331–340 of 574 posts
I'm sure I'd still be able to do it, but was saddened that I didn't get it as quickly as I think I used to be able to. Atrophy might already be in play.
I'm looking forward to having the same experience as COBOL engineers did after retirement: companies backing up the brinks truck to anyone with the skills to keep the lights on.
that would be nice, but unfortunately I think the supply vs demand situation is quite different this time
Sure there might be a dozen individuals making over $300k but most COBOL devs live in the deep south making less than $100k for their entire careers. Fine salary, but that line of work is severely limited and the salaries do not reflect how valuable that work is.
100% We're already seeing this at the enterprise level. Companies have dictates from leadership that "if you're writing code manually, you're doing it wrong." Okay, that kind of works for a while. We are indeed producing a shit-ton of code, but the reality is that engineers are pumping out code faster than the humans can understand and (honestly) review it. That sounds great until you realize that "hey Claude, read t…
We have a product guy on the team who was in a deeply not technical role before AI who is trying to do the “hey Claude, read this Jira ticket, implement” thing. It doesn’t work for the vast majority of tickets he attempts because he doesn’t have the necessary understanding to even start thinking about if the solution that the autocomplete generates is even remotely workable. And that’s with fancy dev loops and whatno…
Remove the dev from the equation. Suppose you need to produce circumstances for the slop machine to succeed on its own (imagine a loop).
What is missing? A good enough description of the current behavior, desired changes and how it should work? Understanding of the business domain or the system in question, its architectural choices? Enough guardrails and linters and tests to ensure that the solution will indeed be testable and work end to end? Cause a lot of the things that will help human devs will also help LLMs make their output more workable - for example ADRs in the repo and custom in-house tools to ensure they follow architectural conventions and practices (or just something like ArchUnit). Realistically, how close to a finished implementation must you get and how far backwards from that can you go before its output degrades too much?
I tried figuring that out myself on a personal project where I mostly want what I want in GitHub issues and then feed them to Kepler, which spawns OpenCode in worktrees and also gives me a UI to follow the execution. Most models, even SOTA, occasionally implement things wrong, but it's suprising how far you can take things when you've spent a dozen hours planning out what you want the end result to be vs not to be (talking about the goals for an entire system, maybe an hour of planning for a more bounded type of task).
100% We're already seeing this at the enterprise level. Companies have dictates from leadership that "if you're writing code manually, you're doing it wrong." Okay, that kind of works for a while. We are indeed producing a shit-ton of code, but the reality is that engineers are pumping out code faster than the humans can understand and (honestly) review it. That sounds great until you realize that "hey Claude, read t…
> the reality is that engineers are pumping out code faster than the humans can understand and (honestly) review it The word "engineering" means doing things using a repeatable process to get predictable results. If you can get predictable results (e.g. guaranteeing the absence of data integrity issues, security issues, anything that will cause downtime, etc.) without looking at the code, you're still doing the work…
Perfect example of begging the question.
Vibe coding works great as long as vibe coding works great.
Personally, I'd love to see how you enforce security and long-term maintainability without looking at the code cuz we need to add that to our build pipelines ASAP.
Earlier quoted context omitted.
> That sounds great until you realize that "hey Claude, read this Jira ticket and implement the feature in this code base" isn't really worth $200K/year. When you factor in overhead and benefits, many companies were regularly paying that much for someone (many someones) to "read this Jira ticket and implement the feature". We are currently in the "centaur" phase where a human-AI combination produces the best output,…
We've gone through this with chess, and the days when a human can do anything to help AI there are long past; the human can only drag it down. It seems to me to be a form of the bitter lesson. I expect this will happen in every field where we don't add guardrails to require humans in the network. I have a hard time seeing regulation happening around this in the US but vanity may also serve, will CEOs be satisfied rul…
Chess is a perfect information game with objective, easily measurable outcomes.
Show me a software business that looks like that and I'll agree with your hypothesis.
Otherwise I don't believe your metaphor proves much of anything.
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Out of curiosity, I just tried this: write a comment about how to use ChatGPT to write a game like you're a barely literate reddit user, short answer, maximum incoherency and the result was a pretty good simulation. I tried less insulting prompts first, this did not produce a good simulation. Not perfect, gptzero.me still knew it was AI generated (tayo42 is human by the same measure), but if for some reason someone w…
Redditor is too easy. Conveying the errors typical in a Raise The Colours group on Facebook, that's the hard stuff.
I think that is a question we are all mulling about these years.
Our expertise has been packaged into a 200$ product and the competition has become ourselves.
While I have been feeling better for quite some time, I feel another starting to brew. While I was never one of the fabled 10x or rockstar developers, I still derived a lot of enjoyment and and sense of purpose from my work.
With the utility of LLMs becoming more ubiquitous by the day, what purpose can I provide anymore? I struggled greatly to get where I am today, and while it might not be impressive to any of my fellow programmers, I am still proud to be a programmer.
I obtained a degree in CS because I found the entire field to be fascinating. I had great passion for learning many of the subjects. What I learned in my degree changed my life forever. I seriously went from one of the, "What's the point in learning most math if you never use it?" to being absolutely infatuated with the subject. (I'm still bad at math, but that does not detract from my pleasure).
With the utmost certainty, I did not push through all my struggles just to prompt LLMs all day. Maybe's its my insecurities manifesting, but I want people to say, "You did a great job" and not "Claude did a great job." I understand the Buddhist were likely correct. My suffering really does come from my attachment, but at the same time, I do not want to let it go.
I have no opposition to using LLMs as tools. I think a fine balance can be achieved. LLMs can even be exceptional learning tools when used appropriately.
If programming is just a means to an end to you, then you will receive no ill judgements from me. We all have different motives in life. But programming has always meant something more to me.
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A deterministic LLM is possible. Would you trust it?
I mean in the traditional software sense. We trust autopilots to fly planes. Would you get on a plane flown by an LLM?
:)
Even their fans agree, LLMs are inherently unreliable. The fact some people trust them regardless is due to a deep flaw in human psychology that I believe has not been significantly exploited by any previous tech. There will be tears.