| It's way easier. People don't need to read code anymore, nor will they have to care about building mental models about the system as this article suggests. The way to think about coding agents is that a good one should in theory literally replace the developer entirely. No, a whole organisation of developers. In theory a product owner should just be able to dictate how they want to product to function at a high level and the AI should take care of the rest in the same way a human programmer or team of programmers would have in the past. If there are conflicts in what's being requested, then the AI should be able to recognise that and ask for production direction. As always with every generation of AI people seem to way over index on the now. - "They're good for autocomplete, that's about it" - "They're good for quickly mocking up small functions, but they make a lot of mistakes" - "They're good for scaffolding some parts of the system if you're good at prompt engineering" - "They're good at writing most of the code, but humans will always need to do the last 10%" - "They can write all of the code, but humans will still need to architect the system" You are here. Perhaps this is where progress stops. I wouldn't bet on that however. AI is making programming an irrelevent field. |
| If my experience with RDBMS generalizes, I predict that this trend will result in companies hiring skilled developers to unfuck their codebases. Furthermore, I predict they will identify massive structural issues, propose huge lifts to redo it correctly, and will instead be told to do patchwork fixes to stop the bleeding. Now, I do think AI is (or will be) good enough to implement these patchwork fixes when given explicit instructions, but someone will need to figure it out for them. The problem is if you don’t understand the root cause, you’ll at best feed the LLM a list of symptoms, and it will dutifully fix them. “Our p99 on this endpoint is breaching” becomes “I’ve added an index for this query,” or “I’ve added a caching layer,” when the actual problem may well be that you’re storing huge blobs that bloat your working set, cause buffer pool churn, and saturate your NIC. Is the symptom solved? Yes. Is it scalable? No, you’ll next need to vertically scale the instance, which is more expensive, and has an upper bound. Eventually you’ll decide to shard, which adds complexity, when the actual solution would’ve eliminated all of those issues at once. |
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| ▲ | kypro a day ago | parent [-] | | > The problem is if you don’t understand the root cause, you’ll at best feed the LLM a list of symptoms Today maybe. When Cloudflare has an outage does the CEO need to know the root cause though? If he just assigns some engineers to investigate, fix and report back to him – what's the issue with that? Assuming you agree with my analogy, can you explain what it is that you feel an agent or group of agents assigned to an engineering tasks could not do that a human can? And if can't do it today, why do you believe it wouldn't able to do it in the future? Are we just disagreeing about timelines here or whether humans have some magical quality which algorithms and AI can never capture? I feel like it's reasonable to disagree on timelines. It's quite unreasonable to assume human coders are special. | | |
| ▲ | sgarland a day ago | parent [-] | | My personal belief is that the most effective leaders do in fact deeply understand the technical side of their business, yes. To be fair, I am biased, because I was previously a nuclear reactor operator on a USN fast attack submarine, and the Commanding Officer is absolutely expected to fully understand technical issues. I think that a lot of organizational and technical problems would be solved if companies took several notes from the Nuclear Navy’s playbook. FWIW, Google’s SRE program was heavily influenced by it. I of course don’t have a crystal ball, and can’t say with certainty that AI will never replace human intelligence and judgment. However, I don’t see a viable path forward where that occurs, and we all still have jobs. Why would I be kept around if a superhuman AI can do my job 1000x better and faster, and at a drastically cheaper price? Or, if I was kept around as a human QA agent, why would I be paid nearly what I am now? I don’t see humans allowing AI to replace them. UBI is a pipe dream that would be destroyed by rent-seeking behavior anyway, and there’s no way billionaires would go for an AI tax, so we’ll be at an impasse. | | |
| ▲ | kypro 13 hours ago | parent [-] | | > However, I don’t see a viable path forward where that occurs, and we all still have jobs. Why would I be kept around if a superhuman AI can do my job 1000x better and faster, and at a drastically cheaper price? Or, if I was kept around as a human QA agent, why would I be paid nearly what I am now? Well as an AI doomer I agree with this. In my view you will lose your job, along with everyone else, and we'll just need to hope that those in power will give us some cash to feed our families. Ultimately us regular folks won't have the collective bargaining power of our labour and could not revolt with nation-wide strikes, nor are we any physical threat for those with power anymore. But that's the good outcome. This assumes AI remains obedient to it's human owners and that bad actors don't have access and can't use it to create biological weapons and other civilisation-level threats. I know we're not there yet, but the history of AI is one of continuous step changes in capabilities with each algorithmic breakthrough. AIs today are far more knowledgable and much quicker than humans, but still missing a few bits that keep them from being broadly super human. One or two algorithmic breakthroughs is all it takes though. It was just two breakthroughs over the last 8 years that took us from not even having code-autocomplete to having reasoning models advanced enough to solve math problems which have stumped humans for decades. | | |
| ▲ | sgarland 12 hours ago | parent [-] | | > AIs today are far more knowledgable and much quicker than humans, but still missing a few bits that keep them from being broadly super human. Generally, yes, but it’s the non-determinism that gets me. Even easy stuff: I’m currently on a road trip, and asked Claude (Fable) to plan various routes, optimizing for scenery while also ensuring a maximum drive time each day, and ending every night in a town that has a decent hotel. Along the way, I’ve made various tweaks, like “we’d like to drive an extra hour or two today, so adjust the rest of the route so we don’t end up with a short intermediate day.” While in general it’s done quite well, it occasionally made errors on distance between stops, something that’s trivially queryable. It wasn’t off by a few miles, either, it was hundreds. Until they can get the confidently incorrect problem solved, I don’t see it being a viable replacement. Maybe if you have agents that are aggressively checking the main ones’ output, but that seems unnecessarily wasteful of resources to me. | | |
| ▲ | kypro 8 hours ago | parent [-] | | > Until they can get the confidently incorrect problem solved, I don’t see it being a viable replacement. Maybe if you have agents that are aggressively checking the main ones’ output, but that seems unnecessarily wasteful of resources to me. 2 years ago AI could even count the number of letters in a word or do basic maths. Now we're at the point where we can't trust it because makes occasional errors. Don't get me wrong, I agree with you. These are things that need to be solved first, I just don't have reason to believe these are particularly difficult problems. Anyway, I enjoyed the convo. Was interesting hearing your thoughts. I would give anything to be wrong. |
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