SAP’s updated API policy blocks third-party AI agents from accessing its data, and it’s not a SAP story. It’s a preview of how enterprise platforms will use policy as a competitive weapon against the AI ecosystem built on top of them.
Coinbase cut 700 people and cited AI as part of the reason. The coverage focused on the human cost. Founders should focus on the operational model it signals instead.
Anthropic is raising at a $900B valuation. The founder instinct is to panic. The non-obvious read: the bigger this arms race gets, the better it is for small builders.
Every SaaS product was built assuming the user has hands. Computer-use AI just made that assumption worth questioning.
Anthropic may hit a $1 trillion valuation. Most founders haven’t seriously gamed out what that means for the products they’re building on top of AI APIs. The risk isn’t just pricing — it’s whether your differentiation lives in a layer you actually own.
LinkedIn just disclosed $450M in annual revenue from its agentic hiring tools. That's not a feature metric. Here's what it signals for every B2B founder still building AI as a bolt-on.
Everyone talks about how much AI coding tools save. Fewer people publish the actual numbers. Here’s a real cost breakdown — including the hidden expenses most founders don’t account for.
Building every feature yourself feels like ownership. It’s usually just overhead. Here’s a clear-eyed look at the real cost of DIY feature development — and how to know when to stop.
Most founders making AI product development decisions right now are walking into the same trap: building is too easy. The cost of shipping a feature dropped to near zero.
Edge AI chips are where startups should focus. The real hardware battle is not in cloud GPUs. It is in embedded, low-power, device-side inference.
Cerebras filing for IPO at $35B reveals the compute layer beneath every AI product is consolidating fast. Here is what founders building on AI infrastructure need to understand about pricing power and switching costs.
Most founders choose their AI model the same way they pick a laptop: look at the benchmark scores, pick the highest number. That approach will cost you in production.