There is a quiet assumption embedded in most agent infrastructure: that agents need structured interfaces.
Last week, I dropped an LLM agent into a plain HTML file. No Node.js. No Webpack. No Docker container running a Python backend that proxies to another…
In February 2026, we pointed a browser-embedded AI agent at a demo e-commerce store and asked it to buy a laptop stand.
When Moonshot AI demonstrated its Kimi K2 model tackling a PhD-level mathematics problem in hyperbolic geometry, according to examples published in their…
There's a delicious irony at the heart of modern AI development. We've spent years training large language models on every scrap of code humanity has ever…
AI hallucinations refer to instances where a model generates a confident response that sounds plausible but is factually incorrect or entirely fabricated .
For years, the language model arms race seemed to belong exclusively to cloud providers and their API keys.
If you've been building with large language models, you've hit this wall: every API call requires re-explaining your entire workflow.
The AI revolution has a dirty little secret: most organizations can't actually use it for their most important work.
For decades, software engineers have endured a peculiar form of professional imposter syndrome. While their colleagues in mechanical, civil, and chemical…