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Startups.RIP is a useful first example for AI in the Wild: failed startup history becomes product memory when agents can compare what was tried, why it broke, what changed, and what to test next.

The interesting GPT-5.5 question is not whether it is smarter. It is where the model leaves less unfinished work behind, and whether that reduction is worth the premium routing cost.

OpenAI shipped GPT Image 2 today. It is the new ceiling on text + UI mock realism. Google still owns cost. Black Forest Labs owns open weights. Ideogram owns dense typography. Firefly owns brand safety. Here is the honest map of the field after today, and a one-line recipe for picking the right model per job.

Chrome MCP drives my week. Playwright ships my builds. Everything else sits further down the stack. Here's the honest ranking after actually using each one, with the exact job each is best for.

The useful prompt was not 'design me a dashboard.' It was 'show me what needs human judgment now.' That shift turned Claude Design from novelty into a real workflow tool.

The shocking part of U.S. market infrastructure is not the chart. It is the amount of free, public corporate data sitting in SEC systems, and how much product value still comes from making that data usable.

I asked two local models for five JSON objects. One took 27 seconds. The other took 3 minutes and 26 seconds deliberating before producing the same array. That gap changed my default.

I built a vibe-based image search tool to understand what multimodal embeddings actually change. The short version: captions are no longer the only bridge between what users mean and what systems can find.

OpenAI's Atlas browser has a reactive Ask ChatGPT sidebar and a proactive suggestion layer that changes per page. The second layer is the actual product insight, and it points to where all AI tools are headed.