A few months ago I started with a simple goal: have a solid, reusable base for my PHP projects without pulling in a full framework every time. What I ended up with is something I'm genuinely proud of, and today I'm making it public. php-template is a PHP 8.2 MVC starter template with serious tooling, full testing stack, and something I haven't seen in other PHP templates: native support for AI age
Metric Value Django Average Response Time 287ms Node.js Average Response Time 193ms Django Memory Usage (1000 users) 1.8GB We tested Django 4.2 and Node.js 18.16 under identical conditions to measure their performance for reporting dashboard workloads. The test environment consisted of AWS EC2 m5.2xlarge instances (8 vCPUs, 32GB RAM) running Ubuntu 22.04. Both frameworks connected to th
I was reading an Anthropic engineering post this winter that mentioned, almost in passing, that Claude Code's biggest token sink across their fleet is package-related queries. Every "how do I do X in Y", every npm install, every dependency audit. The model fetches the registry JSON, reads it, summarizes for itself, and only THEN answers you. I started measuring it on my own agent traffic. 74% of t
If you've ever built ETL pipelines pulling data from MongoDB into Delta Lake using Spark, you've probably hit this wall. The pipeline works fine — until it doesn't. A single document with an unexpected shape is enough to break the entire write, leave the table in an inconsistent state, and send your on-call engineer digging through Spark logs at 11pm. I built and maintained more than 10 of these j
By Nasarah Dashe This is Challenge #2 in a series. Read Challenge #1 here. Imagine waking up to 50 missed calls from your bank. You check your account balance. It is empty. A SIM‑swap fraudster convinced your telco agent to transfer your number to another SIM card, then used it to reset your mobile banking PIN and drain every kobo. Later that week, you receive an email from "Flutterwave Support" a
"Why does this auth flow use JWT instead of sessions?" My AI coding assistant gave a confident, well-formatted, completely generic answer. The actual reason was buried in a 2024-08 commit referencing an incident in our pager. The AI never saw it. Every conversation I had with my AI assistant started from zero. The codebase had hundreds of commits, dozens of architectural decisions, a graveyard of
GitHub has thousands of open-source apps with binary releases — but finding and downloading the right one is painful. Release pages are buried, and you're left squinting at filenames like app-1.2.3-linux-x86_64.tar.gz guessing which one is yours. So I built GHFrog — a browser-based app store on top of the GitHub API. No install, no account needed. Live: ghfrog.pages.dev · Source: github.com/iamovi
I've been building AQE (Atomic Quantum Engine), a DOM selector engine that replaces tree traversal with flat bitmask operations. Instead of walking the DOM on every query, each node gets a 64-bit BigInt mask at sync time. Matching becomes a single integer AND. AQE Light is the free, open-source version — zero dependencies, MIT license, on npm now: npm install atomic-quantum-engine I'm looking for