AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Originally published at Perl Weekly 771 Hi there, I put the 'Testing in Perl' course on hold for now. Instead of that we are going to explore the use of some of the mocking libraries we saw during the course. In the next session we'll pick one of the Perl modules used for mocking and we'll look for modules that use it. We'll try to understand how it is being used and we'll try to contribute someth
Building CLMA: A Self-Verifying Multi-Agent Framework from Scratch Posted on May 4, 2026 · #LLM #MultiAgent #CodeGeneration #OpenSource #SystemDesign #WebUI #SSE All code is open source on GitHub: github.com/kriely/CLMA If you've spent any time using AI for coding, you've experienced this cycle: ask → get code → try to run → it fails → paste error → get fix → something else breaks → lather, rins
My scrapers run on PythonAnywhere. My phone runs Termux. I wanted them to talk to each other. The standard options all had the same problem: they required infrastructure I didn't want to maintain. Firebase — cloud lock-in, SDK overhead, costs money at scale Ngrok — exposes a port on my phone, dies when the tunnel resets A VPS with Redis — another server to maintain, SSH into, keep alive Webhook to
Si usas Claude Code para programar ya sabes lo que pasa: abres una nueva sesión y el agente vuelve a improvisar. El contexto de la sesión anterior desapareció. Le describes la feature de nuevo, asume cosas distintas, y acabas corrigiendo código que nadie pidió. OpenSpec resuelve exactamente eso. Es un CLI open-source que inserta una capa de especificación versionada dentro de tu proyecto. Claude C
Manual content discovery is a core skill in application security testing. Instead of relying only on automated scanners, you can use simple HTTP requests and browser tools to find exposed files, hidden paths, and technology fingerprints. This covers techniques like checking robots.txt, fingerprinting favicons, reading sitemap.xml, inspecting HTTP headers, and spotting framework markers in HTML sou
Before you train a model, you need data in the right format. This took me longer than I expected and taught me a lot about how LLMs actually learn. I used MedQA USMLE — real medical licensing exam questions used to certify doctors in the US. It's available on HuggingFace for free. from datasets import load_dataset dataset = load_dataset("GBaker/MedQA-USMLE-4-options") Each sample looks like this:
Series: AI Isn’t an Engineering Problem Anymore (Part 2) In the last post, I talked about hitting a usage limit while debugging my robot and realizing how repetitive my own AI usage had become. When we use LLMs, whether through APIs or tools, it feels like every request is new. The inefficiency isn’t from using AI too much. You don’t ask once, you iterate. These are the most interesting ones. Some