An opinionated list of Python frameworks, libraries, tools, and resources
Becoming a tech lead was the goal from pretty early in my career. I had a clear picture of what the role was. More responsibility, more influence over the work, more of the interesting problems landing on my desk because someone had to figure them out and that someone, finally, would be me. It read like the natural next step. The thing you graduate to once you're good enough. What that picture did
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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
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:
Reaching an annual salary of ¥8,000,000 is often seen as a major milestone for software engineers in Japan in 2026. On paper, it sounds like a ticket to a comfortable, upper-middle-class life in Tokyo. But is 8 million yen a good salary in Tokyo—really? But if you are coming from abroad—or if you've only looked at the "Gross" figure on your offer letter—you might be walking into a "logic bug" that
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
The 3 AM Nightmare Last week, I let an AI agent run loose on my production server. It was fine — until 3 AM. To interact with the agent, a user must first authenticate across Gmail, a support desk, and a payment platform — all before the agent takes its first action. Permission denied. Permission denied. Permission denied. Three different connectors. Three different auth systems. One very tired