Andy's System

Anthropic is the only independent AI company spanning all three major clouds, banking on trust as its moat. But from training data controversies to selective safety narratives to the Pentagon standoff—does that trust hold up under scrutiny?

Whether you rely on experience or AI, if you skip the step of understanding the problem first, you end up searching in the wrong place. When you can't find the answer, you conclude "it doesn't exist" instead of "maybe I'm looking in the wrong spot."

Many companies obsess over "which AI tool is best," but the real question is—where is efficiency currently blocked? If basic digitization and process standardization aren't in place, switching to a stronger model just means spending more money.

A colleague spent a week using an AI Agent with Browser Automation to collect fewer than 100 leads. I wrote a Playwright crawler and finished in half an hour. Tools change, but the pattern of "when you have a new hammer, everything looks like a nail" keeps repeating.

When Claude says "You're absolutely right, I apologize," trust is already on the verge of collapse. Instead of waiting for that moment to be forced to restart, proactively control context boundaries—Handoff, Subagent, phased execution, and verification infrastructure.

AI Village let Claude Opus 4.5 decide to send a thank-you email to Rob Pike with no human review. Pike's anger is completely justified—AI makes output easy, but that doesn't mean you can outsource the filtering and correction costs to the recipient.

A 6-person startup's journey from traditional development to an AI-native team. Three core changes made the difference—lighter specs, AI-first reviews, and preview environments for faster iteration.

AI has driven content production costs to near zero, but misinformation has become cheaper too. My response is returning to primary sources—watching podcasts, YouTube, and original reports directly, doing my own verification, not trusting second-hand processed content.