Enterprise AI

My take on WTO's AI trade report: infrastructure gaps, labor impacts, and projected economic gains varying significantly by country income level.

Learn what AP2 actually does, why the proof matters, and which early automations are worth piloting.

Breaking down Gartner's bold claims about agentic AI adoption and explaining why CIOs should watch tech progress instead of rushing strategy.

A practical guide to selecting LLM models and providers based on your product's specific needs and constraints.

Testing Lovable, Replit, and Bolt.new shows their struggle with custom logic. A comparison of no-code platforms' real capabilities.

While no-code tools dominate, developers who do everything need scriptable, API-first tools. This underserved market is growing fast.

Success in LLM applications comes from niche focus, speed to market, and cost optimization, not big funding or features.

Like ML's loss function, your product needs one metric to optimize while others serve as guardrails. Choose wisely.

As frontier model improvements slow down and trust increases, enterprises have a unique window to adopt LLMs without the risk of rapid obsolescence.

Marketing doesn't work like code deployment. Learn why search ads can bridge the gap between engineering certainty and marketing chaos.