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The Future of AI Software Development

martinfowler.com

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Re: The Future of AI Software Development

#41

Post by crystal_revenge »

embedding-shape wrote: post #19
chadash wrote: post #11

> 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…

> a near-frontier model Is Kimi K2 near-frontier though? At least when run in an agent harness, and for general coding questions, it seems pretty far from it. I know what the benchmarks say, they always say it's great and close to frontier models, but is this other's impression in practice? Maybe my prompting style works best with GPT-type models, but I'm just not seeing that for the type of engineering work I do, wh…

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 wouldn’t surprise me if in two more years we continue to see more powerful open models on even cheaper hardware.

Re: The Future of AI Software Development

#42

Post by greymalik »

The headline misrepresents the source. It’s not the title of the page, not the point of the content, and biases the quote’s context: “ if traditional software delivery best practices aren’t already in place, this velocity multiplier becomes a debt accelerator”

Re: The Future of AI Software Development

#44

Post by charcircuit »

newsoftheday wrote: post #29
chadash wrote: post #11

> 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…

> a cost that a (somewhat wealthy) hobbyist can afford $20,000 is a lot to drop on a hobby. We're probably talking less than 10%, maybe less than 5% of all hobbyists could afford that.

You can rent computer from someone else to majorly reduce the spend. If you just pay for tokens it will be cheaper than buying the entire computer outright.

Re: The Future of AI Software Development

#45

Post by rawgabbit »

petcat wrote: post #24
simonw wrote: post #9

> 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…

From https://annievella.com/posts/finding-comfort-in-the-uncertai...

“Ideas that surfaced: code as ‘just another projection’ of intended behaviour. Tests as an alternative projection. Domain models as the thing that endures. One group posed the provocative question: what would have to be true for us to ‘check English into the repository’ instead of code?

The implications are significant. If code is disposable and regenerable, then what we review, what we version-control, and what we protect all need rethinking.”

Re: The Future of AI Software Development

#46

Post by manwe150 »

chadash wrote: post #11

> 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

Re: The Future of AI Software Development

#47

Post by mikkupikku »

neebz wrote: post #23
simonw wrote: post #9

> 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…

I've faced the same but my conclusion is the opposite. In the past 6 months, all my code has been written by claude code and gemini cli. I have written code backend, frontend, infrastructure and iOS. Considering my career trajectory all of this was impossible a couple of years ago. But the technical debt has been enormous. And I'll be honest, my understanding of these technologies hasn't been 'expert' level. I'm 100%…

Similar experience for me. I've been using it to make Qt GUIs, something I always avoided in the past because it seemed like a whole lot of stuff to learn when I could just make a TUI or use Tkinter if I really needed a GUI for some reason.

Claude Code is producing working useful GUIs for me using Qt via pyside6. They work well but I have no doubt that a dev with real experience with Qt would shudder. Nonetheless, because it does work, I am content to accept that this code isn't meant to be maintained by people so I don't really care if it's ugly.

Re: The Future of AI Software Development

#48

Post by louiereederson »

anthonypasq wrote: post #18

What is up with all this nonsense about token subsidies? Dario in his recent interview with Dwarkesh made it abundantly clear that they have substantial inference margins, and they use that to justify the financing for the next training run. Chinese open source models are dirt cheap, you can buy $20 worth of kimi-k2.5 on opencode and spam it all week and barely make a dent. Assuming we never got bigger models, but ha…

Anthropic reduced their gross margin forecast per external reporting (below) to 40%, and have exceeded internal forecasts on inference costs. This does not take into account amortized training costs which are substantial (well over 50% of revenue) and accounted for as occurring below gross profit. If you view training as a cost of staying in the game, then it is justifiable to view it as at least a partially variable cost that should be accounted for in gross margin, particularly given that the models stay on leading edge for only a few months. If that's the case then gross margins are probably minimal, maybe or negative.

https://www.theinformation.com/articles/anthropic-lowers-pro...

Re: The Future of AI Software Development

#49

Post by softwaredoug »

petcat wrote: post #24
simonw wrote: post #9

> 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…

I’d say the jury might be out on whether code is worthless for giant pieces of infrastructure (Linux kernel). There, small problems create outsized issues for everybody, so the incentive is to be conservative and focused on quality.

Second there’s a world of difference still between a developer with taste using AI with care and the slop cannons out there churning out garbage for others to suffer through. I’m betting there is value in the former in the long run.

Re: The Future of AI Software Development

#50

Post by nthypes »

greymalik wrote: post #42

The headline misrepresents the source. It’s not the title of the page, not the point of the content, and biases the quote’s context: “ if traditional software delivery best practices aren’t already in place, this velocity multiplier becomes a debt accelerator”

IMHO, it doesn't, but I have changed the title to avoid any confusion.
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