New top story on Hacker News: Show HN: AI Code Detector – detect AI-generated code with 95% accuracy

Show HN: AI Code Detector – detect AI-generated code with 95% accuracy
12 by henryl | 2 comments on Hacker News.
Hey HN, I’m Henry, cofounder and CTO at Span ( https://span.app/ ). Today we’re launching AI Code Detector, an AI code detection tool you can try in your browser. The explosion of AI generated code has created some weird problems for engineering orgs. Tools like Cursor and Copilot are used by virtually every org on the planet – but each codegen tool has its own idiosyncratic way of reporting usage. Some don’t report usage at all. Our view is that token spend will start competing with payroll spend as AI becomes more deeply ingrained in how we build software, so understanding how to drive proficiency, improve ROI, and allocate resources relating to AI tools will become at least as important as parallel processes on the talent side. Getting true visibility into AI-generated code is incredibly difficult. And yet it’s the number one thing customers ask us for. So we built a new approach from the ground up. Our AI Code Detector is powered by span-detect-1, a state-of-the-art model trained on millions of AI- and human-written code samples. It detects AI-generated code with 95% accuracy, and ties it to specific lines shipped into production. Within the Span platform, it’ll give teams a clear view into AI’s real impact on velocity, quality, and ROI. It does have some limitations. Most notably, it only works for TypeScript and Python code. We are adding support for more languages: Java, Ruby, and C# are next. Its accuracy is around 95% today, and we’re working on improving that, too. If you’d like to take it for a spin, you can run a code snippet here ( https://ift.tt/OilGeIL ) and get results in about five seconds. We also have a more narrative-driven microsite ( https://ift.tt/exojnym ) that my marketing team says I have to share. Would love your thoughts, both on the tool itself and your own experiences. I’ll be hanging out in the comments to answer questions, too.

New top story on Hacker News: Show HN: AI-powered web service combining FastAPI, Pydantic-AI, and MCP servers

Show HN: AI-powered web service combining FastAPI, Pydantic-AI, and MCP servers
7 by Aherontas | 2 comments on Hacker News.
Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://ift.tt/OFslJ9S ) https://ift.tt/wDPZTlI... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers - MCP servers (Brave search, GitHub, filesystem, etc.) as tools - A2A communication between services - Minimal UI for experimentation for Tech Trend - repo analysis I built this repo because most agent frameworks look great in isolated demos, but fall apart when you try to glue agents together into a real application. My goal was to help people experiment with these patterns and move closer to real-world use cases. It’s not production-grade, but would love feedback, criticism, or war stories from anyone who’s tried building actual multi-agent systems. Big questions: Do you think agent-to-agent protocols like MCP/A2A will stick? Or will the future be mostly single powerful LLMs with plugin stacks? Thanks — excited to hear what the HN crowd thinks!