[suls]

The bigger question for me is how to use this efficiently as a team of engineers. Most workflow tools i've seen so far focus on making a single engineer get more out of a claude/codex subscription but not much how teams as a whole can become more productive.

Any ideas?

[jillesvangurp]

My hunch is to experiment not as a team but individually. With teams you want a bit more stability in terms of workflows. A lot of this stuff involves people handcrafting workflows on top of tools and models that are dramatically changing nearly constantly. That kind of chaos is not something you want at the team level.

I'm mostly sticking to a codex workflow. I transitioned from the cli to their app when they released it a few weeks ago and I'm pretty happy with that. I've had to order extra tokens a few times but most weeks I get by on the 20$ Chat GPT Plus subscription. That's not really compatible with burning hundreds/thousands on using lots of parallel agents in any case.

I also have a hunch that there are some fast diminishing returns on that kind of spending. At least, I seem to get a lot of value out of just spending 20/month. A lot of that more extreme burn might just be tool churn / inefficiency.

With teams, basically you should organize around CI/CD, pull requests and having code reviews (with or without AI assists). Standard stuff; you should be doing that anyway. But doubling down on making this process fast and efficient pays off. With LLMs the addition to this would be codifying/documenting key skills in your repositories for doing stuff with your code base and ways of working. A key thing in teams is to own and iterate on that stuff and not let it just rot. PRs against that should be well reviewed and coordinated and not just sneaked in.

Otherwise, AI usage just increases the volume of PRs and changes. Most of these tools in any case work a lot better if you have a good harness around your workflow that allows it to run linting/tests, etc. If you have good CI, this shouldn't be hard to express in skill form. The issue then becomes making sure the team gets good at producing high quality PRs and processing them efficiently. If you are dealing with a lot of conflicts, PR scope creep, etc. that's probably not optimal.

A lot of stuff related to coordinating via issue trackers can also be done with agents. If you have gh cli set up, it can actually create, label, etc. or act on github issues. That opens the door to also using LLMs for broader product management. It's something I've been meaning to experiment with more. But for bigger teams that could be something to lean on more. LLMs filing lots of issues is only helpful if you have the means to stay on top of that. That requires workflows where a lot of issues are short lived (time to some kind of resolution). This is not something many teams are good at currently.

[wiseowise]

The bigger question for me is how much compensation is increased as we enter this insanity? (It’s a rhetoric question, answer is 0)

[samusiam]

IMO we should all be asking for a raise if our company is making more money. Proportionally, even.