Hi, This is indeed a new frontier and there is great potential for both good and for harm. I will agree with Sam that for a person tasked with helping to maintain something like Cinelerra-GG with little programming skills then AI opens up some great possibilities. I am also not a programmer but AI has allowed me to improve AV Linux in various ways but I always try to remain with programming languages that I am at least somewhat familiar with so I can read and audit what it is doing while I'm testing. I think it is always valuable to have the AI also create debugging, testing and verification tools for your projects as well as the main development. When this gets to a public beta testing phase please let us know on the list, I would be interested in testing if time from other things allows. Thanks very much to Sam, Phyllis and all other contributors for your tireless work, it is very much appreciated! Best, Glen On 2026-09-21 15:04, Sam via Cin wrote:
Am 21.09.26 um 20:00 schrieb Andrew Randrianasulu via Cin:
Thanks for this (building qt6 on unsupported OS/architecture is a big pain, so I like to have something less modern for my odd usecases).
Thanks Sam, this is indeed Big Surprise - I see a lot of emulators or even FPGA implementations supercharged with "AI" tools.
My other problem with AI (apart from resource use and how it shoveled into everything) is who control it - as those companies increasingly look for some profitability "free" options will dry up, leaving users with expanded codebase uneasy to navigate/fix manually. It was "a bit" of problem with original Cinelerra, too, I must admit.
I am relatively happy that I am not only person poking those C files now. For now I live mostly on Macintosh forums, testing new software for PPC machines or emulators for/on said machines.
There are some talks about upcoming harder times (due to all those wars etc), so stay safe from preventable dangers!
Your concerns are absolutely valid, and I ask myself the same question almost every day.
I’m fully aware that many of the tools currently leading the industry are heavily subsidized. Claude Code, for example, currently costs around $200 per month, and even then I sometimes need more than the weekly quota allows.
I’ve built an API cost calculator into my workflow to estimate what the same usage would have cost through direct API access. At this point, the theoretical cost is already in the tens of thousands of dollars. In the long run, I don’t think this level of subsidization is sustainable for providers such as Anthropic or OpenAI. They will either have to raise prices, improve efficiency significantly, or both, something we are already seeing from Chinese AI providers, with increasingly capable and efficient models such as the latest DeepSeek 4.1 Flash model.
That is also why I’m actively testing alternative coding models and frameworks, including offerings from providers such as Qwen, Kimi, GLM, and DeepSeek. I’ve always been a strong supporter of open source (open weights); it’s simply in my DNA. If these tools give me the opportunity to improve Cinelerra, I’m going to use them. I use many of them through OpenRouter, where I can select specific data-center providers and, where available, use zero-data-retention policies.
I have to say that open-weight models have reached a level of quality that I would not have expected only a few months ago. As a result, I’m gradually shifting more and more of my workload toward them.
I’m also using OpenCode much more extensively and expanding it with the functionality I need for my own development workflow. One of the most interesting developments is that some AI companies have realized that scaling cannot depend indefinitely on simply adding more and more hardware. There is enormous value in making models smaller, faster, and more efficient while maintaining, or even improving, their capabilities.
For highly complex coding tasks, models from Anthropic and OpenAI are still among the strongest options available in my experience. But I’m no longer dependent on them alone, I already have a Plan B, and that Plan B is improving rapidly.
As for Cinelerra-GG Qt6 itself, I’m continuously reviewing and optimizing the code. I often run multiple independent code reviews on the same sections to identify problems, improve structure, and catch things that might have been missed in an earlier pass.
I know the code will not always be perfect, especially during an active modernization effort. But at some point, you have to start.
I could wait years and hope that new developers eventually join the project, or I can start doing the work now, improve it step by step, and learn along the way.
I chose to start. It’s an experiment. It’s worth a try, in my opinion.
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