Does anyone else feel like Google is just always a dollar short and a day late here? Maybe not a dollar short, but it's like they've consistently been focused on the wrong thing. First they missed chatbots, now they're missing coding agents while they double down on chatbots and video gen (which OpenAI has already basically abandoned). Maybe this strategy is actually genius and I'm too stupid to grasp it.
Nano Banana Pro is still the industry standard as far as I’m concerned. I think giving a vision model spatial awareness is the next evolutionary step here, so I don’t think they’re behind at all.
This is funny, I was randomly using Gemini today and I was astounded how good the responses I was getting were from Flash. I guess this must be the reason why.
I feel like the main issue here is that it does seem like in the current trajectory the job loss outcome is going to happen before any of these potential really good outcomes. I'm down for a utopian future, but I don't have to want to spend 10 to 20 years in a depressing unemployed hellscape before I get there.
Agreed, there is one simple solution that always works albeit limited and temporary. Jefferson said it, Luigi did it, many are thinking it - but we must ensure it does not turn into a mass purge, just limit to maybe a few parasitical PE players and everyone else will fall in line for at least a few years.
I don't know about this one. For me, at least, the reward of "self progression" is intimately tied to external systems. I would not care about getting better at programming if there wasn't a social and financial reward attached.
In my view, UBI basically puts me, an upstanding citizen with hard skills that AI made obsolete, on the same playing field as the average junkie off the street in SF. Why on earth would I want that? People are different, the modern economy is a great stratification mechanism at putting you near people of similar conscientiousness, and getting rid of that is a recipe for misery.
I feel the backlash really comes down to the fact that AI is a fucking pain in the ass when it comes to planning your life. Nobody asked for it, nobody wanted it, but regardless we're all now thrust into a technological revolution where you have to bust your ass upskilling or else be fired. Most people are inherently lazy and "work to live" as opposed to the other way around. It's no wonder they'd be less than enthused about a technology that basically promises to enrich their bosses thanks to they themselves being more productive.
Moreover, the executives have done an absolutely horrible job of communicating the benefits. It's all "your job is going to be replaced in the next few years". I've had plenty of amazing conversations with Claude about the imminent AI-enabled revolutions in materials science, biotech, etc - and yet for some reason this is the exact opposite of the PR line they're taking.
This happened to me and I can promise you that I did nothing wrong. It is very frustrating to essentially be locked out of the app-based dating market without even knowing why.
This is pretty cool. How would you say that these open models compare to SOTA on coding tasks? I pay $200/mo for Claude Max but honestly this sounds way more fun.
Nowadays I use our local setup 95% of the time, but it is not that long since that flipped for me personally.
Context: I have a $20 Claude Code subscription, and have used it for a handfull of small-ish projects the last year, in parallel with local models on my AMD 9700XTX (24GB) at home. Mostly Ministral 14B and more recently Qwen3.6 27B Dense 4q.
Historically, the tooling (interferens engines and harness) has been the biggest challenge when using local models, a lot of the benefits from Claude Code was a rather unified and well oiled agent system. Local setups often bring with them sutle incompatibilities between models, inference engines and agent systems that are not obvious from initial testing, but cause trouble on projects larger than a couple of files.
The Spark setup at work is now at a point where I do not miss Claude, like at all. A big part of this is the harness and the tools available to the agent, most critically a good tool for searching online. I use my Kagi subscription to allow the models to fetch up-to-date information, and the Kagi MCP I use also has a summarizer which is very helpful in avoiding rapidly filling up the context window.
I mostly use Zed and it's native agent, which only recently got muuuch better, and on the terminal I use Pi with a minimal selection of extensions (currently pi-kagi-search, pi-smart-fetch, pi-btw and pi-diffloop). I also have Pi in Zed via the ACP, but it does not work so well with some of the extensions, especially the lack of a built-in permission system is a problem, when YOLO-mode is the only mode :)
Honestly, as long as you have a model that is decent at tool calling, your good. Having a solid and stable frame around your model makes a huge difference. The only caveat in all of this is that I spend most of my time on smaller projects and debugging on linux base systems, not huge and complex code bases, so your mileage might vary.
The next phase at work is to set up a chatGPT-like webinterface, and so far LibreChat is at the top of my shortlist. We had OpenWebUI for a while, but it is so bad at using MCP tools that it is practically non-functional for us. LibreChat is a bit more work to set up, but the interface and it's MCP story is much more solid. The goal is to plug in our internal helpdesk, docs and task manager system to LibreChat via MCPs to give us a quick way to query and gather information that is currently very time consuming to do on your own.
I don't get why you would have an LLM interpret things for you. Like honestly, you replace the software in this example with simple transcription software, the issues disappear.
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