It's refreshing to hear people say "We're not really sure" in public, especially from experts.
I agree that AI tools are likely to amplify the importance of quick cycles and continuous delivery.
The Future of AI Software Development
71–80 of 156 posts
Re: The Future of AI Software Development
#72Earlier quoted context omitted.
20k for such a setup for a hobbyist? You can leave the somewhat away and go into sub 1% region globally. A kw of power is still 2k/year at least for me, not that I expect it will run continuously but still not negligible if you can do with 100-200 a year on cheap subscriptions.
There are plenty of normal people with hobbies that cost much more. Off the top of my head, recreational vehicles like racecars and motorcycles, but im sure there are others. You might be correct when you say the global 1%, but that's still 83 million people.
I used to think photography was an expensive hobby until my wife got back into the horse world.
Re: The Future of AI Software Development
#73> LLMs are eating specialty skills. There will be less use of specialist front-end and back-end developers as the LLM-driving skills become more important than the details of platform usage. Will this lead to a greater recognition of the role of Expert Generalists? Or will the ability of LLMs to write lots of code mean they code around the silos rather than eliminating them? This is one of the most interesting questi…
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Re: The Future of AI Software Development
#74In the section on security: > One large enterprise employee commented that they were deliberately slow with AI tech, keeping about a quarter behind the leading edge. “We’re not in the business of avoiding all risks, but we do need to manage them”. I’m unclear how this pattern helps with security vis-à-vis LLMs. It makes sense when talking about software versions, in hoping that any critical bugs are patched, but prom…
I took this to mean more like not jumping right on OpenClaw, but wait a quarter or so to give it at least a little time to shake out. There are so many new tools coming out I think it's beneficial not to be the guinea pig.
Re: The Future of AI Software Development
#75> LLMs are eating specialty skills. There will be less use of specialist front-end and back-end developers as the LLM-driving skills become more important than the details of platform usage. Will this lead to a greater recognition of the role of Expert Generalists? Or will the ability of LLMs to write lots of code mean they code around the silos rather than eliminating them? This is one of the most interesting questi…
Code is, I think, rapidly becoming a commodity. It used to be that the code itself was what was valuable (Microsoft MS-DOS vs. the IBM PC hardware). And it has stayed that way for a long time. FOSS meant that the cost of building on reusable components was nearly zero. Large public clouds meant the cost of running code was negligible. And now the model providers (Anthropic, Google, OpenAI) means that the cost of prod…
> What is still valuable is the intuition to know what to build, and when to build it. That's the je ne sais quoi still left in our profession.
Absolutely. Also crucial is what's possible to build. That takes a great deal of knowledge and experience, and is something that changes all the time.
Re: The Future of AI Software Development
#76Earlier quoted context omitted.
A lot of people aren’t realizing that it’s not about replacing software engineers, it’s about replacing software . We’ve been trying to build well engineered, robust, scalable systems because software had to be written to serve other users. But LLMs change that. I have a bunch of vibe coded command lines tools that exactly solve my problems, but very likely would make terrible software. The thing is, this program onl…
I absolutely believe in that value proposition - but I've heard a lot about how beneficial it will be for large organizationally backed software products. If it isn't valuable to that later scenario (which I have uncertainty about) then there is no way companies like OpenAI could ever justify their valuations.
> there is no way companies like OpenAI could ever justify their valuations
The value proposition isn't really "we'll help you write all the code for your company" it's a world where the average user's computer is a dumb terminal that opens up to a ChatGPT interface.
I didn't initially understand the value prop but have increasingly come to see it. The gamble is that LLMs will be your interface to everything the same way HTTP was for the last 20 years.
The mid-90s had a similar mix of deep skepticism and hype-driven madness (and if you read my comments you'll see I've historically been much closer to the skeptic side, despite a lot of experience in this space). But even in the 90s the hyped-up bubble riders didn't really see the idea that http would be how everything happens. We've literally hacked a document format and document serving protocol to build the entire global application infrastructure.
We saw a similar transformation with mobile devices where most of your world lives on a phone and the phone maker gets a nice piece of that revenue.
People thought Zuck was insane for his metaverse obsession, but what he was chasing was that next platform. He was wrong of course, but what his hope was was that VR would be the way people did everything.
Now this is what the LLM providers are really after. Claude/ChatGPT/Grok will be your world. You won't have to buy SaaS subscriptions for most things because you can just build it yourself. Why use Hubspot when you can just have AI do all your marketting, then you just need Hubspot for their message sending infrastructure. Why pay for a budgeting app when you can just build a custom one that lives on OpenAIs server (today your computer, but tomorrow theirs). Companies like banks will maintain interfaces to LLMs but you won't be doing your banking in their web app. Even social media will ultimately be replaced by an endless stream of bespoke images video and content made just for you (and of course it will be much easier to inject advertising into this space you don't even recognize as advertising).
The value prop is that these large, well funded, AI companies will just eat large chunks of industry.
Re: The Future of AI Software Development
#77> Will LLMs be cheaper than humans once the subsidies for tokens go away? At this point we have little visibility to what the true cost of tokens is now, let alone what it will be in a few years time. It could be so cheap that we don’t care how many tokens we send to LLMs, or it could be high enough that we have to be very careful. We do have some idea. Kimi K2 is a relatively high performing open source model. Peopl…
Horrific comparison point. LLM inference is way more expensive locally for single users than running batch inference at scale in a datacenter on actual GPUs/TPUs.
Re: The Future of AI Software Development
#78> Will LLMs be cheaper than humans once the subsidies for tokens go away? At this point we have little visibility to what the true cost of tokens is now, let alone what it will be in a few years time. It could be so cheap that we don’t care how many tokens we send to LLMs, or it could be high enough that we have to be very careful. We do have some idea. Kimi K2 is a relatively high performing open source model. Peopl…
Horrific comparison point. LLM inference is way more expensive locally for single users than running batch inference at scale in a datacenter on actual GPUs/TPUs.
How is that horrific? It sets an upper bound on the cost, which turns out to be not very high.
Re: The Future of AI Software Development
#79> Will LLMs be cheaper than humans once the subsidies for tokens go away? At this point we have little visibility to what the true cost of tokens is now, let alone what it will be in a few years time. It could be so cheap that we don’t care how many tokens we send to LLMs, or it could be high enough that we have to be very careful. We do have some idea. Kimi K2 is a relatively high performing open source model. Peopl…
Reminder to others that $20k is the one time startup cost, and is amortized perhaps 2-4k/year (plus power). That is in the realm of a mere gym membership around me for a family
So 5-10 years to amortize the cost. You could get 10 years of Claude Max and your $20k could stay in the bank in case the robots steal your job or you need to take an ambulance ride in the US.
Re: The Future of AI Software Development
#80Earlier quoted context omitted.
I’ve been running K2.5 (through the API) as my daily driver for coding through Kimi Code CLI and it’s been pretty much flawless. It’s also notably cheaper and I like the option that if my vibe coded side projects became more than side projects I could run everything in house. I’ve been pretty active in the open model space and 2 years ago you would have had to pay 20k to run models that were nowhere near as powerful.…
> it’s been pretty much flawless So above and beyond frontier models? Because they certainly aren't "flawless" yet, or we have very different understanding of that word.
I have increasingly changed my view on LLMs and what they're good for. I still strongly believe LLMs cannot replace software engineers (they can assist yes, but software engineering requires too much 'other' stuff that LLMs really can't do), but LLMs can replace the need for software.
During the day I am working on building systems that move lots of data around where context and understanding of the business problem is everything. I largely use LLMs for assistance. This is because I need the system to be robust, scalable, maintainable by other people and adaptable to large range of future needs. LLMs will never be flawless in a meaningful sense in this space (at least in my opinion).
When I'm using Kimi I'm using it for purely vibe coded projects where I don't look at the code (and if I do I consider this a sign I'm not thinking about the problem correctly). Are these programs robust, scalable, generalizable, adaptable to future use case? No, not at all. But they don't need to be, they need to serve a single user for exactly the purpose I have. There are tasks that used to take me hours that now run in the background while I'm at work.
In this latter sense I say "flawless" because 90% of my requests solve the problem on the first pass, and the 10% of the time where there is some error, it is resolved in a single request, and I don't have to ever look at the code. For me that "don't have to look at the code" is a big part of my definition of "flawless".