tracehub-mcp: Giving AI Assistants a Real Query Interface Into Your LLM Traces
The Copy-Paste Problem Here's what debugging an LLM application looks like for most people today, including me until recently: something is slow, or…
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The Copy-Paste Problem Here's what debugging an LLM application looks like for most people today, including me until recently: something is slow, or…
The query that shouldn't have run Give an AI agent a warehouse MCP server and, sooner or later, it will write a query that scans a full multi-teraby…
The software engineering toolkit is undergoing its most radical transformation since the transition from raw text editors to integrated development…
AI is writing more of our code every day. But are we paying close attention to what happens when that code quietly fails? → Silent failures are the…
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 a…
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…
After building 50+ AI systems, here is what we know about agentic coding models and the burgeoning open-source AI frontier, particularly with the gr…
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 t…
The first number anyone quotes when asked what generative AI costs is a per-token figure. It is a comfortable number — small, unambiguous, available…
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…
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…
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 c…