Articles
8 posts tagged "AI Economics"
Encoded Judgment: How a Cheap Model Performs Like an Expensive One
I ran a product team that captured every customer question into a playbook before handing it off. That old loop is exactly how you make a cheap AI model carry expensive work.
Loop Engineering: For me it's about using dumber models and smarter code
My take on loop engineering: push judgment onto dumber, cheaper models and smarter code over time, so a long-running agent gets cheaper and more trustworthy with use.
Five Paradigm Shifts You Need to Embrace About AI
Five paradigm shifts from three years building with AI: design time over runtime, judgment over prompts, real feedback loops, conversation, and knowledge that's built, not stored.
How to Stop Burning AI Budget Without Stopping What AI Lets You Do
Companies are blowing through AI budgets, but pricing isn't the real cause. Two habits keep my bills flat without rolling back what AI lets me do.
Why Your AI Bill Is Too High (And the Architecture Fix That Saves 40%)
Most companies run their AI like a doctor's office. The ones that scale run it like an ER. Here's the architecture decision that cuts AI costs by 40%.
Why I Build Before I Write Requirements (And Why AI Makes That Smart)
After 20 drafts of our core product over more than a year, I've learned the most valuable requirements come from building — not planning. Here's what negative specification taught me about product development with AI.
How Should Your Strategy Change When Coding Costs Shrink to Nothing?
When coding costs shrink to nothing, the smart strategy isn't perfecting one version. It's generating many and synthesizing the best.
There Are Two Kinds of AI Work. What If You're Missing One?
There are two kinds of AI work — design-time and runtime. Most people throw everything at runtime, making it slow and expensive.
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