381–390 of 443 posts
Here's what I'd like: For the AIs to interface with the rich existing toolset for refactoring code from the pre-AI era. E.g., if it decides to rename a function, it resorts to grepping and fixing all usages 'manually', instead of invoking traditional static code analysis tools to do the change.
Earlier quoted context omitted.
From my IT POV, that’s what this is all about. It’s why none of these major players produce locally-executable LLMs (Mistral, Llama, and DeepSeek being notable exceptions), it’s why their interfaces are predominantly chat-based (to reduce personal skills growth and increase dependency on the chatbot), it’s why they keep churning out new services like Skills and Agents and “Research”, etc. If any of these outfits trul…
"It’s why none of these major players produce locally-executable LLMs (Mistral, Llama, and DeepSeek being notable exceptions)" OpenAI have gpt-oss-20b and 120b. Google have the Gemma 3 models. At this point the only significant AI lab that doesn't provide a locally executable model are Anthropic!
None of the present AI industry is operating in an ethical or responsible way, full stop. They know it, they admit to it when pressed, and nobody seems to give a shit if it means they can collapse the job market and make money for themselves. It’s “fuck you got mine” taken to a technological extreme.
This is interesting, and I think there are use cases where this feature may make sense. But this is not the feature they should or could have built, at least for Claude Code. CC already had a feature very similar to this -- subagents (or agents-as-tools). Like Skills, Subagents have a metadata description that allows the model to choose to use them in the right moment. Like Skills, Subagents can have their own instru…
I think skills and subagents are entirely complementary to each other. A subagent can use a skill. A skill can encourage the agent to run a subagent.
Let me just say: I'm nitpicking what I think is overall an incredible tool and a great new feature of said tool.
For a moment, pretend Subagents don't exist. And Anthropic just released "In-Thread Skills" (identical to what are now "Skills") and "Out-of-Thread Skills" (identical to Subagents). I feel like the library of Skills that would be published would be useful in more circumstances if this were the reality. Of course some may publish both versions of a thing, and of course you could do a shim of some kind, but it could be _nicer_.
Another similar thing: how are Skills different than the Slash Command Tool [0]? Why not just amend Slash Commands to allow them to include scripts and other supplementary files stored in a directory, and boom, you have Skills. Instead we have a net new primitive.
And the larger unfortunate reality is that because Claude Code is the white-hot center of this white-hot ecosystem, there are likely a dozen other tools in this space that are going to copy the exact same primitive set just to have perceived parity with CC.
I'm veering into "yelling at clouds" territory now, so I'll get off my soapbox. It's just one of those things that feels like it could be slightly more awesome than the awesome that it is, is all.
[0] https://docs.claude.com/en/docs/claude-code/slash-commands#s...
I fear the conceptual churn we're going to endure in the coming years will rival frontend dev. Across ChatGPT and Claude we now have tools, functions, skills, agents, subagents, commands, and apps, and there's a metastasizing complex of vibe frameworks feeding on this mess.
You forgot mcp-everything! Yes, it's a mess, and there will be a lot of churn, you're not wrong, but there are foundational concepts underneath it all that you can learn and then it's easy to fit insert-new-feature into your mental model. (Or you can just ignore the new features, and roll your own tools. Some people here do that with a lot of success.) The foundational mental model to get the hang of is really just:…
I’ve done this a few times (pre and post MCP) and learned a lot each time.
Earlier quoted context omitted.
This is an uninformed take. Much of the improvement in performance of LLM based models has been through RLHF and other RL techniques.
> This is an uninformed take. You may disagree with this take but its not uninformed. Many LLMs use self‑supervised pretraining followed by RL‑based fine‑tuning but that's essentially it - it's fine tuning.
Also how do you think the most successful RL models have worked? AlphaGo/AlphaZero both use Neural Networks for their policy and value networks which are the central mechanism of those models.
Earlier quoted context omitted.
You forgot mcp-everything! Yes, it's a mess, and there will be a lot of churn, you're not wrong, but there are foundational concepts underneath it all that you can learn and then it's easy to fit insert-new-feature into your mental model. (Or you can just ignore the new features, and roll your own tools. Some people here do that with a lot of success.) The foundational mental model to get the hang of is really just:…
You have a great way of demystifying things. Thanks for the insights here! Do you think a non-programmer could realistically build a full app using vibe coding? What fundamentals would you say are essential to understand first? For context, I’m in finance, but about 8 years ago I built a full app with Angular/Ionic (live on Play Store, under review on Apple Store at that time) after doing a Coursera specialization. T…
For personal or professional use?
If you want to make it public I would say 0% realistic. The bugs, security concerns, performance problems etc you would be unable to fix are impossible to enumerate.
But even if you had a simple loging and kept people's email and password, you can very easily have insecure dbs, insecure protections against simple things like mysqliinjections etc.
You would not want to be the face of "vibe coder gives away data of 10k users"
Earlier quoted context omitted.
You have a great way of demystifying things. Thanks for the insights here! Do you think a non-programmer could realistically build a full app using vibe coding? What fundamentals would you say are essential to understand first? For context, I’m in finance, but about 8 years ago I built a full app with Angular/Ionic (live on Play Store, under review on Apple Store at that time) after doing a Coursera specialization. T…
Really depends on the app you want to build. If I'd use Vibe coding I wouldn't use Lovable but Claude code. You can run it in your terminal. And I would ask it to use NextAuth, NextJS and Prisma (or another ORM), and connect it with SQLite or an external MariaDB managed server (for easy development you can start with SQLLite, for deployment to vercel you need an external database). People here shit on nextjs, but due…
I’m not 100% set on Lovable yet. Right now I’m using Stitch AI to build out the wireframes. The main reason I was leaning toward Lovable is that it seems pretty good at UI design and layout.
How does Claude do on that front? Can it handle good UI structure or does it usually need some help from a design tool?
Also, is it possible to get mobile apps out of a Next.js setup?
My thought was to start with the web version, and later maybe wrap it using Cordova (or Capacitor) like I did years ago with Ionic to get Android/iOS versions. Just wondering if that’s still a sensible path today.
I’m kind of in stitches over this. Claude’s “skills” are dependent upon developers writing competent documentation and keeping it up to date…which most seemingly can’t even do for actual code they write, nevermind a brute-force black box like an LLM. For those few who do write competent documentation and have well-organized file systems and the risk tolerance to allow LLMs to run roughshod over data, sure, there’s so…
LLMs reward developers who can write. Maybe that's one of the reasons so many developers are pushing back against them!
I fear the conceptual churn we're going to endure in the coming years will rival frontend dev. Across ChatGPT and Claude we now have tools, functions, skills, agents, subagents, commands, and apps, and there's a metastasizing complex of vibe frameworks feeding on this mess.
You forgot mcp-everything! Yes, it's a mess, and there will be a lot of churn, you're not wrong, but there are foundational concepts underneath it all that you can learn and then it's easy to fit insert-new-feature into your mental model. (Or you can just ignore the new features, and roll your own tools. Some people here do that with a lot of success.) The foundational mental model to get the hang of is really just:…
That description sounds a lot like PocketFlow, an AI/LLM development framework based on a loop that's about 100 lines of python:
https://github.com/The-Pocket/PocketFlow
(I'm not at all affiliated with Pocket Flow, I just recall watching a demo of it)
Earlier quoted context omitted.
Not dense to ask questions! There are two separate concepts in play: 1) Maintaining the state of the "conversation" history with the LLM. LLMs are stateless, so you have to store the entire series of interactions on the client side in your agent (every user prompt, every LLM response, every tool call, every tool call result). You then send the entire previous conversation history to the LLM every time you call it, so…
Very helpful. It helps me better understand the specifics behind each call and response, the internal units and whether those units are sent and received "live" from the LLM or come from a traditional db or cache store. I'm personally just curious how far, clever, insightful, any given product is "on top of" the foundation models. I'm not in it deep enough to make claims one way or the other. So this shines a little…