Taste in the Loop
A Note from the Editors
This week we've been thinking a lot about what the future of software engineering will look like, how to move faster, and how to wrangle AI slop. So this week's articles are centered around that. Enjoy!
— Josh, Donnie, and Ben
The Future of Software Engineering ↗
— Adam Bender
Adam Bender gave a great talk at Google I/O this year about the future of software engineering, “software ecology”, and all the things that will break due to AI agents “10x-ing” the throughput of our ability to write code. Definitely worth watching.
MiniMax M3 ↗
— MiniMax
MiniMax released M3, their newest LLM, yesterday (June 1st). MiniMax claims M3 benchmarks competitively with Opus 4.7 and GPT 5.5, will be open-weight soon, and comes at a fraction of the price of those other models — only $0.60 per million input tokens and $2.40 per million output tokens (when context is under 512k tokens). Historically, MiniMax’s M-series models have been really good (for their size), but don’t perform as well in practice as the benchmarks suggest (which is common for Chinese models). This one is worth trying out for your own use cases.
Building Pi With Pi ↗
— Armin Ronacher
A great post by Armin on the challenges of dealing with AI slop while using Pi (Earendil’s coding agent) to build Pi. This post also covers the challenges associated with running a large open source project at a time where a lot of the people submitting issues are submitting bad issues full of slop. This is important because wielding coding agents effectively requires writing good issues, which we’ve covered in the past.
Moving Faster ↗
— Jamie Brandon
Jamie has a very practical post on how to move faster. It’s an older post (from 2021), so it focuses on the things you can do as a human to move faster, rather than what you can do with AI coding agents. His discussion on the limits of human attention and the cost of multitasking is especially relevant today given the push for people to frantically alt-tab across multiple coding agent sessions.
Consequently, this is one of the reasons why background coding agents are so valuable; they take you out of the loop and allow you to focus your attention on the most important task at hand, rather than trying to spread your attention across N tasks concurrently.
Please Use AI ↗
— Shawn Smucker
LLMs are extremely powerful (and useful) tools, but they shouldn’t be used in ways that remove our own voice or deprive us of human social connection. Shawn writes a beautiful and heartfelt essay on the pitfalls of doing that.
There are a lot of coding agent harnesses out there: Claude, Codex, Cursor, Amp, Droid, Pi, OpenCode, etc. You’re #harness-curious, so you want to try them all. But it’s so painful because every harness has its own configuration format for slash commands, skills, etc.
Rulesync is a nice little open-source project that takes the pain away by keeping your configuration in sync across many of the most popular coding agent harnesses.
Join our community Slack and send us screenshots of your favorite clanker fails.