Three weeks ago I shipped IndieOps — a free invoicing and client management tool built specifically for freelancers. Here's the honest version of how it went. It handles the boring-but-critical stuff that eats freelancer time: creating professional invoices, collecting payments via Stripe, sending automatic payment reminders, and keeping a client directory. All free. No "upgrade to send more than
Last week I posted that I had no code, just the work that makes the code possible. The PRD, the prompt spec, the architecture doc, the build brief for Kiro. I went into this week thinking I had every decision pre-made. Then I started building. By Block 2, real testing surfaced a phrase the model was using that no court employee would say. "Strip identifiers" sounds reasonable to a developer. To a
The Small Problem No One Talks About Sometimes the text is correct… But it still feels wrong. You write something like: “hello everyone welcome to my post” It’s readable. But it doesn’t feel… good. When I wanted text to stand out, I’d: Add emojis Try different styles manually Copy from random websites Paste weird Unicode text Half the time: 👉 It broke formatting This wasn’t about “writing bette
TL;DR: I shipped image → PDF conversion but spent most of the week on SEO content instead of the planned batch UI and landing page. The numbers say that was the right call. Organic search became the #1 traffic source for the first time. Convertify is a free image converter I'm building solo: Rust + Axum + libvips on the backend, Next.js 16.2 SSG on the frontend, PostgreSQL for landing page content
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
When I first started building my real-time chat platform, most of the focus was on the core experience: instant access no signup low friction fast WebRTC connections Initially, almost all traffic went to the homepage. But over time, I realized something important: Instead of targeting only broad keywords like: anonymous chat random video chat I started creating country-specific and intent-focused
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