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”
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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”
AI agents just made your data pipeline obsolete
Subscribe • Previous Issues 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,Continue reading “AI agents just made your data pipeline obsolete”
The margin paradox threatening every AI company
Subscribe • Previous Issues The AI Bubble Is Real. Enterprise Usage Is Even More Telling. The existence of an AI bubble is beyond dispute. What remains unclear is when or how it deflates. As investors know all too well, the most costly mistake in business is often being correct prematurely. The infrastructure layer has already booked revenues.Continue reading “The margin paradox threatening every AI company”
Your agents need runbooks, not bigger context windows
Subscribe • Previous Issues Why Your AI Agents Need Operational Memory, Not Just Conversational Memory Now that AI agents are moving out of the lab and into the real world, we’re realizing that “memory” isn’t one-size-fits-all. Most people think of agent memory like a personal assistant. It remembers your preferences, your travel plans, and the email youContinue reading “Your agents need runbooks, not bigger context windows”
The “Data Center Rebellion” is here
Subscribe • Previous Issues Beyond the Chips: The Local Politics of AI Infrastructure Even the most ardent cheerleaders for artificial intelligence now quietly concede we are navigating a massive AI bubble. The numbers are stark: hyperscalers are deploying roughly $400 billion annually into data centers and specialized chips while AI-related revenue hovers around $20 billion — aContinue reading “The “Data Center Rebellion” is here”
The 6 security shifts AI teams can’t ignore in 2026
Subscribe • Previous Issues The AI-Native Security Playbook: Six Essential Shifts As we expand from AI-assisted tools to AI-native operations, the security landscape is undergoing a structural transformation. Those building, scaling, and investing in generative AI applications, are starting to see a shift from static models to autonomous agents with the authority to interact directly with enterpriseContinue reading “The 6 security shifts AI teams can’t ignore in 2026”
Your AI passed benchmarks. Why is it failing in production?
Subscribe • Previous Issues AI Reliability Patterns That Generalize Beyond Medicine The gap between pilot projects and production deployments has emerged as a defining challenge for enterprise AI teams. Recent surveys indicate that only a small percentage of generative AI initiatives reach full production, with most stalling due to brittle workflows and integration failures. At last year’sContinue reading “Your AI passed benchmarks. Why is it failing in production?”
Emerging AI patterns in finance (what to watch in 2026)
Subscribe • Previous Issues What’s Emerging in Financial AI: From Foundation Models to Compliance-as-Code While the public discourse remains fixated on Artificial General Intelligence, the more immediate and consequential story is the diffusion of AI into specialized enterprise domains. Having spent time as a quant within the hedge fund industry, I have long viewed financial services asContinue reading “Emerging AI patterns in finance (what to watch in 2026)”
Agent workflows: stop guessing, start measuring
Subscribe • Previous Issues Agent Optimization: From Prompt Whispering to Platform Engineering Agent optimization is the work of making an agent workflow dependable — despite long tool chains, multiple roles, and the inherent variability of large language models. In day-to-day engineering terms, it is closer to debugging a complex system than “making the model smarter”: you areContinue reading “Agent workflows: stop guessing, start measuring”