Most conversations about AI transformation ask whether the technology can do the work. We debate accuracy, cost, reliability and how quickly companies can move from pilots to production. I expect the technology to keep improving. I’ve become more interested in what happens when the answer is yes. In Migrating Scarcity, I argued that when technologyContinue reading “The Corner Case: What Happens After AI Does the Easy Work?”
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AI Won’t Kill the SDLC. It Will Reprice It.
Everyone seems to agree on the same story: agents write the code, and the tools we already use stick around. Jira orchestrates the agents, GitHub verifies their work, Terraform enforces policy. I buy the first half. The second half assumes that because a function survives, the vendor performing it keeps getting paid. That doesn’t follow.Continue reading “AI Won’t Kill the SDLC. It Will Reprice It.”
Harness Learning: Who Gives the Proposer Permission?
I came across a paper on harness learning that got me thinking about something we don’t discuss enough in enterprise AI. We spend a lot of time worrying about what agents are allowed to do. What happens when they can also change how they do it? The researchers train a model, called a proposer, toContinue reading “Harness Learning: Who Gives the Proposer Permission?”
