Mercury: Ultra-fast language models based on diffusion

A good chance to bring up something I've been flagging to colleagues for a while now: with LLM agents we are very quickly going to become even more CPU bottlenecked on testing performance than today, and every team I know of today was bottlenecked on CI speed even before LLMs. There's no point having an agent that can write code 100x faster than a human if every change takes an hour to test.

Maybe I've just got unlucky in the past, but in most projects I worked on a lot of developer time was wasted on waiting for PRs to go green. Many runs end up bottlenecked on I/O or availability of workers, and so changes can sit in queues for hours, or they flake out and everything has to start again.

As they get better coding agents are going to be assigned simple tickets that they turn into green PRs, with the model reacting to test failures and fixing them as they go. This will make the CI bottleneck even worse.

It feels like there's a lot of low hanging fruit in most project's testing setups, but for some reason I've seen nearly no progress here for years. It feels like we kinda collectively got used to the idea that CI services are slow and expensive, then stopped trying to improve things. If anything CI got a lot slower over time as people tried to make builds fully hermetic (so no inter-run caching), and move them from on-prem dedicated hardware to expensive cloud VMs with slow IO, which haven't got much faster over time.

Mercury is crazy fast and in a few quick tests I did, created good and correct code. How will we make test execution keep up with it?

It’s because people don’t know how to write tests. All of the “don’t do N select queries in a for loop” comments made in PRs are completely ignored in tests.

Each test can output many db queries. And then you create multiple cases.

People don’t even know how to write code that just deals with N things at a time.

I am confident that tests run slowly because the code that is tested completely sucks and is not written for batch mode.

Ignoring batch mode, tests are most of the time written in a a way where test cases are run sequentially. Yet attempts to run them concurrently result in flaky tests, because the way you write them and the way you design interfaces does not allow concurrent execution at all.

Another comment, code done by the best AI model still sucks. Anything simple, like a music player with a library of 10000 songs is something it can’t do. First attempt will be horrible. No understanding of concurrent metadata parsing, lists showing 10000 songs at once in UI being slow etc.

So AI is just another excuse for people writing horrible code and horrible tests. If it’s so smart , try to speed up your CI with it.