In the world of 10-digit error codes and countless hours spent troubleshooting, tech support professionals are the unsung heroes who keep our digital lives running smoothly. They are the patient, compassionate frontline warriors who, despite facing a relentless barrage of problems, never shy away from going the extra mile to fix them. There’s no denying,…
Plausible Is Not Correct, and That Gap Is Where Production Dies There is a framing going around right now that I think every engineer working with AI-generated code needs to internalize before they ship another feature. It comes from a post by @KatanaLarp, and the core argument is this: LLMs do not write correct code….
OpenAI Just Launched a Security Agent. Here’s Why the Validation Step Is the Whole Point. Security reviews are where engineering velocity goes to die. They’re slow, they happen too late, and the person responsible for them is also the person trying to close four other tickets before end of week. Most teams treat security as…
Dario Amodei Put a Number on It. Now What? Anthropic’s CEO went on the New York Times podcast recently and said something most tech executives would never say out loud. He estimated there’s roughly a 20% chance that Claude is conscious. Not a metaphor. Not a dodge. An actual probability, stated publicly, by the person…
NotebookLM Cinematic and the Death of the “Nobody Read My Doc” Problem Google quietly dropped something last week that I think is being badly misread by most of the people reacting to it. NotebookLM Cinematic takes the audio podcast generator that already made content creators nervous and pushes it a full step further. You drop…
The Best Engineers I Know Are Getting Slower And I mean that as a compliment. Not slower because the tools are failing them. Slower because, for the first time, they have enough leverage to actually feel the weight of what they’re building. When you can produce in one hour what used to take two days,…
Data Freshness Rot: The Silent Killer of Production RAG Systems Most ML engineers I know are obsessed with model quality. Better evals, better prompts, better fine-tuning. And honestly, I get it. Model quality matters. But after watching enough production RAG systems quietly degrade over months, I’m convinced the real killer isn’t the model at all….
Data Freshness Rot: The Silent Failure Mode Killing Your RAG System Everyone I know building AI systems is obsessed with model quality. Better evals, tighter prompts, more sophisticated retrieval. And that obsession is understandable. Model quality is visible. You can benchmark it. You can show stakeholders a chart. But the thing quietly destroying production RAG…
The Silent Killer in Your RAG Pipeline Most ML engineers I know are obsessed with model quality. Better evals, better prompts, more fine-tuning. I get it. Model quality matters. But the thing quietly destroying production AI systems right now is not a model problem at all. It is data freshness rot. And almost nobody treats…
Data Freshness Rot: The Silent Killer of Production RAG Systems Most ML engineers I know are obsessed with model quality. Better evals. Smarter prompts. More fine-tuning. And I get it, that stuff matters. But after years of building and debugging production AI systems, I’ve come to believe the thing quietly destroying most RAG deployments has…
Harvard’s ML Systems Curriculum Is Free Now. Here’s What That Actually Means. Prof. Vijay Janapa Reddi just open-sourced the entire Harvard CS249r ML Systems course. The textbook is on GitHub. The curriculum is public. The thing that costs tens of thousands of dollars per credit hour to sit near in Cambridge, Massachusetts is now free…
