2026

  2. 2PG

    I use AI agents to build UI features daily. The thing that kept annoying me: the agent writes code but never sees what it actually looks like in the browser. It can’t tell if the layout is broken or if the console is throwing errors. So I built a CLI that lets the agent open a browser, interact with the page, record what happens, and collect any errors. Then it bundles everything — video, screenshots, logs — into a self-contained HTML file I can review in seconds. proofshot start --run "npm run dev" --port 3000 # agent navigates, clicks, takes screenshots proofshot stop It works with…

    Mar 2026 · github.com

  3. 3

    Build powerful agents in seconds with AI CANVA GENERATOR

    2025

  4. 4WB

    Hey HN, We’re two developers (co-founders) with a team of 20 who got tired of spending hours reviewing PRs, so we built Infinitcode.ai, an AI-powered code reviewer that: - *Summarizes PRs in plain English*: No more deciphering 1,000-line diff jungles - *Catches more than bugs*: Security holes, performance pitfalls, code smells, even typos (yes, we’ll flag “vurnerabilities” and vulnerabilities) - *Zero onboarding*: Works instantly—no “let me learn your codebase for weeks” nonsense. Why we’re posting: We’re in alpha and need brutal honesty. Roast our tool, mock our UI, or tell us why AI will…

    2025 · infinitcode.ai

  5. 5
    CodeGuide126

    Generate PRDs, specs and wireframes your AI understands.

    Mar 2026

  6. 6
    YepCode109

    Developer-first AI integrations: build, run, scale safely

    Jan 2026

  7. 7

    Connect Claude Code to your internal systems w/o credentials

    Mar 2026 · hoop.dev

  8. 8

    Validate agent-generated code before it ever reaches CI

    May 2026 · circleci.com

  9. 9MA

    I've been exploring the (not so=) amazing potential of AI in coding and have compiled a list of tools. From AI-powered IDEs to code generators, this resource is my contribution to the community. I'm still on the fence about including txt2sql projects, as their functionality seems too basic to me. And I'm personally maintaining this, so your feedback is wellcome.

    2025 · aicode.danvoronov.com

  10. 10

    Full-stack apps and PoCs in hours, not weeks.

    2025

  11. 11

    Production-tested architecture for autonomous Claude agents

    Apr 2026 · dvdshn.com

  12. 12
    formal1

    Formal verification for AI-generated code using Lean 4

    Apr 2026 · github.com

  13. 13FA

    We've been working on an open-source coding agent that generates code alongside machine-checkable proofs. We'd love feedback from the HN community, especially from people interested in formal verification, Lean, Dafny, or AI coding agents. Currently, only 3 langauges can be verified.

    Jul 2026 · github.com

  14. 14MC
  15. 15

    Formal verification for AI-generated code

    Feb 2026

  16. 16RE

    I've been building an open source formal methods system (fizzbee.io) for the past few years. Today I'm launching a new app built on the same technology. It performs requirements engineering using formal verification to uncover gaps and produce precise instructions for your coding agents to follow. When given a prompt, it - asks high signal follow-up questions - converts to formal spec and identifies complex requirements gaps - generates validation scenario At the end, it produces a specification document that can be shared with coding agents. In my trials on various projects, it produces…

    Jul 2026 · fizzbee.ai

  17. 17AB

    Hi there, HN! We’re Jai and Sanket from DeepSource (YC W20), and today we’re launching Autofix Bot, a hybrid static analysis + AI agent purpose-built for in-the-loop use with AI coding agents. AI coding agents have made code generation nearly free, and they’ve shifted the bottleneck to code review. Static-only analysis with a fixed set of checkers isn’t enough. LLM-only review has several limitations: non-deterministic across runs, low recall on security issues, expensive at scale, and a tendency to get ‘distracted’. We spent the last 6 years building a deterministic, static-analysis-only…

    Dec 2025

  18. 18RT
  19. 191D

    We just open-sourced the internal system we built at Assembled for running coding agents as a team. Coding agents worked well for individual engineers, but the surrounding workflow was a bit of a mess. We generally found that many engineers had different MCP connections and context for their agents, personal automations running that other people couldn’t access, and very little introspection for what a human’s input into the coding agent looked like. So we built an internal system that converted coding agents into shared team infrastructure. The system runs Codex, Claude Code, OpenCode, and…

    Jun 2026

  20. 20

    Hi HN, I built VT Code, a semantic coding agent. Supports all SOTA and open sources model. Anthropic, OpenAI, Gemini, Codex. Agent Skills, Model Context Protocol and Agent Client Protocol (ACP) ready. All open source models are support. Local inference via LM Studio and Ollama (experiment). Semantic context understanding is supported by ast-grep for structured code search and ripgrep for powered grep. I built VT Code in Rust on Ratatui. Architecture and agent loop documented in the README and DeepWiki. Repo: https://github.com/vinhnx/VTCode DeepWiki:…

    Apr 2026 · github.com

  21. 21GV
  22. 22EY

    I built an open-source AI agent for security testing to find and fix vulnerabilities in your code. I’ve noticed how bad security vulnerabilities have gotten with everyone shipping AI code slop, so I wanted to build something that allows for vibe-coding at full speed without compromising security. Traditional security tools aren’t effective, and manual pen-testing can’t keep up with the rapidly growing AI code This tool runs your code dynamically, finds vulnerabilities, and validates them through actual exploitation. You can either run it against your codebase or enter your (or someone…

    2025 · github.com

  23. 23IS
  24. 24SD

    Spec Driven Development approach allows to squeeze more from coding agents thanks to few strong concepts: - decomposition across two dimensions. first you generate specs in multiple steps (requirements, code analysis, design), than you split task into multiple subtasks and implement them one by one - you clear context between every step - after spec generation and after subtask implementation. this helps keep cost low and context clear and focused which boost performance - specs written to disk help with information persistency - delivering specs layer by layer help to catch early when agent…

    May 2026

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