How building software is changing at Anthropic

Much-improved AI tooling is changing how we build software, and I want to take a peek into how the future of software engineering may unfold under its influence. What better place for that than with tech’s most “AI-pilled” teams: the AI labs themselves.

So, I visited the two leading AI labs to see how teams and engineers do things day to day. In this article and in an upcoming follow-up, I’ll share what I learned about how AI is reshaping software engineering principles many of us are accustomed to – and what’s stayed mostly the same despite the AI wave.

In a later article, we’ll compare findings from Anthropic and OpenAI to see what their ways of working might mean for the overall direction of software engineering.

Thanks to Anthropic for showing me inside their lab in San Francisco. I talked with four people:

• Katelyn Lesse, head of engineering for Claude Platform, whose organization owns the infrastructure that Claude runs on

• Jarred Sumner, creator of Bun, now at Anthropic on Bun and Claude Code

• Thariq Shihipar, who works across Claude Code engineering and education

• David Hershey, at Anthropic’s Applied AI organization in a role resembling a sales engineer, working with customers like Cursor, Cognition, and Perplexity

Thanks to them, I got a sense of where things are headed at the leading AI lab – and possibly for the wider industry.

Before we continue, The Pragmatic Engineer will be on summer break for the next week and a half. This means no Thursday article this week, and no articles next week. I appreciate your understanding and support!

Back to today’s deepdive, we cover:

1. Complex & long: Claude Managed Agents. One of the most complicated projects took the Claude Platform team six months to ship, and created a new primitive to use at the agent infra level. Infra projects still need re-architecting mid-way through and take time to get right.

2. Twelve-month project done in 11 days: Bun rewrite to Rust. Migrating a 500K+ line project to another language used to take a small team a year, making it impractical. With Fable and $165K of tokens, it recently took the creator of the project less than two weeks.

3. Changing engineering practices. Inside the AI lab with more than 3,500 employees, prototyping is more fluid, verification is more time-consuming than implementation, code review and testing are increasingly done by AI.

4. Team-level changes. Design is more ongoing and less upfront, teams work on more projects, a maximum of two engineers per project, and more.

5. Still the same: two-pizza teams, planning is important, PRDs are relevant in complex projects, context switching is a challenge, the ratio of time spent on coding vs testing not changing that much.

6. Changing the “standout” software engineer archetype? Deep understanding, including of a layer below what you work on, is valuable, along with the ability to coordinate work.

7. Will AI replace software engineering? The more hands-on software engineers get with AI at the lab, the less they fear their jobs are going away.

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1. Complex & long: Claude Managed Agents

The Claude Platform team’s most complex project in the past year was building Claude Managed Agents, a pre-built harness for production agents that runs in the cloud on infrastructure managed by Anthropic, or on your team’s own infrastructure, with any sandbox you choose. The project took around six months from idea until launch in April. Katelyn Lesse, head of engineering for Claude Platform, shared the story.