Alternatives
Products that do what Requirements Engineering with Formal Verification does
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…
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2022 · mango-slra1-ckwssph7iq-ue.a.run.app
- 3SD
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
- 4FV
To my knowledge, this is the first formally verified implementation of a 3D constructive solid geometry (CSG) operation: mesh intersection, implemented in Lean 4 and verified against a concise specification that pins down the surface of the resulting mesh exactly and guarantees practical well-formedness conditions on the triangulation. This project is also an experiment in avoiding having to trust AI-generated code. A human reviewer only needs to read 93 lines of formal specification and run the Lean checker to certify the correctness of the kernel, skipping the intricate 1000+ lines of…
Jul 2026 · github.com
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- 6ED
Aug 2026 · github.com
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Deep Work Plan▲114Models matter. Context matters more. Give your agent a plan.
Jun 2026 · deepworkplan.com
- 8FV
We open-sourced the TLA+ and Fizzbee verified spec behind Ursa's storage engine. Verification across ~200K states caught a design bug that years of production missed. We then handed the spec to Claude Code — it produced a working Rust implementation (concurrent producers, compaction, fencing) without back-and-forth. We think verified specs are the best harness for coding agents: open-source the spec, let anyone implement it.
Apr 2026 · github.com
- 9SC
Hey HN! We're Charles and Dean. A few weeks ago we posted about Stage, a code review tool that guides you through reading a PR step by step - https://news.ycombinator.com/item?id=47796818. We got a lot of great feedback but also heard from many people that they wanted to have the chapters experience even before opening a PR… so we built the Stage CLI as the local, open-source version that anyone can try. Here’s a quick demo video: https://www.tella.tv/video/stage-cli-demo-f55q It works with any coding agent of your choice. The skill instructs the agent to…
May 2026 · github.com
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- 12ST
We're a couple of software engineers who believe that to build great software you need to write good tests, but we also sympathise when engineers say things like: - "Writing tests was too time consuming on my tight schedule", or - "Unit tests don't catch enough bugs, so they're useless", or - "I've inherited a legacy code base without tests and have no idea where to start" To tackle this we're building Symbolica (https://www.symbolica.dev), a symbolic code executor [1], that lets you run your code for all possible inputs. This means you can do things like: - Assert properties about…
2021
- 131D
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
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Aug 2026 · github.com
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Requirements traceability and AI tool for software dev teams
Jun 2026 · reqmatrix.com
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AI-powered requirements & specification management
Jul 2026 · play.google.com
- 17OA
As AI agents autonomously write and deploy code, there's no standard for verifying that what they shipped actually satisfies business requirements. OQP is an attempt to define that standard. It's MCP-compatible and defines four core endpoints: - GET /capabilities — what can this agent verify? - GET /context/workflows — what are the business rules for this workflow? - POST /verification/execute — run a verification workflow - POST /verification/assess-risk — what is the risk of this change? The analogy we keep coming back to: what OpenAPI did for REST APIs,…
Apr 2026 · github.com
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Build better hardware with AI for engineering requirements
24d ago · altium.com
- 19SM
I built this because I got tired of watching Claude Code read through massive files just to find a few functions. Sourcerer lets AI agents search code semantically and grab exactly the code chunks they need instead of burning tokens on whole files. It uses tree-sitter to parse your codebase and creates a searchable index. So instead of "read auth.py (538 lines)", an agent can search for "user authentication logic" and get back just the relevant functions. Demo: https://asciinema.org/a/736638 GitHub: https://github.com/st3v3nmw/sourcerer-mcp
2025 · github.com
- 20FA
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
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Your AI has your code's text, never its map. Fix that.
Jun 2026 · luuuc.github.io
- 22GS
I've worked on several projects writing and implementing specifications (particularly CLN): I've found the specs I write are much better when I quote them in the implementation, so I can see what implementers need to know. Also, when specs change in development, it's almost trivial to find where to update the code. This project is a formalization of my various hacky scripts which ensure the requirements are accurately quoted, and give coverage if any are missing. Not a major Opus, but I hope someone else finds it useful!
Jul 2026 · greatspectations.org
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2021 · github.com
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