Remember in 2023 when people thought "prompt engineering" would be the new software engineering and invested tons of time into learning CoT, ReAct, thread-of-thoughts, etc?

Those were mostly obviated by reasoning models and harness updates by 2024.

It seems pointless to invest energy into the latest/greatest AI technique or framework when they're going to either be absorbed or replaced on a 3 month cycle.

Not only that, but all of this tooling around models has such a short shelf life as the models themselves grow in capabilities, they absorb the tooling. We've already seen it over and over again.

There was an article by Vercel on how ineffective tool calling is compared to just a single md file with clearly defined instructions. They showed a clever way on how to use compressed indexes. My experience with tool calling was similar to what Vercel described, and I spent hours trying to perfect it. Since reading Vercel’s findings, Claude.md and Agents.md, maybe a Project.md it’s all I use.

Right now I feel like I'm getting so much value out of working daily with Fable, but I'd be embarrassed to share my sessions because they're pretty much how I would talk to a colleague. Spelling mistakes and half-baked thoughts included. Gone are the formal sounding prompts and specs I was proudly writing 6 months ago. But it's getting the results.

>I'm either going to ask the AI how to do it

LLMs seem terrible at using LLMs in harnesses. Have you seen how they rot their context with the stuff they put in .md files if you let them?

You'd have to have the LLMs search, and thus these resources could be for them more than you

Thanks for saying the quiet part out loud. Everytime I do a demo it seems like a waste of time compared to just actually building.

Unless I'm doing something super complicated even taking time to set things up like subagents, etc. seems like a waste compared to just building.

The only things that really seem beneficial (for Claude Code) seems to be learning to set up loops, memory and finding relevant MCP servers.

Exactly. I think we all have to come to this conclusion ourselves, because the message we’ve been getting from the LLM companies is “sweet user, you DO add value to the LLM, you gave it that custom subagent, remember?”, and then they go and roll that idea into the next version. Once they do that a few times you go “eh why would I bother, this will be a default soon. I’ll just prompt it like normal”.

Just use the vanilla settings.

I suspect certain workflows like langchain and others like it will retain usefulness into the future. Having deterministic steps before and after the llm is the way to go for anything that might be potentially harmful. Which I guess is what the harness does, but why be limited to a generic harness when we can use it to make specific ones for our needs.

> I'm either going to ask the AI how to do it

First you have to know that "it" exists and is possible. A cookbook like this introduces readers to concepts and features they didn't know were there in the first place.

Yea i do the same. I can't be bothered to watch videos and courses on how to use claude better when I can simply ask it myself.

It was more important with earlier models, as they were less RL'd to golden paths, so the context could steer them more.

Now process engineering is more important than prompt engineering.

This is how I've gone about it with my Shopify site.

I appreciate there may be more efficient ways to do things if you're an actual developer or engineer but I'm not and the tools I've been able to build so far have been both fun to make and add value to our workflow as a small 2 person ecommerce business.

I do at least have a background in web as a designer for many years and having worked with developers I can at least spec and understand how a product might work which is one thing Claude/AI isn't hugely helpful with and often it's the testing and QA phase as always where the problems and shortcomings expose themselves.

Ok, thanks, because I looked at one example and was like, “I am supposed to take someone’s OpenAPI doc and translate it back to English for the model?” And if they’re implying I should have an AI do that, why don’t they just build that step into the models rather than having someone prompt an AI to write these half-ass docs?

Not only that, but they change on a whim with new ideas on how to do things every few weeks.

if you know how to ask Ai about how to use Ai, you already know how to use Ai

the point of guides is to provide assurance for people unfamiliar to the process in the first place

If these things are so smart why do I have to coax it to be useful with all these magic spells scrawled on markdown parchment.

I think the main thing of interest in the linked site is the dates. You can quickly get a view of what was possible and when.

You don't learn about progress if you don't take part in it.

Before /goal was ralph-wiggum it was def an interesting learning experience, it was interesting to see how Claude became a lot better doing this itself but it still took 6 Month and more.

You can wait and sit it out and suddenly you get fired if you miss the point when to start spending more time and energy on topics like this.

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