Comment by entropicdrifter
2 days ago
I'm on the same page. Do people not analyze the problems themselves? Are they just copy/pasting their entire ticket description into Claude Code and having it iterate until they land on something that works?
I don't get it.
> Are they just copy/pasting their entire ticket description into Claude Code and having it iterate until they land on something that works?
That is exactly what they are doing, yes
That's my take as well. I've had my unPRed branches grabbed up and blindly merged by an agent twice now. The guy doing it was shocked both times that his PR had my change sets in it.
Also one engineer is treating the code as assembly. I've asked some pointed questions about code in his PR and the response was "yeah, I don't know that's what the agent did".
Edit:
To everyone freaking out about the second guy. Yeah, I think being unable to answer questions about the code you're PRing is ill advised. But requirement gathering, codebase untangling, and acceptance testing are all nontrivial tasks that surround code gen. I'm a bit surprised that having random change sets slurped up into someone else's rubber stamped PR isnt the thing that people are put off by.
My friend is a CTO at a non-tech company and he's now dealing with code from non-SWEs trying to self serve with LLMs.
But it's like a kid running a lemonade stand. Total DIY weekend project quality stuff that they are demanding go live. Hardcoded credentials, no concept of dev/qa/prod environments, no logging, no tests, no source control.
I'm not really sure teaching basic SWE practices / SDLC / system design to people whose day job is like.. accounting makes sense compared to just accelerating developer productivity.
4 replies →
So he's being paid and is sitting there letting an AI tool do his work for him? Insanity.
10 replies →
To that last guy, as the manager I would say "What is it that you do here??"
12 replies →
It's bizarre to me that people being paid to use their brains with a job title including the word "engineer", which essentially means "clever thought thinker" in Latin, just offloading all of their thinking to a bot instead of just using it as a way to ensure clean execution and faster understanding of the structures of underdocumented projects.
There's some people who are offloading all of their thinking to a bot, and I agree with you that I don't really understand this. But the good version of it is to offload some of your thinking to a bot so you can focus your own thinking on the parts that matter. My time is much better spent on "ah there is a scalability tradeoff here" than "I guess I have to initialize the FooBarProviderServiceProvider in a different spot so that I can pass a mock to the FooBarProvisionConsumer unit tests".
And why wouldn't they? Companies are quite literally instructing them to do so. I work at such a company and have heard similar anecdotes from colleagues that work at other companies.
Why wouldn't you do this even if not instructed to do so?
I can do so much more with my spare time now. I throw agents at problems and get way more done.
$1k in tokens every day is easy to hit.
1 reply →
To be fair, taking an average SWE at $160k/y, and spending $1k/m, and offloading mechanical ticket work from their working set sounds like a bargain to me. They could be spending the time on design and planning and working on new things, figuring out how to save costs in optimizations. In fact for every soul sucking mechanical task you offload, the better of you are overall.
It’s not like AI is the first time this happened. CI/CD and extensive preflight and integration and canary testing is also a way of saving engineer time and improving throughput at the cost of latency and compute resources. This is just moving up the semantic stack.
Obviously as engineers we say “awesome more features and products!” but management says “awesome fewer engineers!” either way pasting the ticket in and letting a machine do the work for a fraction of the cost was the right choice. There’s no John Henry award.
> pasting the ticket in and letting a machine do the work for a fraction of the cost was the right choice
If it were producing equivalent outcomes, sure. So far I haven't personally seeing strong evidence for that. LLMs do write code pretty competently at this point, but actually solving the correct problem, and without introducing unintended consequences, is a different matter entirely
2 replies →
> and offloading mechanical ticket work from their working set sounds like a bargain to me
Unfortunately the people who offload the work of understanding and interacting with tickets just end up offloading the consequences to everyone else who has to do extra work to make sure their LLM understands the task, review the work to make sure they built the right thing, and on and on.
The same thing happens when people start sending AI bots to attend meetings: The person freed up their own time, but now everyone else has to work hard to make sure their AI bot gets the right message to them and follow up to make sure what was supposed to happen in the meeting gets to them.
2 replies →
[dead]
That'd be crazy. The agent has a skill configured to fetch ticket descriptions from Jira by itself. Copy-pasting feels like manual labor.
Not what I do. I'll reformulate the ticket description so that the purpose and as many details as possible about the solution are made clear from the start. Then I tell Opus to go and research the relevant parts of the codebase and what needs to be done, and write its findings to a research.md file. Then I'll review that file, bring answers to any open questions and hash out more details if any parts seem fuzzy. When the research is sound I'll ask Opus to produce a plan.md document that lists all the changes that need to be made as actionable steps (possibly broken into phases). Then I'll let Sonnet execute the steps one by one and quickly review the changes as we go along.
You are making it too hard on yourself. Most people would just paste the ticket URL and type "fix this", then spend the next 3 hours on social media.
OTOH, I try hard to provide all possibly relevant context, manually copy/paste logs to reduce context overhead, always ask to produce an implementation plan and review it before making any code changes. Yet I often feel like a dinosaur here, all coworkers who tout "LLM productivity" just type a few words in and let the agent spin for hours without any guidance.
I'd call that irresponsible use. One of the principles I try to stick by is to never offload any major decisionmaking to the LLM without oversight. Because some percentage of the decisions it makes are going to be wrongful (and more often just against my taste).
> Are they just copy/pasting their entire ticket description into Claude Code and having it iterate until they land on something that works?
"Their ticket" = that was AI generated. After which they will wait their AI generated PR be checked by an automated AI QA that will validate against the AI generated spec.
It feels like important metric of "corporate AI adoption" should be how effective the human in steering the AI.
IF THE HUMAN ISN'T EFFECTIVE, THE HUMAN NEEDS TO GO.
You should.
If it manages to solve the working solutions - then it's great! why would you waste your time on it?
It it fails - then it's great! you find your value by solving the ticket, which can be a great example where human can still prevail to the AI (joke: AI companies might be interested to buy such examples)
(All assuming that your time cost is pricier than token spending. Totally different story if your wage is less than token cost)
Actually no. We ask business analysts to supply documentation for whole products. We use AI to analyze that documentation and after that we use AI to create tasks in Jira. Business analysts will review them.
After that we use AI to translate the tasks to a more technical view.
After that we use AI to implement the tasks.
After that we use AI to review the tasks.
After that a human QA tests the tasks.
If all is good, the code is merged and lands in production.
And yes, we burn a lot of tokens but the process is very fast. It takes months instead of years.
> Are they just copy/pasting their entire ticket description into Claude Code and having it iterate until they land on something that works?
There's also the pattern of creating an army of agents to solve problems. Human write a plan. One agent elaborates on it. Another reviews it and makes changes. Another splits it up into tasks and delegates out to multiple agents who make changes. Yet another agent reviews the changes, and on and on. All working around the clock.