Heading back to San Diego after spending today in a team offsite. It’s fun working on 2027 goals knowing we’ll completely change them again in three months.
[blog] TorchTPU is now open source: Run native PyTorch on TPUs. Big news for PyTorch users. Alongside CPUs and GPUs, TPUs are now a native option.
[blog] How the Claude Code team does code review. Yes, they still do code reviews. No, people aren’t very involved. But if you learn from the AI mistakes and codify fixes into the process, you end up with a very good system.
[blog] Speeding up code review with ‘small-change.’ Let’s stick with code reviews. This post explains a system that routes reviews for human review if needed, and which get very fast approval.
[blog] No more tech debt. Wasn’t this phrase in that John Lennon song “Imagine”? I’m misremembering. Now you can just rewrite versus handle all the quirks of an existing codebase.
[blog] Bringing the borderless Lakehouse into the agentic era with innovations for Gemini. What are the chances that ALL your data lives in a single place? Zero? Being able to (virtually) pull it together is about to be even more important than before.
[blog] How Software Trusts Software: MCP, A2A, & the Registries Agents Use. Protocols like MCP and A2A help AI agents find tools, but they only verify who published them, not whether they’re safe. Registries play an increasingly-important role.
[repo] secure-tdd-agent-framework. My colleague Aron has a repo with some excellent skills for a secure development process. Take a look.
[blog] Announcing llm-d 1.0: Open distributed inference for agents on Google Cloud TPUs and GPUs. This open serving stack for Kubernetes is now ready for prime time.
[article] Training Your Own Models is an Incredibly Stupid Idea. Probably right. You don’t need to bake your data into the weights to get value from AI.
[blog] Developing Taste. This doesn’t come quickly or easily. That’s ok. But surround yourself with the right people and ask the right questions.
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