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News
When Every Event Looks Normal: Logster and the Context Gap in Endpoint Detection
9+ hour, 9+ min ago (1029+ words) A PowerShell process starts. A script appears in a temporary directory. A scheduled task is registered. A connection goes out to an unfamiliar address. An analyst could find a reasonable explanation for each of those actions. Software deployment, perhaps. A…...
One global threshold is how you delete valid data
13+ hour, 47+ min ago (388+ words) Our GPS filter worked perfectly, right up until someone sat in Bangalore traffic. A parked phone does not sit still in the data. The reported position wanders a few metres in every direction, and if you naively sum the gaps…...
Real-Time AI Monitoring: Catching Model Drift Before It Costs You
9+ hour, 49+ min ago (499+ words) Then there’s the drift your own team introduces. Someone tweaks a system prompt to fix one edge case and shifts the distribution of every other output. A retrieval index gets rebuilt with a different chunking strategy. A fallback route that…...
The Logging Dilemma
15+ hour, 44+ min ago (123+ words) Every developer has lived through this scene: the adrenaline spike when a production incident is... Tagged with go, monitoring, logging, module....
First Rollback: Revert the Agent PR You Cannot Explain
21+ hour, 12+ min ago (783+ words) Your first AI pull request will often need rollback. Plan that rollback before you merge anything. You lack repo history on day one. Agents still produce large and confident diffs today. A rollback plan keeps that blast radius tiny. First…...
🔥 Stop using 500KB heavy telemetry packages for basic logs or canvas tracking. Rebuilding BeeLadybug 🐞: a zero-dep universal visual debugger with a blind Core & Shadow DOM overlay. No lag, no style conflicts 🚀 Check out the full breakdown 👇
21+ hour, 42+ min ago (12+ words) Riscrivere BeeLadybug da zero: dall'engine di gioco al Debugger Universale......
Five Failure Modes Evals Won't Catch And What To Do About Them
1+ day, 2+ hour ago (1076+ words) Evals are a critical part of every data and AI team’s agent development process. An engineer builds an eval, defines what a bad answer looks like, runs a judge against a test set, and ships when the score looks good....
tracehub-mcp: Giving AI Assistants a Real Query Interface Into Your LLM Traces
1+ day, 3+ hour ago (102+ words) The Copy-Paste Problem Here's what debugging an LLM application looks like for most... Tagged with aiengineering, mcp, observability, opensource....
How Developers Can Monitor Production — and Why It Matters
1+ day, 9+ hour ago (352+ words) When we write code, it often feels like the main thing is to make it work locally. But reality is different: the real life of a service begins not on your laptop, but in production. That’s where it faces load,…...
tokeneff: An Open-Source LLM Cost Meter That Runs Locally
1+ day, 15+ hour ago (338+ words) Most LLM dashboards show you the bill after the damage is done. You run a coding agent for an afternoon, ship a feature, and two days later your OpenAI dashboard says you spent $47. On what? Which model? Which request? You…...