341–350 of 375 posts
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This is not the fantastic argument you think it is. 100% is only achievable if you have software engineers at the helm so there's no contradiction here.
If the AI is doing 100% of the work why would you need software engineers at the helm?
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"Learn AI tooling" What is there to learn, honestly? People act like it's learning to write a Linux driver. The maximum knowledge you need how to write a plan or text file. Maybe throw in a "Plz no mistakes" There's no specific model, a better one comes out every month, everything is stochastic.
>What is there to learn, honestly? With all due respect, that answer shows that you don't know enough about agentic coding to form an opinion on this. Things to learn: - What agent are you going to use? - What skills are you going to use? - What MCPs are you going to use? - What artifacts are you going to provide beyond the prompt? - How are you going to structure it so the tooling can succeed without human interacti…
A pretty basic Claude Code or Codex setup and being mindful of context handling goes a long way. Definitely long enough to be able to use AI productively while not spending much time on configuring the setup.
Staying on top of all details is not necessary but in fact counter productive, trust me.
> However, it is important to ask if you want to stop investing in your own skills because of a speculative prediction made by an AI researcher or tech CEO. Consider the case where you don’t grow your software engineering or problem-solving skills, yet the forecasts of AI coding agents being able to handle ever expanding complexity don’t come to pass. Where does this leave you? The current Claude Code setup with Opus…
Do you think your organisation as a whole is doing more ? Is the more being done actually useful ? i.e: is the outcome better ?
But personally: yes and to an immense degree. The excuse “we don’t have the time for this” has pretty much evaporated when it comes to me. I do more than colleagues do and have gotten enough automation working that the AI will be made to iterate and fix its code to my desires before I ever see a line of it. I’ve added tests to entire systems thanks to it, fixed bugs across the codebase, added a bunch of additional quality control scripts and tools, improved CI, built and shipped not only entire features but systems. I can now work on about 3 projects in parallel, even if it can be super tiring.
But hey, I’m also working more on side projects outside of work and nice utilities I never had time for. I don’t really build in public sadly, but it very much is a force multiplier and makes me hate my job less sometimes (everyone has a horrible brownfield codebase or two).
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>What is there to learn, honestly? With all due respect, that answer shows that you don't know enough about agentic coding to form an opinion on this. Things to learn: - What agent are you going to use? - What skills are you going to use? - What MCPs are you going to use? - What artifacts are you going to provide beyond the prompt? - How are you going to structure it so the tooling can succeed without human interacti…
I can bet that a single standard instance of existing tool like codex and Claude Code to do whatever someone with a convoluted setup like that can. It could be marginally slower if you but it's all literally just English language text files. I use codex almost everyday, none of that is necessary unless you're trying to flatten up your resume. It's micro services all over again, a concept useful for some very select o…
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Or just wait for things to settle. As fast as the field is moving, staying ahead of the game is probably high investment with little return, as the things you spend a ton of time honing today may be obsolete tomorrow, or simply built into existing products with much lower learning cost. Note, if staying on the bleeding edge is what excites you, by all means do. I'm just saying for people who don't feel that urge, the…
Interesting - what makes you think things will slow down?
The closest parallel I can think of is javascript frameworks. The 2010s had a new framework out every week. Lots of people (somewhat including myself) wasted a ton of time trying to keep up with the churn, imagining that constantly being on the bleeding edge was somehow important. The smart ones just picked something reasonably mature and stuck with it. Eventually things coalesced around React. All that time trying to keep up with the churn added essentially no value.
I think most of the issues with "vibe coding" is trusting the current level of LLM's with too much, as writing a hacky demo of a specific functionality is 1/10 as difficult as making a fully-fledged, dependable, scalable version of it. Back in 2020, GPT-3 could code functional HTML from a text description, however it's only around now that AI can one-shot functional websites. Likewise, AI can one-shot a functional de…
Of course - and autonomous driving is 1 year away.
That's the nature of all tech, it keeps not being good enough, until it is, and then everything changes.
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HN often bring up that quote pretty quickly whenever author of an article is perceived to be bias one way or another. I’m surprised it hasn’t been mentioned in the comments here.
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i agree, and its strange that this failure mode continually gets lumped onto AI. The whole point of longer term software engineering was to make it so that the context within a particular persons head should not impact the ability of a new employee to contribute to a codebase. turns out everything we do to make sure that is the case for a human also works for an agent. As far as i can tell, the only reason AI agents…
The failure mode is getting lumped into AI because AI is a lot more likely to fail. We've done this with Neural Networks v1, Expert Systems, Neural Networks v2, SVM, etc, etc. only a matter of time before we figured it out with deep neural networks. Clearly getting closer with every cycle, but no telling how many cycles we have left because there is no sound theoretical framework.