Some tools take more effort to hold properly than others. I'm not saying there's not a lot of room for improvement - or that the ux couldn't hold the users hand more to force things like this in some "assisted mode" but at the end of the day, it's a thin, useful wrapper around an llm, and llms require effort to use effectively.
I definitely get value out of it- more than any other tool like it that I've tried.
Think about what you would do in an unfamiliar project with no context and the ticket
"please fix the authorization bug in /api/users/:id".
You'd start by grepping the code base and trying to understand it.
Compare that to, "fix the permission in src/controllers/users.ts in the function `getById`. We need to check the user in the JWT is the same user that is being requested"
On a shorter timeline than you'd think none of working with these tools will look like this.
You'll be prompting and evaluating and iterating entirely finished pieces of software and be able to see multiple attempts at each solve at once, none of this deep in the weeds fixing a bug stuff.
We're rapidly approaching a world where a lot of software will be being made without an engineer hire at all, maybe not the hardest most complex or novel software but a lot of software that previously required a team of 3-15 wont have a single dev.
> So, AIs are overeager junior developers at best, and not the magical programmer replacements they are advertised as.
This may be a quick quip or a rant. But the things we say have a way of reinforcing how we think. So I suggest refining until what we say cuts to the core of the matter. The claim above is a false dichotomy. Let's put aside advertisements and hype. Trying to map between AI capabilities and human ones is complicated. There is high quality writing on this to be found. I recommend reading literature reviews on evals.
The grandparent is talking about how to control cost by focusing the tool. My response was to a comment about how that takes too much thinking.
If you give a junior an overly broad prompt, they are going to have to do a ton of searching and reading to find out what they need to do. If you give them specific instructions, including files, they are more likely to get it right.
I never said they were replacements. At best, they're tools that are incredibly effective when used on the correct type of problem with the right type of prompt.
I have been quite skeptical of using AI tools and my experiences using them have been frustrating for developing software but power tools usually come with a learning curve while "good product" with clean simplified interface often results in reduced capability.
VIM, Emacs and Excel are obvious power tools which may require you to think but often produce unrivalled productivity for power users
So I don't think the verdict that the product has a bad UI is fair. Natural language interfaces is such a step up from old school APIs with countless flags and parameters
Mh. Like, I'm deeply impressed what these AI assistants can do by now. But, the list in the parent comment there is very similar to my mental check-list of pair-programming / pair-admin'ing with less experienced people.
I guess "context length" in AIs is what I intuitively tracked with people already. It can be a struggle to connect the Zabbix alert, the ticket and the situation on the system already, even if you don't track down all the zabbix code and scripts. And then we throw in Ansible configuring the thing, and then the business requriements by more, or less controlled dev-teams. And then you realize dev is controlled by impossible sales-terms.
These are scope -- or I guess context -- expansions that cause people to struggle.
I definitely get value out of it- more than any other tool like it that I've tried.