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The Future of AI Software Development

martinfowler.com

31–40 of 156 posts

Re: The Future of AI Software Development

#31
post #8
post #5

Earlier quoted context omitted.

> but prompt injection springs eternal. Yes, but some are mitigated when discoverd, and some more critical areas need to be isolated from the LLM so taking their time to provision LLM into their lifecycle is important, and they're happy to spend the time doing it right, rather than just throwing the latest edge tech into their system.

How exactly can you "mitigate" prompt injections? Given that the language space is for all intents and purposes infinite, and given that you can even circumvent these by putting your injections in hex or base64 or whatever? Like I just don't see how one can truly mitigate these when there are infinite ways of writing something in natural language, and that's before we consider the non-natural languages one can use to…

The only ways that I can think of to deal with prompt injection, are to severely limit what an agent can access.

* Never give an agent any input that is not trusted

* Never give an agent access to anything that would cause a security problem (read only access to any sensitive data/credentials, or write access to anything dangerous to write to)

* Never give an agent access to the internet (which is full of untrusted input, as well as places that sensitive data could be exfiltrated)

An LLM is effectively an unfixable confused deputy, so the only way to deal with it is effectively to lock it down so it can't read untrusted input and then do anything dangerous.

But it is really hard to do any of the things that folks find agents useful for, without relaxing those restrictions. For instance, most people let agents install packages or look at docs online, but any of those could be places for prompt injection. Many people allow it to run git and push and interact with their Git host, which allow for dangerous operations.

My current experimentation is running my coding agent in a container that only has access to the one source directory I'm working on, as well as the public internet. Still not great as the public internet access means that there's a huge surface area for prompt injection, though for the most part it's not doing anything other than installing packages from known registries where a malicious package would be just as harmful as a prompt injection.

Anyhow, there have been various people talking about how we need more sandboxes for agents, I'm sure there will be products around that, though it's a really hard problem to balance usability with security here.

Re: The Future of AI Software Development

#32
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…

[deleted]

Re: The Future of AI Software Development

#33

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…

[deleted]

Re: The Future of AI Software Development

#34
post #24
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…

yes, agreed that coding (implementation), which was once extremely expensive for businesses, is trending towards a negligible price. Planning, coordination, strategy at a high level are as challenging as ever. I'm getting more done than ever, but NOT working less hours in a day (as an employee at a product company).

Re: The Future of AI Software Development

#35
post #4

Looks to me like the people that are filthy rich [0] can afford to move so fast that even the people who are very rich in the regular way can't keep up. [0] Which is not even enough, these are the ones with truly excess money to burn.

I'm not sure you read the article, it's not referring to financials, but tech debt.

I like Fowler and reviewed it well.

Are you assuming tech debt has no financial cost?

Re: The Future of AI Software Development

#36
I really hate that we allowed "debt" to become a synonym for "liability."

This isn't a case where you have specific code/capital you have borrowed and need to pay for its use or give it back. This is flat out putting liabilities into your assets that will have to be discovered and dealt, someday.

Re: The Future of AI Software Development

#37
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…

>24 tokens/second

this is marketing not reality.

Get a few lines of code and it becomes unusable.

Re: The Future of AI Software Development

#38
post #30
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…

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.

"a (somewhat wealthy) hobbyist"

Re: The Future of AI Software Development

#39
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…

You don't even need to go this expensive. An AMD Ryzen Strix Halo (AI Max+ 395) machine with 128 GiB of unified RAM will set you back about $2500 these days. I can get about 20 tokens/s on Qwen3 Coder Next at an 8 bit quant, or 17 tokens per second on Minimax M2.5 at a 3 bit quant.

Now, these models are a bit weaker, but they're in the realm of Claude Sonnet to Claude Opus 4. 6-12 months behind SOTA on something that's well within a personal hobby budget.

Re: The Future of AI Software Development

#40

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…

There exist a large number of people who are absolutely convinced that LLM providers are all running inference at a loss in order to capture the market and will drive the prices up sky high as soon as everyone is hooked.

I think this is often a mental excuse for continuing to avoid engaging with this tech, in the hope that it will all go away.

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