Coding agents could make free software matter again

The blog post of this thread argues that now, even average users have the ability to modify GPL'd code thanks to LLMs. The bigger advantage though is that one can use it to break open software monopolies in the first place.

A lot of such monopolies are based on proprietary formats.

If LLM swarms can build a browser (not from scratch) and C compiler (from scratch), they can also build an LLVM backend for a bespoke architecture that only has a proprietary C compiler for it. They can also build adobe software replacements, pdf editors, debug/fix linux driver issues, etc.

The Sunsama example actually argues the opposite direction. He spent an afternoon hacking around a closed system with an agent and it worked. If agents are good enough to reverse-engineer and workaround proprietary software today, the urgency to switch to open source decreases, not increases. "Good enough" workarounds are how SaaS stays sticky.

And agents don't eliminate the trust problem, they move it. Today you trust Sunsama with your workflows. In this vision, you trust your agent to correctly interpret your intent, modify code safely, and not introduce security holes. Non-technical users can't audit agent-modified code any better than they could audit the original source. You've traded one black box for another.

On the real measures of "fair use", at least in the US: https://fairuse.stanford.edu/overview/fair-use/four-factors/ I would contend that it absolutely face plants on all four measures. The purpose is absolutely in the form of a "replacement" for the original, the nature is something that has been abundantly proved many times over in court as being something copyrightable as a creative expression (with limited exceptions for particular bits of code that are informational), the "amount and substantiality" of the portions used is "all of it", and the effect of use is devastating to the market value of the original.

You may disagree. A long comment thread may ensue. However, all I really need for my point here is simply that it is far, far from obvious that waving the term "FAIR USE!" around is a sufficient defense. It would be a lengthy court case, not a slam-dunk "well duh it's obvious this is fair use". The real "fair use" and not the internet's "FAIR USE!" bear little resemblance to each other.

A sibling comment mentions Bartz v. Anthropic. Looking more at the details of the case I don't think it's obvious how to apply it, other than as a proof that just because an AI company acquired some material in "some manner" doesn't mean they can just do whatever with it. The case ruled they still had to buy a copy. I can easily make a case that "buying a copy" in the case of a GPL-2 codebase is "agreeing to the license" and that such an agreement could easily say "anything trained on this must also be released as GPL-2". It's a somewhat lengthy road to travel, where each step could result in a failure, but the same can be said for the road to "just because I can lay my hands on it means I can feed it to my AI and 100% own the result" and that has already had a step fail.

That's debatable. In case of a king you always know whom to blame and who has full responsibility. No opportunity to hide behind "well, you voted for this" or "I'm not making the laws, I'm merely enforcing them".

1. The code generated should be available to use. Some languages are simple enough there is an obvious way to do it. Many companies have developer programs with staff producing code intended to be used in the form of open source SDKs, example code, and tutorials.

2. If on the off chance, there is code that shouldn't be there, people should use DMCA. Anthropic, GitHub, and others support this.

3. At the macro level, it's hard to know know where this is going, so we should look to bellwether apps with more attention for guidance.