Every data leader has a version of this story. A regulatory audit surfaces a metric that doesn’t match across systems. A board member catches conflicting revenue numbers in two reports presented back-to-back. An AI tool generates a recommendation based on data that hasn’t been governed since the analyst who built it left the company two […]
In “Don’t Automate Your Moat,” I argue that engineering organizations should match AI autonomy to two independent dimensions: business risk and competitive differentiation. I used AI Gateway cost controls as a worked example throughout the piece because a single feature touches all four quadrants depending on which piece you’re building. A piece making that argument […]
Everyone is adopting AI coding tools. Engineers are writing code faster than ever. But are organizations actually delivering value faster? That’s not obvious. I wrote Enabling Microservice Success with a big focus on engineering enablement, guardrails, automated testing, active ownership, and light touch governance. I didn’t know AI coding agents were coming, but it turns […]
Every day, millions of pieces of fake content are produced. Videos, audio clips, posts, articles, generated by artificial intelligence, distributed at industrial scale, aimed at shifting public opinion across entire countries. The people producing them are often outside the country being targeted. The people receiving them almost never know they’re fake. And they have no […]
The release of Gemma 4 has added energy to the discussion of local models and their importance. Models that you can download and run on hardware you own are becoming competitive with the “frontier models” hosted by large AI providers. These models have gotten good enough for production use, good enough for tasks that until […]
Cat Wu leads product for Claude Code and Cowork at Anthropic, so she’s well-versed in building reliable, interpretable, and steerable AI systems. And since 90% of Anthropic’s code is now written by Claude Code, she’s also deeply familiar with fitting them into routine day-to-day work. Last month, Cat joined Addy Osmani at AI Codecon for […]
This is the fifth article in a series on agentic engineering and AI-driven development. Read part one here, part two here, part three here, and part four here. I recently had a taste of humility with my AI-generated code. I live in Park Slope, Brooklyn, and recently I needed to get to the other side of the neighborhood. […]
I was talking to a senior engineer at a well-funded company not long ago. I asked him to walk me through a critical algorithm at the heart of their product, something that ran hundreds of times a second and directly affected customer outcomes. He paused and said, “Honestly, I’m not totally sure how it works. […]
We tend to assume that if every part of a system behaves correctly, the system itself will behave correctly. That assumption is deeply embedded in how we design, test, and operate software. If a service returns valid responses, if dependencies are reachable, and if constraints are satisfied, then the system is considered healthy. Even in […]
A colleague told me something recently that I keep thinking about. She said, unprompted, that she appreciated seeing both sides of my AI conversations. Not just the output. The full thread. My prompts, the AI’s responses, the back and forth, the dead ends, the iterations. She said it made her trust me more. This piece […]
ChatGPT has been publicly available for over three years now, and generative AI is woven into the tools students use every day: web search, word processors, code editors. You might assume that by now, most programming instructors have figured out how to handle it. But when my collaborators and I went looking for computing instructors […]
Enterprise AI governance still authorizes agents as if they were stable software artifacts.They are not. An enterprise deploys a LangChain-based research agent to analyze market trends and draft internal briefs. During preproduction review, the system behaves within acceptable bounds: It routes queries to approved data sources, expresses uncertainty appropriately in ambiguous cases, and maintains source […]
The following article originally appeared on the Asimov’s Addendum Substack and is being republished here with the author’s permission. Are LLMs reliable? LLMs have built up a reputation for being unreliable. Small changes in the input can lead to massive changes in the output. The same prompt run twice can give different or contradictory answers. […]
The following article originally appeared on “Dan Shapiro’s blog” and is being reposted here with the author’s permission. Companies are now producing dark factories—engines that turn specs into shipping software. The implementations can be complex and sometimes involve Mad Max metaphors. But they don’t have to be like that. If you want a five-minute factory, […]
We all read it in the daily news. The New York Times reports that economists who once dismissed the AI job threat are now taking it seriously. In February, Jack Dorsey cut 40% of Block’s workforce, telling shareholders that “intelligence tools have changed what it means to build and run a company.” Block’s stock rose […]