Glad to see this response, I was wondering the other day how the affected accessibility. I remember reading a thread a few years back of visually challenged developers and their work flow and was kinda surprised there has been such little discussion around developer accessibility with the advent of ai agents and coding routines.

If there is one thing I have seen is that there is a subset of intellectual people will still be adverse to learning new tools, hang to ideological beliefs (I feel this though, watching programming as you know it die in a way, kinda makes you not want to follow it) and would prefer to just be lazy and not properly dogfood and learn their new tooling.

I'm seeing amazing result to with agents, when provided an well formed knowledge base and directed through each piece of work like its a sprint. Review and iron out scope requirements, api surface/contract, have agents create multi phase implementation plans and technical specifications in a share dev directory and to make high quality changes logs, document future consideration and any bugs/issues found that can be deferred. Every phase is addressed with a human code review along with gemini who is great at catching drift from spec and bugs in less obvious places.

While I'm sure an enterprise code base could still be an issue and would require even more direction (and opus I wont let touch java, it codes like an enterprise java greybeard who loves to create an interface/factory for everything), I think that's still just a tooling issues.

I'm not of the super pro AI camp, but having followed its development and used it throughout. For the first time I am actual amazed and bothered, and convinced if people dont embrace these tools, they will be left behind. No they dont 10-100x a jr dev, but if someone has proper domain knowledge to direct the agent, performs dual research with it to iron things out with the human actually understanding the problem space, 2-5x seems quite reasonable currently if driven by a capable developer. But this just move the work to review and documentation maintenance/crafting. Which has its own fatigue and is less rewarding for a programmers mind who loves to solve challenges and gets dopamine from it .

But given how man people are adverse...I dont think anyone who embraces it is going to have job security issues and be replaced, but here are many capable engineers who might due to their own reservations. I'm amazed by how many intelligent and capable people try llms/agents like a political straw man, there is no reasoning with them. They say vibe coding sucks (it does for anything more than a small throw away that wont be maintained), yet their examples for agents/llm not working is it can't just take a prompt and produce the best code ever and automatically and manifest the knowledge needed to work on their codebase. You still need to put in effort and learn to actually perform the engineering with the tools, but if it doesnt take a paragraph with no AGENTS.md and turn it into a feature or bug fix they are not good to them. Yeah they will get distracted and fuck up, just like if you throw 9/10 developers in the same situation and told them to get to work with no knowledge of the code base or domain and have their pr in by noon.

Damn, I just dove back into a vulkan project I was grinding through to learn graphics programing, life and not having the time to chase graphic programming bugs led me to put it aside for a year and a half and these new models were able to help me squash my bug and grok things fully to dive back in, but I never even consider that the rust vulkan ecosystem was worse off. it was already an insane experience getting imgui, winit and ash to play nice together, after bouncing back and forth between WGPU, I assume vulkan via ash was the safer bet.

IIRC there is another raw vulkan library that just generated bindings as well and stayed up to date but that comes with its own issues.

I've gotten interested in local models recently after trying the here and there for years. We've finally hit the point where small <24GB models are capable of pretty amazing things. One use I have is I have a scraped forum database, and with a 20gb devstral model I was able to get it to select a bunch of random posts related to a species of exotic plants in batches of 5-10 up to n, summarize them into and intern sqllite table, then at the end go through read the interim summarization and write a final document addressing 5 different topics related to users experience growing the species.

Thats what convinced me they are ready to do real work, are they going to replace claude code...not currently. But it is insane to me that such a small model can follow those explicit directions and consistently perform that workflow.

I've during that experimentation, even when not putting the sql explicit it was able to craft the queries on its own from just text description, and has no issue navigating the cli and file system doing basic day to day things.

I'm sure there are a lot of people doing "adult" things, but my interest is sparked because they finally at the level they can be a tool in a homelab, and no longer is llm usage limits subsidized like they used to be. Not to mention I am really disillusioned with big tech having my data or exposing a tool making API calls to them that then can make actions on my system.

I'll still keep using claude code day to day coding. But for small system based tasks I plan on moving to local llms. Their capabilities have inspired me to write my own agentic framework to see what work flows can be put together for just management and automation of day to day task. Ideally it would be nice to just chat with an llm and tell it to add an appointment or call at x time or make sure I do it that day and it can read my schedule and remind-me at a chill time of my day to make the call, and then check up that I followed through. I also plan on seeing if I can also set it up to remind me and help to practice mindfulness and just general stress management I should do. While sure a simple reminder might work, but as someone with adhd who easily forgets reminders as soon as they pop up if I can get to them now, being pestered by an agent that wakes up and engages with me seems like it might be an interesting workflow.

And the hacker aspect, now that they are capable I really want to mess around with persistent knowledge in databases and making them intercommunicate and work together. Might even give them access to rewrite themselves and access the application during run time with a lisp. But to me local llms have gotten to the point they are fun and not annoying. I can run a model that is better than chatgpt 3.5 for the most part, its knowledge is more distilled and narrower, but for what they do understand their correctness is much better.