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”
Category Archives: Uncategorized
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”
8 domains where AI agents are actually working
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-trainingContinue reading “8 domains where AI agents are actually working”
What No One Tells You About Staying Employable in the AI Era
The Shift from Routine Execution to Spec-Driven Work Orchestrating Multiple AI Agents: A Skill That Won’t Stay in Software Engineering How to Protect Your Career When Your Output is Used to Train Models
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 ones controlled by someone else. AI isContinue reading “The Honeymoon Phase Won’t Last: Preparing for AI’s Platform Shift”
The warning signs your AI vendor is becoming your cage
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 chronologicalContinue reading “The warning signs your AI vendor is becoming your cage”
Ethics.dev
Ethics.dev is our new sister site that tracks the practical impact of AI across fields like safety, labor markets, government regulation, and the economy. Bookmark this page for daily updates on how these rapid developments will reshape your industry. It is designed as a practical resource to help you keep up with the complex rulesContinue reading “Ethics.dev”
The Industrialization of Synthetic Data
Synthetic data used to be a fairly narrow idea: pad a small dataset, test a model without touching production data, maybe stress a system for bias. The rise of generative AI and autonomous agents has changed the landscape. Teams use synthetic data to train and evaluate agentic systems, to cover rare failure cases, to meetContinue reading “The Industrialization of Synthetic Data”