Nearly halfway into 2026, enterprises are beginning to see tangible returns on their AI investments. Yet many are discovering that scaling requires something far less glamorous than flashy frontier models and state-of-the-art benchmarking: Clean, interoperable, governed data.

According to a new AI Momentum Survey from Dun & Bradstreet, 97% of organizations report active AI initiatives, but just 5% say their data is ready to support them. — Read More

Last month Salesforce announced it would open its APIs and launch a headless product, essentially betting that in an agentic world, its value lies in the data layer, not the UI. It’s a smart repositioning. (Although it’s worth noting that not much appears to have changed technically: the APIs Salesforce is now marketing as a “headless product” have largely existed for years. In other words it was a classic Salesforce marketing launch.) The idea behind the new product is that agents can access the data from the system of record without needing to interact with the UI, which is designed for humans to track workflows.

The announcement is a useful prompt for a more interesting question: if you strip away the UI and expose the database, what are you actually left with? How is that different from a Postgres database, a well-designed schema, and an API? Do the classic factors that make systems of record durable persist, or is there a new set of criteria? In the SaaS era, the system of record was defensible because humans lived in the interface. In the agentic era, that advantage weakens. The defensible layers shift downward into data models, permissions, workflow logic, and compliance, and upward into networks, proprietary data generation, and real-world execution.

When software goes headless, where does defensibility move? — Read More

AI is changing the way engineering teams complete work and measure productivity, with more time spent on reviewing code, fixing bugs and context switching between tools. When AI generates an organization’s code, output metrics improve, cycle times shorten and developers report feeling more productive for moving through work more quickly.

But 81% of engineering leaders said much of the time saved on coding is now spent reviewing AI’s work. Nearly a third of a developer’s day is spent on this invisible work that doesn’t appear in productivity metrics such as output, the report found.

“It is not the work organizations are trying to accelerate; it is the overhead attached to the work. — Read More

…If you’re a senior developer, and if you’ve played with the agents and skills and models and all the other things that are blowing people’s minds, and if your intuition is still telling you something is off in how people are proclaiming your job obsolete, then here, in this post, I’m going to try and put words to your intuition (as a good copywriter does).

But wait a minute! Many seasoned and famous developers are also proclaiming the death of the developer.

How’s that? Whose intuition is right? And what’s causing this split? — Read More

Meta engineers reportedly had an internal leaderboard called Claudeonomics. It is available to all 85,000 employees, and 60 trillion “AI tokens” have been burned in 30 days. The company even created digital badges like “Token Legend” and “Cache Wizard.” Some employees are reportedly leaving agents running overnight to climb the rankings.

On a recent podcast, Jensen Huang said something that sounds wild but is far more plausible if you extrapolate current trends out: if a $500,000 engineer isn’t burning at least $250,000 in tokens a year, he’d be “deeply alarmed.”

At the same time, economists are calling it a paradox. — Read More

April was a strange month for anyone who’s been tracking AI pricing. I keep a running file of the meaningful packaging and pricing moves from the major labs. By the third week of April my notes for the month had outgrown the page and started spilling into a separate document. Five major announcements, three of the four biggest providers, all in three weeks, all pointing in roughly the same direction.

… Five panicked moves in three weeks, from three of the four biggest commercial AI providers in the world, with one common thread:

The original design of their subscription plans is being challenged by evolving product capabilities and usage patterns. — Read More

#strategy

…[Gabriel Petersson] is a researcher at OpenAI, working on the Sora team — the people building the AI video models that are currently blowing everyone’s minds.

He didn’t get there because he had the right connections or a shiny Ivy League diploma.

He got there because he realized something early on that most of us take decades to figure out: School was just a side quest. Yes you heard right, he took school as a side quest. —  Read More

For years, “Dead Internet Theory” was framed as something done to us. Foreign bot armies. State-sponsored troll farms. Algorithmic propaganda flooding social media from the outside. A clean external villain you could point at, sanction, and try to take down.

That’s not really what’s happening. The platforms are doing it to themselves. Sometimes through outright bad-faith decisions. More often, through the kind of strategic confusion that looks identical to bad-faith from the outside.

In the last two years, four of the most human-feeling corners of the web (Pinterest, Reddit, Steam, Discord) have each made a series of decisions that are gutting the very thing that made them work. Some of those decisions are pure villainy. A lot of them, honestly, are just woefully bad judgment dressed up as strategy. The result is the same either way.

This isn’t really a “the internet is dying” piece. I genuinely don’t know what the internet looks like in five years. I’m pretty sure it’ll be very different from what we have today. But the mechanism is now visible enough that it’s worth writing down, because once you see the pattern, you can’t unsee it on whichever platform you open next. — Read More

If you’re looking for evidence of AI’s unrelenting pace, here it is: In January, Dan wrote that whoever wins vibe coding wins how you work on your computer—and that OpenAI had some serious catching up to do.

Three months and the release of OpenAI’s latest model later, Codex is there, and in a new episode of AI & I, Dan and Austin get into why they do much of their knowledge work in Codex now. They cite the power of GPT-5.5, paired with a desktop app that is faster and more powerful than Claude Desktop or Cowork. — Read More

2026 is the year CEOs must rewire the C-suite—redesigning how decisions are made, how authority is distributed, and how AI reshapes influence—while preserving the decisiveness and clarity enterprises need to move fast. Getting there takes proactive leadership. CEOs will need to work with their C-suite leaders to build execution mechanisms, incentives, and operating models all focused on driving these outcomes.

Our research shows that CEOs who have the greatest success with AI are actively rethinking cross-functional collaboration and embedding AI across end-to-end workflows. They’re building organizations designed to thrive in uncertainty, where productive debate sharpens strategy and smart risk-taking is rewarded.

The 2026 CEO Study’s data, gathered in partnership with Oxford Economics, builds on our study, The enterprise in 2030, which identifies five predictions for the future of the organization. This study’s analysis, informed by our 2030 predictions, reveals five plays that CEOs must make to lead in an AI-first landscape. — Read More