trelix v1.0 to v2.7: When "It Works" Meets "It Scales"
Twelve days after I shipped trelix v1.0.0, I was staring at a RetrievalConfig object with two conflicting sets of values and no idea which one was act…
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One agent, many skills: structuring a production AI assistant
We didn't give our AI agent one big brain. We gave it skills. We built a conversational AI inside an enterprise SaaS platform, where users get work do…
LongCat-2.0 & Agentic AI: Reshaping India's Tech by 2026
After building 50+ AI systems, here is what we know about agentic coding models and the burgeoning open-source AI frontier, particularly with the grou…
From Vibe Coding to Verified Engineering
AI agents should not just generate code. They should produce evidence . That is the core idea behind Agile V: → Requirements before implementation → I…
Six Levels of MCP Servers
Most MCP servers I see in production are stuck at Level 1 or 2. They wrap an API, expose some tools, and stop there. The result: an agent that can tec…
What GenAI Actually Costs in Production
The first number anyone quotes when asked what generative AI costs is a per-token figure. It is a comfortable number — small, unambiguous, available o…
The Token Tax Problem: How I Built a Super Memory Layer for AI Coding Assistants using LLM Wiki
The Token Tax Problem: How I Built a Super Memory Layer for AI Coding Assistants We Solved the Wrong Problem First When AI coding assistants arrived, …
Production LLM Guardrails: 8 Controls Every AI Team Needs
Most AI projects fail somewhere between demo works and production ships . The gap is rarely the model. It's the absence of the controls that turn a on…
The Most Useful AI Workflow I’ve Built Isn’t About Writing Code
The Problem Wasn’t Triage Most AI workflows in software engineering still keep the human directly in the middle of triage. The AI might help write cod…