Content moderation is a high-stakes needle-in-a-haystack problem. Over 90% of AI-generated content is benign, but the rare harmful slice carries high severity, making detection both difficult and critical.

Code review of AI-generated scientific papers found only ~30% of claimed discoveries were real, down from an initial novelty assessment of 70-80%.

GitHub distributes its CLI to non-technical employees and grants agents broad read access to internal communications as a way to democratize AI tooling inside the company.

Comfy UI allows users to set a fixed seed ensuring exact reproducibility of image generations, unlike other models that hide parameters like seed.

The same landline phone product is tracking toward $5 million in annual revenue in 2026.

The market will support at most 4-5 large language models, with only 2 being very large winners; the rest will merely get by or the field will consolidate down to 2 over time.

Daniel Mesler coined the term 'bitter lesson engineering' to describe iteratively updating AI harnesses as underlying models improve. Worth watching as a practitioner framework for managing model churn.

“Any company who takes that call that we're going to respond to the market is already dead.”

“I don't think the stock market cares about the price of oil. I think it cares about these crisis events.”

“It's not the P that's the bubble, it's the E.”

“Get out of the feedback business. Get in the recommendation, suggestion business.”

“My job wasn't to add process. It was to restore social contract.”

“If every deal is right in a roll-up, we're either not taking enough risk or not moving fast enough.”