AI agents

Take · The biggest worry about letting coding agents run freely has always been what they can touch on your machine. I'd set the team default to: write only to the current repo, no access to Git credentials, network via an allowlist, with local MCP servers included. That beats reviewing every command after the fact, and teams on other coding agents should hold their isolation to the same bar.

Take · This is the same MXC that powers Copilot's local sandboxing above, so the isolation layer for running agents on your own machine now ships with the OS. With 128GB of unified memory holding a 100B-plus model, keeping private data on the device can be validated on a single machine, and products handling private files like my AI Cloud Drive could consider a local-inference edition. Don't rush the hardware purchase, though: first check whether a local model is good enough for your workload.

Take · Single-attempt pass rates flatter agents. I'm applying the same idea to scoring in my AI Interview product: run the same answer sheet several times and check that what lands in the database agrees, not what the model says. When picking a model, put all-20-pass rate and cost per dependable task in your eval sheet; it tells you more than a leaderboard.