When you build a PowerShell project from multiple files, the natural structure is clear: enums first, then classes, then functions. Each group has its own place, and as long as dependencies only flow in one direction, that structure works perfectly. But sometimes a function depends on a class, and that class calls the function. There is no longer a clean boundary between the two groups — they need
TL;DR You can integrate Azure DevOps with GitHub to get the best of both worlds in Power Platform development. ADO stays as the backbone: work items, sprint planning, test plans, and deploy pipelines all remain on Azure DevOps. Code moves to GitHub: Power App Code Apps or Power Pages SPA live in GitHub repos, unlocking native GitHub Copilot integration and the Copilot Cloud Agent. The two platfo
The drift problem nobody told you about If you have used Claude Code, Cursor, Aider, or any other AI coding agent across more than two projects, you have felt this: You start project A. You copy the .agents/ folder (or CLAUDE.md, or .cursorrules) from your last project. You tweak two things. Done. You start project B six weeks later. You copy from project A. You tweak three things this time. Now
Cross-posted from the Stigmem blog. Today we're releasing stigmem v1.0: A stable, open-source specification and reference implementation for a federated knowledge fabric for AI agents. Stigmem = Stigmergy + Memory. Stigmergy (Greek stigma — mark; ergon — work) is the coordination mechanism you see in ant colonies and termite mounds: agents don't communicate directly with each other. Instead, they
More rules should mean better output. That's the intuition. I spent weeks building a comprehensive CLAUDE.md — 200 lines covering naming conventions, security rules, error handling, architectural patterns, import ordering, type safety requirements, and more. I was proud of it. I'd thought through every scenario. Then I scored the output. 79.0 / 100. My carefully crafted documentation was actively
Hello Developers! 👋 Most developers today pick a side: Let’s talk about combining C++ and JavaScript—the ultimate hybrid stack for high-performance applications. 👇 1. The Core Engine (C++) ⚙️ 2. The Browser Bridge (WebAssembly) 🌉 3. The Cinematic Experience (Vanilla JS + UI/UX) ✨ The Takeaway 🎯 Keep optimizing, keep building! 💻✨ ~ Ujjwal Sharma | @stackbyujjwal About the Author 👨💻 Ujjwal
I built a Vamana-based vector search engine in C++ called sembed-engine. Recently I made a pull request that sped up queries by 16x and builds by 9x. The algorithm stayed exactly the same. The recall stayed at 1.0. The number of visited nodes did not change. The speedup came from data layout. The original code stored vectors as separate objects pointed to by shared_ptr: struct Record { int64_t
The first time I implemented Vamana from the DiskANN paper, my approximate nearest neighbor index was slower than brute force. On tiny test fixtures, brute force took 0.27 ms per query. My Vamana implementation took 22.98 ms. That sounds absurd. ANN exists to skip work. The problem was not the algorithm. It was how I mapped the paper's abstractions to actual data structures. The DiskANN pseudocode