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,…
Context Is the Moat. Not the Model. Most teams building AI products are optimizing the wrong thing. They debate model size, chase benchmark scores, and spend weeks on fine-tuning runs. Then they ship something that feels hollow. Generic. Like a customer support bot that clearly has no idea who it’s talking to. I’ve seen this…
Google Stitch Just Leveled Up. Here Is What Designers and Builders Should Actually Think About That. The design community had a collective moment this week, and I think the reaction is telling us something more interesting than the tool itself. Google’s Stitch dropped what can only be described as a significant overhaul. Five major upgrades,…
The Study Nobody Is Reading Correctly Anthropic just published what they’re calling the largest qualitative study of AI users ever conducted. 81,000 people. One week. And most of the coverage I’ve seen misses the point entirely. Everyone is focused on the number. 81,000 is a big number, so people write about the number. But the…
Google’s AI Ecosystem Is Building the Operating System Nobody Else Can Copy Min Choi said it plainly this week on X: “The next AI war won’t be Claude vs ChatGPT. It’s who will own the entire AI operating system.” I think he’s right. And I think most developers building on these platforms right now are…
The Indispensable Engineer Trap (And Why I Walked Right Into It) For most of my early career, I optimized for the wrong thing. I made myself the person who knew where all the bodies were buried. The one who understood the legacy pipeline no one else had touched in three years. The one you called…
The Hardest Skill in AI Engineering Is Knowing When to Stop I’ve been sitting with a uncomfortable observation for a few months now. We’ve crossed some kind of threshold in AI tooling where the answer to “can an agent do this?” is almost always yes. The models are capable enough, the frameworks are mature enough,…
I’ve shipped games. I’ve spent entire afternoons obsessing over the curve of a character’s eyelid, the way light catches the edge of a lip, the exact desaturation that makes a stylized world feel intentional rather than unfinished. Those choices aren’t accidents. They’re craft. So when NVIDIA announced DLSS 5 at GTC 2026 — real-time AI…
Microsoft just open sourced BitNet, and I think people are sleeping on how significant this actually is. While most of the AI conversation stays locked on GPU clusters, foundation model releases, and cloud API pricing, something quietly landed that could change the entire equation for how and where large language models actually run. Let me…
Most AI engineers I know are solving the wrong problem. We obsess over model quality. Benchmark scores. Parameter counts. Token speeds. And I get it — these things feel concrete. They are measurable. You can point to a number going up and feel like you made progress. But the actual bottleneck in most production AI…
40.9K Stars and a “Junior Engineer With Poor Taste” — What the Superpowers Repo Is Really Telling Us A GitHub repository called Superpowers just crossed 40.9K stars, and I think it’s one of the more honest signals we’ve gotten about where AI coding agents actually stand right now. Not from a benchmark. Not from a…
