Scott Shambaugh didn’t think twice when he denied an AI agent’s request to contribute to matplotlib, a software library that he helps manage. Like many open-source projects, matplotlib has been overwhelmed by a glut of AI code contributions, and so Shambaugh and his fellow maintainers have instituted a policy that all AI-written code must be…
The transformational potential of AI is already well established. Enterprise use cases are building momentum and organizations are transitioning from pilot projects to AI in production. Companies are no longer just talking about AI; they are redirecting budgets and resources to make it happen. Many are already experimenting with agentic AI, which promises new levels…
Many engineering challenges come down to the same headache — too many knobs to turn and too few chances to test them. Whether tuning a power grid or designing a safer vehicle, each evaluation can be costly, and there may be hundreds of variables that could matter. Consider car safety design. Engineers must integrate thousands…
For most of the history of software engineering, we’ve built systems around a simple and comforting assumption: Given the same input, a program will produce the same output. When something went wrong, it was usually because of a bug, a misconfiguration, or a dependency that wasn’t behaving as advertised. Our tools, testing strategies, and even…
The following article includes clips from a recent Live with Tim O’Reilly interview. You can watch the full version on the O’Reilly Media learning platform. Addy Osmani is one of my favorite people to talk with about the state of software engineering with AI. He spent 14 years leading Chrome’s developer experience team at Google,…
Think about what happens when you onboard a new employee. First, you provision them tools. Email access. Slack. CRM. Office software. Project management software. Development environment. Connecting a person to the system they’ll need to do their job. However, this is necessary but not sufficient. Nobody becomes effective just because they can log into Salesforce….
This post first appeared on Addy Osmani’s Elevate Substack newsletter and is being republished here with the author’s permission. TL;DR: Aim for a clear spec covering just enough nuance (this may include structure, style, testing, boundaries. . .) to guide the AI without overwhelming it. Break large tasks into smaller ones versus keeping everything in one large…
Agentic AI has clearly moved beyond buzzword status. McKinsey’s November 2025 survey shows that 62% of organizations are already experimenting with AI agents, and the top performers are pushing them into core workflows in the name of efficiency, growth, and innovation. However, this is also where things can get uncomfortable. Everyone in the field knows…
For most of the past decade, AI governance lived comfortably outside the systems it was meant to regulate. Policies were written. Reviews were conducted. Models were approved. Audits happened after the fact. As long as AI behaved like a tool—producing predictions or recommendations on demand—that separation mostly worked. That assumption is breaking down. As AI…
Most multi-agent AI systems fail expensively before they fail quietly. The pattern is familiar to anyone who’s debugged one: Agent A completes a subtask and moves on. Agent B, with no visibility into A’s work, reexecutes the same operation with slightly different parameters. Agent C receives inconsistent results from both and confabulates a reconciliation. The…