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Products that do what Case study: A coding agent refactors a 750k LOC app, no code review does
In the following case study, the AI coding agent rebuilds a core system invariant in just three days, with minimal human input, running 31 verification passes and correcting 201 errors, before shipping code with zero bugs, zero regressions, and zero technical debt. https://aisovereignlabs.ai/docs/case-study/liveSession/case-... Disclaimers: This case study is NOT: - a project written from scratch - yet another Rust transpilation - a clone of an open-source project found in the LLM's training data - a Super Mario clone in HTML It IS: - a complex application…
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Hello all, I'm a software developer. Over the last few months more and more of my work has turned into using coding agents instead of typing the whole code myself. Usually a few claude sessions at once, sometimes codex, one per feature or per revealed bug. I ran them in a split terminal for a few weeks, and quickly spotted two main problems. The first is that I couldn't easily tell which agent was stuck waiting on me and which was still working, so I'd cycle through sessions and checking on them. The second one: agents sharing a single branch step on each other. Two of them could be editing…
Jul 2026 · shikigami.dev
- 6IB
The main goal of this was to be able to not just run multiple Claude Code sessions at once, but actually manage them and keep track of what I was doing. Sometimes this is multiple attempts on the same task, sometimes I work several tasks at once. Really I was just sick of twiddling my thumbs waiting for the coding agent to finish, and I wanted it to be easy to work on/review/test another change while I waited.
2025 · github.com
- 7CA
I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!
Sep 2025 · infrastructureas.ai
- 8RA
Hi HN! Sean from MindStudio here. I wanted to share something we've been working on that I think introduces some new ideas into the "AI coding agent" space. Remy is an AI agent that builds full-stack TypeScript apps from a spec written in a new flavor of annotated markdown. The spec has two layers: prose describing what the app does, and annotations that carry the technical precision (data types, edge cases, validation rules, code snippets). The agent then "compiles" this into code: backend methods, typed schemas, frontends, test scenarios, and everything else are derived artifacts of the…
Apr 2026 · remy.msagent.ai
- 9WI
At Laminar (https://github.com/lmnr-ai/lmnr) we're building open source AI observability platform in Rust. We obsess over instrumentation DX for our Python and TS SDKs and in this new blog we outline how we made the most seamless way of instrumenting recently released claude agent sdk
Dec 2025 · laminar.sh
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We built an open sourced coordination layer for AI agents working on the same repository. Detects work duplication and design conflicts early
8d ago · twing.dev
- 11IB
Link: https://docs.trysoma.ai/ For the past ~9 months I’ve been building Soma, an open-source AI agent & workflow runtime written in Rust, with a TypeScript SDK (Python coming soon). It’s not a framework; it’s meant to sit underneath whatever agent/tooling code you already write (Vercel AI SDK, LangChain, custom code, etc.). It provides features around your framework + a better DX for building agents. I’ve tried to take a Next.JS model: open-source, good DX, self-deployable. I originally set out to build a vertical back-office/operations product for SMEs. I needed a…
Dec 2025 · docs.trysoma.ai
- 12IB
For the last 6 months, I've been building ORUS Builder, an open-source AI code generator. My goal was to fix the biggest issue I have with tools like v0, Lovable, etc. – they generate broken, non-compiling code that needs hours of debugging. ORUS Builder is different. It uses a "Compiler-Integrity Generation" (CIG) protocol, a set of cognitive validation steps that run before the code is generated. The result is a 99.9% first-time compilation success rate in my tests. The workflow is simple: 1.Describe an app in a single prompt. 2.It generates a full-stack application…
Nov 2025
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This weekend I built a multi-agent coding system which, quite unexpectedly, beat Claude Code on Stanford's Terminal Bench! The architecture is straightforward, consisting of an orchestrator agent that deploys explorer & coder subagents to complete complex terminal based tasks, utilising an intelligent context sharing mechanism along the way which makes it all work. The repo has a lot of technical details, and all the code and prompts for you to play around with if you'd like! I had a lot of fun making this, I hope you have fun reading the README, using it yourself, or even extending it! As…
2025 · github.com
- 14IB
Here is the proof, a 5-hour uncut live session, no edits, no cuts: https://youtu.be/VPrU8WZJOVs Full article: https://medium.com/@bonjourjoel/i-built-a-500-000-line-produ... I believe I am the first human to have done this in a documented, verifiable way: maintaining a stable production-grade 500,000-line TypeScript codebase as a solo developer, using an AI coding assistant I built myself. If you know someone who has done the same, one person, 500k lines, documented proof, please write their name in the comments.
May 2026
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Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven. In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days. Most modern coding agents already go beyond single prompts. They can plan steps, write files, run…
Jan 2026 · marketplace.visualstudio.com
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Hi Hacker News! We're launching Zalor, an agent testing platform. Agents often break when you tweak system prompts, swap models, or add tools. Zalor automatically generates test scenarios and evaluates your agent so you know it's reliable before deploying to production. We currently support the OpenAI Agents SDK and are onboarding other frameworks. A GitHub integration is coming so you can get feedback on every update. Looking forward to hearing feedback from people building agents.
Mar 2026 · agents.zalor.ai
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The magic in AI coding assistants isn't the code -- it's the prompts. I studied the externally observable behavior of Claude Code and recreated it from scratch in Python with the exact same behaviors. It works with any model -- OpenAI, Gemini, Claude. What's surprising: 1. You can keep the core agent really simple, just 280 lines of Python. As long as it supports hooks, custom sub-agents and Model Context Protocol (MCP), then all the rest of the coding-assistant-specific behavior and tools can be factored out into a separate MCP server. 2. The magic is in the prompts (1200 lines of…
2025 · github.com
- 18AC
Built an AI code reviewer using Letta (Python) that I can call natively from Rust applications. The interesting part: real-time streaming works perfectly across the language boundary with zero hassle using RunAgent. The agent runs in Python with persistent memory, leverages the best in house agentic memory management with Letta (Pythonic AI agent framework), and my rust code just uses it (kinda) natively, though Letta has no Rust bindings. And, streaming works like magic. No FFI, no complex bridges - just native async/streaming that feels like calling any Rust librar, but without…
2025 · medium.com
- 19IB
I’ve spent the last 2.5 months building a product that runs LLM-powered code reviews on my pull requests — and I just launched it. The tool is built specifically for solo developers. You install it on your repo, trigger a scan by creating a pull request, and it leaves structured review comments using OpenAI under the hood. Funnily enough, I used the dev version of this app to review its own pull requests while building it. It helped me spot bugs, simplify structure, and keep quality high — all with minimal need for another human in the loop. Things I want to try out in the next months : -…
2025 · codii.dev
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Hi HN. I'm the founder of Phoenix Labs (ex TikTok, Applied AI) and we're open sourcing our internal tooling today which is like a toolchain / meta-harness for CLI agents useful for really scaling eng and creative work. We are a very small team who's building a very ambitious product so we had to find ways to squeeze every ounce of efficiency that we could get our hands on. Harness strengths of different models (Claude, GPTs) and CLI-harnesses (Claude Code, Codex), safe/robust browser integration to speed up UX/QA testing, teams cli to speed up security reviews and parallelize…
May 2026 · agents-cli.sh
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Hi HN, This is a project I've been working on since the beginning of 2025 full time, without funding. Coding agents have fundamentally changed the way we write software. When you let an agent write code, pull dependencies, and run scripts, you are delegating trust while still keeping the responsibility. You shouldn't have to choose between moving fast with agents and maintaining basic control over your host machine. Normally, we just inspect the final result, treating the app like a black box. Most security tools only sandbox the app runtime and ignore the build phase. CapaKit is my attempt…
Jun 2026 · capakit.com
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I built CodeLens.AI - a tool that compares how 6 top LLMs (GPT-5, Claude Opus 4.1, Claude Sonnet 4.5, Grok 4, Gemini 2.5 Pro, o3) handle your actual code tasks. How it works: - Upload code + describe task (refactoring, security review, architecture, etc.) - All 6 models run in parallel (~2-5 min) - See side-by-side comparison with AI judge scores - Community votes on winners (blind voting) - Each evaluation gets reflected in the overall AI model leaderboard, showing us best ones Why I built this: Existing benchmarks (HumanEval, SWE-Bench) don't reflect real-world developer tasks. I wanted to…
Oct 2025 · codelens.ai
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Hi HN! Last night, I live streamed myself coding this Llama 2 Agent on a Single GPU (Colab). After 6 hours it actually has some good results. How it works is it takes in your intuition (e.g. "I think x would be cool") and develops a business idea (with a name and branding colors) and a business plan. After the business plan is developed, it criticizes this plan recursively until the "Investor" prompt is satisfied with the plan. After all this it will generate the final MVP idea and pass it to a the React Engineer Agent I live coded 2 days ago…
2023 · github.com
- 24IB
Hey HN. I built an AI agent harness over the past few months and I'm open sourcing it today. Some context on why. I've been building with Claude Code daily using this harness. It orchestrates multiple AI agents as a team, with a dashboard, chat, kanban board, the works. I used it to build a full SaaS product (MyUpMonitor, https://myupmonitor.com) in about 24 hours of focused coding. Then yesterday Anthropic announced Mythos and decided to keep it behind closed doors. Meanwhile I'm paying for Claude and I can't access their best model. I don't think that is nice at all... So I'm…
Apr 2026 · github.com
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