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Subscribe • Previous Issues Why Your AI Agents Need Engineering Instead of Best Practices I remain optimistic about the impact agents will have on knowledge work. As I noted in an earlier article, fields shaped by clear rules and mature systems, including accounting and contract management, already look well suited to this kind of automation. But even if the opportunity is real,…
Subscribe • Previous Issues The Agentic Sweet Spot: Where AI Moves Fast and Humans Stay in the Loop A recent Anthropic study on agent autonomy offers a clear preview of where knowledge work is headed. Anthropic analyzed millions of real interactions across their public API and Claude Code to see how people actually deploy autonomous systems. The catch is that their clearest…
Subscribe • Previous Issues How Teams Actually Use RL to Make Agents Reliable I have had a longstanding fascination with reinforcement learning (RL) and have monitored its slow diffusion from research labs into enterprise production. Much of the recent activity remains concentrated among foundation model builders and teams with dedicated post-training capacity. They use RL after pre-training to make large models reliable…
Subscribe • Previous Issues The Honeymoon Phase Won’t Last: Preparing for AI’s Platform Shift I am old enough to remember the early days of the internet. It was a time when blogs were everywhere and information felt decentralized. Before the giant platforms and their algorithms, the web felt like a collection of independent voices. We had chronological feeds we controlled, not algorithmic…
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