An opinionated list of Python frameworks, libraries, tools, and resources
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.
A College Project That Planted a Seed Years ago I was on a university team trying to build a Go AI. We explored monte carlo simulation for lookahead search, basic neural networks for pattern recognition, and expert systems for encoding domain knowledge. None of them worked well enough on their own. Go's branching factor is enormous, so brute-force search fails quickly. Neural networks without th
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
DeepClaude: I Combined Claude Code with DeepSeek V4 Pro in My Agent Loop and the Numbers Threw Me Off DeepSeek V4 Pro correctly solves 94% of deep reasoning tasks in my loop… but the latency cost makes it unusable for 60% of my agent cases. Yeah, you read that right. And that completely blows up the narrative of "combining models is always better." Tuesday night I watched the DeepClaude post cli
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
Series: How Machines Learn: A Complete Guide from Zero to AI Engineer Phase 6: Machine Learning (The Core) You've been hearing "machine learning" for years now. Your phone uses it. Netflix uses it. Your spam filter uses it. Every tech company puts it in their job posts. And yet, if someone asked you right now to explain what machine learning actually is in plain words, you might freeze up a little