Linear Thinking, Nonlinear Costs
Many AI agent systems become economically unsustainable long before they become technically impressive. Teams usually focus on model choice, prompt de…
Programming
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Who Owns the Code Claude Wrote?
The following article originally appeared on Sena Evren’s Legal Layer newsletter and is being reposted here with the author’s permission. TL; DR Agent…
The Subsidy Ended: What Tool-Using Agents Actually Cost
On June 1, GitHub Copilot’s usage-based billing became active for all Copilot plans, and developers reacted quickly and loudly. A Pro plan still…
Predict, Don’t Enumerate
A third of the way into a security-operations guide that Anthropic published in April 2026, wedged between a recommendation to patch CISA’s Know…
Context as Code
As syntax becomes cheap and abundant, architectural control becomes the scarce resource. Effective governance starts upstream, where intent, constrain…
SaaS Is Not Dead Yet
With the rise of agents, many people have been proclaiming that the age of software as a service (SaaS) is over. Who needs to subscribe to a service w…
Agent Skills
The following article originally appeared on Addy Osmani’s blog and is being reposted here with the author’s permission. The default behavior of any A…
The Agentic P&L: Beyond the Empire of Headcount
For over a century, both the prestige and budget of a corporate department have been measured by a single crude metric: headcount. If you manage 500 p…
AI Artifact Catalogs: Durable Standards Worth Institutional Investment
Companies everywhere are trying to leverage AI to boost internal productivity metrics. Some, like Ramp and Intercom, are succeeding. Many are failing.…
Why Doesn’t Anyone Teach Developers About Context Management?
This is the sixth article in a series on agentic engineering and AI-driven development. Read part one here, part two here, part three here, part four …
Ryan Carson Is a One-Person Code Factory
Ryan Carson has built companies for 25 years, including Treehouse, which taught over a million people to code. He knows what it takes to grow a team. …
Burnout and Cognitive Debt
Steve Yegge’s article about programmer burnout (“The AI Vampire”) along with Margaret Storey’s article about Cognitive Debt started an ongoing convers…
Gyms for Them, Mirrors for Us
Personal AI doesn’t have to run your life to change it. It just must see you clearly and feed your behavior back to you in a way you can’t dodge. Once…
From Capabilities to Responsibilities
Human-in-the-Loop becomes an operational bottleneck In my previous article, ”The Missing Layer in Agentic AI,” I argued that AI agents need a determin…
Eating My Own Dog Food: How I Used the Framework to Write the Post About the Framework
In “Don’t Automate Your Moat,” I argue that engineering organizations should match AI autonomy to two independent dimensions: business risk and compet…
The Organization Is the Bottleneck
Everyone is adopting AI coding tools. Engineers are writing code faster than ever. But are organizations actually delivering value faster? That’s not …
Radar Trends to Watch: May 2026
The most significant tension in this issue is between two companies making different decisions about how to handle AI with frontier security capabilit…
Local AI
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 o…
Everyone’s an Engineer Now
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 …
AI Code Review Only Catches Half of Your Bugs
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 f…
Don’t Automate Your Moat: Matching AI Autonomy to Risk and Competitive Stakes
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 pr…
When Correct Systems Produce the Wrong Outcomes
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…
Show Your Work: The Case for Radical AI Transparency
A colleague told me something recently that I keep thinking about. She said, unprompted, that she appreciated seeing both sides of my AI conversations…
Emergency Pedagogical Design: How Programming Instructors Are Scrambling to Adapt to GenAI
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 proce…
Dark Factories: Rise of the Trycycle
The following article originally appeared on “Dan Shapiro’s blog” and is being reposted here with the author’s permission. Com…
AI Is Writing Our Code Faster Than We Can Verify It
This is the fourth article in a series on agentic engineering and AI-driven development. Read part one here, part two here, part three here, and look …
Grief and the Nonprofessional Programmer
I can’t claim to be a professional software developer—not by a long shot. I occasionally write some Python code to analyze spreadsheets, and I occasio…
From Capabilities to Responsibilities
Human-in-the-Loop becomes an operational bottleneck In my previous article, ”The Missing Layer in Agentic AI,” I argued that AI agents need a determin…
Eating My Own Dog Food: How I Used the Framework to Write the Post About the Framework
In “Don’t Automate Your Moat,” I argue that engineering organizations should match AI autonomy to two independent dimensions: business risk and compet…
Radar Trends to Watch: May 2026
The most significant tension in this issue is between two companies making different decisions about how to handle AI with frontier security capabilit…