DeepClaude: combiné Claude Code con DeepSeek V4 Pro en mi loop de agentes y los números me desconcertaron DeepSeek V4 Pro resuelve correctamente el 94% de las tareas de razonamiento profundo en mi loop… pero el costo de latencia lo hace inutilizable para el 60% de mis casos de agente. Sí, leíste bien. Y eso cambia completamente la narrativa de "combinar modelos es siempre mejor". El martes a la
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
Specsmaxxing: escribí mis specs en YAML para mis agentes y esto cambió (y esto no) Una spec en YAML para un agente de IA es básicamente como el plano de obra que le dejás al albañil cuando no podés estar presente. Si el plano está bien, el tipo levanta exactamente lo que querés. Si el plano tiene un solo detalle ambiguo — "pared al fondo" sin medidas — el tipo toma una decisión, y cuando volvés,
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
Hash tables feel like the default choice for membership tests. std::unordered_set promises average O(1) lookup, so we reach for it automatically. In performance-sensitive C++ code, that habit can cost you an order of magnitude. I ran into this while building a Vamana graph index for approximate nearest neighbor search. The algorithm needs to track visited nodes. Node ids are dense integers, and th
A production-grade embedded system enabling communication across speech, text, Morse, and haptic signals within a single unified pipeline. Official Project Page: https://anandps.in/projects/unified-assistive-communication-system GitHub Repository: https://github.com/anand-ps/unified-assistive-communication-system Problem Assistive communication systems are fragmented. Most tools so
Barman reemplaza a pgbackrest: migré mis backups de Postgres en producción y esto encontré El fin de semana que migré de Vercel a Railway — el mismo que mencioné cuando hablé de cold starts — pasé casi doce horas leyendo logs de Postgres que nunca había tenido que leer tan en serio. No era un tutorial. Era producción real, datos reales, y la pregunta de fondo era siempre la misma: si esto explot