There's no way I'd call what I do "radically different from what most people do" myself, under any circumstances. Yet in my last cross-team discussions at work, I realized that a whole lot of people were using AI in ways I'd consider either silly or mostly ineffective. We had a team boasting "we used Amazon Q to increase our projects' unit test coverage", and a principal engineer talking about how he uses Cursor as some form of advanced auto complete.
So when I point claude code at a ticket, hand it readOnly access to a qa environment so it can see how the database actually looks like, chat about implementation details and then tell it to go implement the plan, running unit tests, functional tests, run linters and all, that, they look at me like I have three heads.
So if you ask me, explaining reasonably easy ways to get good outcomes out of Codex or Claude Code is still necessary evangelism, at least in companies that haven't spent on tools to do things like what Stripe does. There's still quite a few people out there copying and pasting from the chat window.
> We had a team boasting "we used Amazon Q to increase our projects' unit test coverage"
Well are the tests good or no? Did it help the work get done faster or more thoroughly than without?
> how he uses Cursor as some form of advanced auto complete
Is there something wrong with that? That's literally what an LLM is, why not use it directly for that purpose instead of using the wacky indirect "run autocomplete on a conversation and accompanying script of actions" thing. Not everyone wants to be an agent jockey.
I don't see what's necessarily silly or ineffective about what you described. Personally I don't find it particularly efficient to chat about and plan out all bunch of work with a robot for every task, often it's faster to just sketch out a design on a notepad and then go write code, maybe with advanced AI completion help to save keystrokes.
I agree that if you want the AI to do non-trivial amounts of work, you need to chat and plan out the work and establish a good context window. What I don't agree with is your implication that any other less-sophisticated use of AI is necessarily deficient.
So when I point claude code at a ticket, hand it readOnly access to a qa environment so it can see how the database actually looks like, chat about implementation details and then tell it to go implement the plan, running unit tests, functional tests, run linters and all, that, they look at me like I have three heads.
So if you ask me, explaining reasonably easy ways to get good outcomes out of Codex or Claude Code is still necessary evangelism, at least in companies that haven't spent on tools to do things like what Stripe does. There's still quite a few people out there copying and pasting from the chat window.