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I A/B Test My Prompts Like a Scientist

Most teams evolve prompts by feel. Change something, eyeball the output, ship it if nobody screams. This is alchemy, not engineering. When your system is non-deterministic, a single successful run proves nothing. I built an eval harness that runs prompt versions head-to-head — 10 runs each, scored on behavior, measured on cost and latency. No vibes. No guessing. Just data that tells you exactly what improved, what regressed, and what it costs.

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AI Vision Is a Game Mechanic Now

There’s a category of game that couldn’t have shipped two years ago. Not because the hardware didn’t exist, or the game design theory wasn’t there, or the players weren’t ready. The core mechanic was impossible. It required a machine that could look at a picture, understand a natural language question about it, and answer accurately — in real time, at scale. That machine now exists. And it unlocks game designs that no one has explored yet.

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Build Exactly What You Want

For decades, your computer experience was dictated by what someone else decided to build. You bought the operating system. You paid for the productivity suite. You subscribed to the project management tool that did 60% of what you needed and learned to live with the other 40% — the missing features, the clunky workflows, the integrations that never worked quite right. That era is over. Agentic coding means you describe what you want in natural language, and a frontier AI agent builds it. Not eventually. Now.

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Product Review Is the Future

Code review is dying. When agents own the code, staring at diffs is the wrong job. But that leaves a vacuum. If senior engineers aren’t reviewing pull requests, what are they reviewing? The answer is the product itself — its surfaces, its behaviors, its capabilities. Product review is the emerging discipline that fills the gap, and the teams that figure it out first will ship circles around everyone else.

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