My bet is that we'll see a second layer of harness emerge, as self-driving codebases become the target. There will be an application facing harness, orthogonal to the agent facing harness. The app harness will represent the software factory that is emergent for the specific application being developed.

Anyway, here's mine, still wip:

https://hale-lang.org/docs/dna/

https://github.com/hale-lang/hale/issues/690

This article hints at it, but I think the blocker is environment.

How can you self drive an app on windows? There's no clear UI framework, design pattern, nothing which can bullet proof your app.

I bet you'd have better luck on Plan 9.

Remove the choice. Make frameworks which have limited options which are usable by default.

    > It’s actually fine if agents make a lot of boneheaded mistakes. What’s not ok is if they keep making the same mistakes. 

I worked in life sciences for a bit. There is a process in clinical trials called corrective and preventative actions (CAPA). You'll also find this in other areas where failure tolerance is low (e.g. aircrafts).

It's simple: when a mistake happens, you run you CAPA process and determine the root cause and the correction to the process that allowed the mistake to happen in the first place. This is something most eng shops do not have the discipline for since it requires some diligence.

Should it be fully agentic? Should there be human intervention here to approve the CAPA? Open questions to be answered.

Author here, hello! Happy to expand on how we're thinking about this if any of it is unclear.

We wrote this post as part of a launch, which you can check out here: https://x.com/danlovesproofs/status/2095182189499711759

I suspect that if you're not careful with agent memory it creates a danger of agent-driven cargo-cult behavior. I've watched this in my own ad-hoc agent loops where it starts with something basic, like the first agent tried to run some gigantic dependency inspection command and OOMed the local JVM and eventually recorded a workaround (to enable it to run gigantic dependency inspection commands...), and by time I get a few more agents into the loop, agents have written entire paragraphs about testing and validating local dev environment memory configurations that are mostly irrelevant to whatever is being worked on.

In general I've seen other issues like this where small errors and irrelevant comments in the codebase spin out into larger problems that consume annoying amounts of time/tokens. Maybe Anthropic and OpenAI don't notice this because they're in an "infinite monkeys with typewriters" scenario, but it's noticeable to me when the agent in my CLI has been spinning for 15 minutes contemplating irrelevant details

[delayed]