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Did you use chatjimmy? It's somewhat terrifying to use when you think of the potential results with a better model. Ok, real life example: I now spend most of
by QuiDortDine 2mo ago
Did you use chatjimmy? It's somewhat terrifying to use when you think of the potential results with a better model.
Ok, real life example: I now spend most of my time, as a developer, waiting for the agent to do its thing (after careful prompting, I'm also thinking about work stuff, don't worry I'm not useless). What if it gave back the same excellent results, but instantaneously? Why, then, I certainly would become the bottleneck. So, quite possibly, my last work task would be to plug this agent directly into the ticket system where the domain experts input their feature requests. Maybe we still need 1 developer out of 100, to coordinate releases and all that (ok, say 1 out of 10).
But that's not taking things far enough: why do we need these domain experts at all? Our pitch is clear, and all software-enabled, though it took years to develop. We can just have the clients express their concerns to the AI, directly or indirectly. Have multiple lighting-fast agents with different roles (refactoring agent, new features agent, debugger agent, domain expert agent, etc.). So we fire everyone, maybe keep 1 product owner / devops to keep the trolls out. The cost is still probably 100 times less than it used to be (beyond the initial cost of acquisition of the magic machine or whatever).
But one of these clients, surely, will realize that these 10 years of manual and slowly-automated development can now be emulated in very, very little time. Why not just, say, take screenshots of the entire app and feed them into the magic machine? Why, this way, they could have the service for a tenth of the yearly cost, forever!
And then the economy implodes.
I'm not saying it's THE most likely version of things, I'm saying that at a certain level, quantity (or rather, speed) is a quality all its own. And this new quality might change the world. Let's hope it's for the better!
- wsintra2022 2mo agoI think this reads like Ray Kurzwheil (sorry not able to spell that off top of my head, that bloke who wrote that book about the future) .. But yeah very dystopian and totally realistic. Not if but when..
- QuiDortDine 2mo agoI LOVE Kurzwheil! Thank you for the compliment, I'm very far from having his writing skills. But yes sci-fi is looking more and more like, well, sci.
- xur17 2mo agoI'm not sure inference speed is always the slowest thing for me right now. The agent is running tests, loading webpages, etc, which all take time. I don't know if a fast agent would speed things up in all cases. That said, it obviously depends on the project.
- jodrellblank 2mo ago> "The agent is running tests, loading webpages, etc, which all take time" A frustrating vision of the future would be when we've been asking for faster loading lighter web pages for years and then companies start caring about it and improving it not for us humans but for LLMs.
- evilduck 2mo agoIt's already kind of that way with MCP servers popping up everywhere. The JIRA MCP server is like a couple orders of magnitude faster to work with than the website itself.
- andersonpico 2mo agoThey finally cared about clear requirements and documentation when that meant getting rid of devs.
- layla5alive 2mo agoThat happened at corpo work for each of: * Build times * CI latency * Developer tooling * Documentation * Modularity
- bdangubic 2mo ago> I now spend most of my time, as a developer, waiting for the agent to do its thing (after careful prompting, I'm also thinking about work stuff, don't worry I'm not useless). you need to launch 10-15 more terminals, who is waiting these days? :)
- QuiDortDine 2mo agoYou sound like my boss! I'm not really into the whole "burnout" thing though.
- bdangubic 2mo agohow can you get burned out just watching the work being done for you?? :)
- pastel8739 2mo agoThis is the same pitch that people make about AI today. Speed isn’t the differentiator, quality is
- Certhas 2mo agoSo for every work produced by AI have ten separate agents review it thoroughly.
- sroerick 2mo agoThey are both the differentiator. AI previously provided speed but not quality. As soon as quality reached an acceptable threshold, the speed became the reigning factor. In my opinion the quality is still much lower, but speed means the cost is significantly lower also.
- TeMPOraL 2mo agoAI is already fast enough that human is a bottleneck. Hell, typing speed became a bottleneck like it was never before. I mean, if an agent can do half-decent work in less time than it takes the user to prompt them (and "user" in this context is a fast touch-typist like most programmers are), it's obvious it's not the agent that's the bottleneck anymore.
- tripzilch 2mo agoBecause finishing someone else's (or something else's) "half decent work" to the point of "actually decent" becomes the bottleneck. This has always been the case for human project management, and LLMs just aren't at that level yet. It's more like everyone is speed running to how fast they can convince others that "half decent" is good enough. And for sure, newer models of LLM seem to be getting better at that.
- TeMPOraL 2mo ago> It's more like everyone is speed running to how fast they can convince others that "half decent" is good enough. But that's what Agile is all about, isn't it? We've been speedrunning delivering increasingly smelly shit at increased velocity ever since SaaS became a thing, because ubiquitous Internet access is what allowed our industry to adopt the "lob feces over the fence for users to deal with" release model. AI does speed that up, true (though since the market - and management - didn't catch up with it yet, we have a brief moment where we can use AI to increase quality while keeping usual delivery rate.)
- manmal 2mo agoErrors compound, and making 1000 wrong decisions per hour, will not result in something useful. Maybe you‘ve tried setting up guardrails for good design or architecture at some point? I think it’s simply not possible to do that. It would certainly be an accelerator for people who know exactly what they want. And it would remove multi tasking, which I‘d appreciate.
- Ericson2314 2mo agoIf your task has incremental rewards/feedback, you can push the "intelligence rate" simply by sampling the reward function faster. That's not fake, even if it not a substitute either. This is the "dumber but honest person that works harder" phenomenon, vs "lazy genius".
- gf000 2mo agoThat's a good way to put it, but still my experience is that worse code bases are non-linearly harder to maintain and improve in the future, software tends to break down without a good enough base. Sure, in the future full rewrites and stuff like that will be just another "throw money at it" problem, but fundamentally software can get arbitrary complex and we barely know how to write large, maintainable code bases. Nonetheless, I think testing (and maybe proofs) will have its long-awaited time to shine, as being the "reward function".
- Ericson2314 2mo agoI totally agree with you on the first bit, but I also think that I am way better at deciding on how to refactor code bases than the LLM is. Right now, I put models in low thinking mode during my refactors and hate waiting. I would much rather have a faster model that that maybe was slightly stupider, and I would wait far less long between prompts where it needs my valuable input. Models that are dumb, but humble and fast, can be fine.
- momojo 2mo agoI don't have a great answer but you pose a great question. Obviously a CTO is not going to walk away from the technology just because it's not good enough. That much more incentive for someone to create a powerful enough harness that can direct that power safely and productively. Like a nuclear core, we'll need to come up with the graphite rods and water tank. And if tokens are essentially free, why not, for every million tokens, spend 10x tokens on code review, testing, etc?
- visarga 2mo agoAI helps you but also your competition, and gets factored in by investors while customers can use it to find better deals. The whole market is different even if a company did nothing. Whatever you can cheaply do with AI is not a moat, if there is profit in there there will be quick imitation and competition will eat away those profits. Models can be replaced easily, harnesses & AI tools too. And if cloud inference gets too expensive there are local models keeping the cloud prices hard capped. Probably AI won't make anyone very rich.
- IOT_Apprentice 2mo agoI tried it. I asked where Bruce Lee was born. It stated he was born in Hong Kong. I challenged it and it went further naming a hospital there. I stated he was born in San Francisco and it apologized and then said his father was a missionary traveling in America, which was also wrong. Bruce’s father was a famous Cantonese Opera singer and actor. This model had zero information right, while being fast in responding. Unacceptable.
- selcuka 2mo agoIt gave the correct answers to both questions for me: > Bruce Lee was born in San Francisco, California, USA on November 27, 1940. > Bruce Lee's father was a Chinese opera singer That being said, this is not a good test. It is a language model (a very small one), not an encyclopedia. ChatJimmy interface is just a tech demo. Without tool calling functionality we can't expect it to be factually correct.
- logicallee 2mo agoif it's baked into silicon how can you two get different answers?
- v9v 2mo agoIt still works the same way other LLMs do, by outputting the probability distribution over the possible completions (The weather is ... (sunny (50%), cloudy (50%))). Then the next token is sampled from this probability distribution (in our example the next word could be "sunny" or "cloudy" equally likely), which can result in different outputs every run.
- logicallee 2mo agoCould the model or algorithm be changed to make it deterministic somehow? It could help a lot if there were reproduceable outputs from deterministic baked-in silicon.