Pre-prepared demos don't impress me.

And not all the "fix this - i fixed - no you didn't - here's the fix — there's no fix" back and forth with the AI?

There's very little grandstanding in the comments. They are all very tame, all things considered.

“Anyone opensourcing anything while in the course of ‘commercial activity’ will be fully liable. Effectively they rugpulled the Apache2 / MIT licenses... all opensource released by small businesses is fucked. where the was no red tape now there is infinite liability”

This is my current understanding, from a friend not a lawyer. Would appreciate any insight from folks here.

Yeah, just the usual hn FUD about the EU.

I got rate-limited in like 5 seconds. Wow

Google launched Jules two days ago, which is the gemini coding agent[1]. I was pretty quickly accepted into the beta and you get 5 free tasks a day.

So far I have found it pretty powerful, its also the first time an LLM has ever stopped while working to ask me a question or for clarification.

[1]https://jules.google/

1P = Anthropic's first party API, e.g. not through Bedrock or Vertex

Not if you work there

Absolutely, this should be exactly the kind of task a bot should be perfect for. There's no abstraction, no design work, no refactoring, no consideration of stakeholders, just finding instances of whatever is old and busted and changing it for the new hotness.

Theoretically we don't even need AI. If semantics were defined well enough and maintainers actually concerned about and properly tracking breaking changes we could have tools that automatically upgrade our code. Just a bunch of simple scripts that perform text transformations.

The problem is purely social. There are language ecosystems where great care is taken to not break stuff and where you can let your project rot for a decade or two and still come back to and it will perfectly compile with the newest release. And then there is the JS world where people introduce churn just for the sake of their ego.

Maintaining a project is orders of magnitudes more complex than creating a new green field project. It takes a lot of discipline. There is just a lot, a lot of context to keep in mind that really challenges even the human brain. That is why we see so many useless rewrites of existing software. It is easier, more exciting and most importantly something to brag about on your CV.

Ai will only cause more churn because it makes it easier to create more churn. Ultimately leaving humans with more maintenance work and less fun time.

Except that for breaking changes you frequently need to know why it was done the old way in order to know what behavior it ago have after the update.

That assumes accurate documentation, upgrade guides that cover every edge case, and the miracle of package updates not causing a cascade of unforeseen compatibility issues.

So it works in controlled and predictable circumstances. That doesn't mean it works in unknown circumstances.

> Maybe that's the problem that needs solving then? The threshold doesn't have to be "bot capable of doing entire task end to end", like it could also be "bot does 90% of task, the worst and most boring part, human steps in at the end to help with the one bit that is more tricky".

Still, the big short-term danger being you're left with code that seems to work well but has subtle bugs in it, and the long-term danger is that you're left with a codebase you're not familiar with.

I can just imagine it now, you launch your AI coded first product and get a bug in production, and the only way the AI can fix the bug is to re-write and deploy the app with a different library. Your then proceed to show the changelog to the CCB for approval including explaining the fix to the client trying to explain its risk profile for their signoff.

"Yeh, we solved the duplicate name appearing the table issue by moving databases engines and UI frameworks to ones more suited to the task"