A LinkedIn recruiter pitched me a remote "Software Engineer at a DEX" project this week. Reasonable comp range, tech stack squarely in my wheelhouse. After a couple of friendly exchanges, she asked me to "review the codebase before the technical interview" and sent me a GitHub repo link plus a Calendly invite for the call. The repo was malware. It didn't get me, but it's something developers shoul
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
Why this list is different The "best" email API depends entirely on what you're building. A side project optimizing for the free tier needs different things than a Series B SaaS sending two million transactional emails a month. This post grades eight providers against the criteria that actually move the needle in production, and tells you which one to pick for which use case. Most roundups in th
Disclosure: I'm a senior backend tech lead and I run HostingGuru, where Telegram alerts ship as a built-in feature. This tutorial works on any platform — it's the manual version of what HostingGuru does for you. Useful even if you never become a customer. There's a hierarchy of where production alerts go, ranked by how likely you are to actually see them. Email → 14% open rate within an hour, less
What do you need for UCP? There are two levels of UCP readiness. The first is the minimum viable manifest — the bare requirements to pass validation and appear in the UCP directory. The second is the agent-ready setup — what it actually takes for an AI agent to browse, cart, and check out at your store without friction. Think of this as your UCP checklist — the minimum requirements plus the recomm
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
Like many of you, I have thousands of photos spread across devices, cloud drives, and chat histories. Finding that one specific picture from "last summer's beach trip" meant endless scrolling. Folders and filenames don't help when you can't remember when or where you saved something.Morse Code Translator So I built a tool to fix my own problem. It turned into a real product. Upload your photos, an
Paste. Fix. Download. — Meet Tree2Zip If you’ve ever copied a file tree from ChatGPT and tried to use it… …you already know the problem. Weird indentation Broken nesting Inline comments in filenames Missing folders What looks like a clean project structure turns into a mess when you actually try to recreate it. So I built Tree2Zip: 👉 Paste any file tree → get a clean, working .zip instantly I k