Subscribe • Previous Issues The AI Visibility Playbook: Surviving the Shift from Search to Synthesis More people are turning to AI chatbots instead of traditional search engines to find information online. Even Google now displays an AI Overview at the top of many search results to summarize answers directly. When search engines ruled the internet, search engineContinue reading “AI is describing your competitors better than you. Here’s why.”
Category Archives: Uncategorized
Why People Say “MCP Sucks”: Which Critiques Matter Most
The practical takeaway is straightforward. The strongest objections to the Model Context Protocol (MCP) are not ideological. They are operational. They center on token cost, security, cloud deployment, and enterprise controls. The weaker objections tend to be broader complaints that MCP is unnecessary or too closely tied to Anthropic. For teams building AI products, theContinue reading “Why People Say “MCP Sucks”: Which Critiques Matter Most”
How to Stay Employable When AI Is Coming for Your Job
Over the past few weeks, I have had a lot of conversations with people who are genuinely worried about what AI means for their careers. Not just developers, but marketers, analysts, lawyers, and others who are starting to wonder how much of their job will exist in 2-3 years. The anxiety is real and notContinue reading “How to Stay Employable When AI Is Coming for Your Job”
Why the heaviest AI users actually produce worse results 🤯
Subscribe • Previous Issues How to Stay Employable When AI Is Coming for Your Job Over the past few weeks, I have had a lot of conversations with people who are genuinely worried about what AI means for their careers. Not just developers, but marketers, analysts, lawyers, and others who are starting to wonder how much ofContinue reading “Why the heaviest AI users actually produce worse results 🤯”
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, the practical reality is that AI teamsContinue reading “Why Your AI Agents Need Engineering Instead of Best Practices”
Why smarter agent architecture does not always improve results
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 evenContinue reading “Why smarter agent architecture does not always improve results”
NVIDIA’s Next Moves: A Practitioner’s Guide to GTC 2026
NVIDIA’s GTC 2026 conference, held March 16–19 in San Jose, delivered a sweeping set of announcements. The throughline across hardware, software, models, and partnerships is clear: NVIDIA is engineering a vertically integrated stack that spans from silicon to agentic application frameworks and humanoid robots, positioning itself as the central platform vendor for the entire AIContinue reading “NVIDIA’s Next Moves: A Practitioner’s Guide to GTC 2026”
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 view comes from Claude Code, where they can track longer workflowsContinue reading “The Agentic Sweet Spot: Where AI Moves Fast and Humans Stay in the Loop”
When AI does the junior work, how do we train seniors?
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. TheContinue reading “When AI does the junior work, how do we train seniors?”
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 at executing tasks, not just generatingContinue reading “How Teams Actually Use RL to Make Agents Reliable”