It turns out the "average" version of a recipe that's baked into the weights is usually a solid recipe, and they're really good at offering substitutions for things like "I don't have ingredient X" or "make it vegetarian".

It's also fun promoting "make it tastier" once or twice after each recipe just to see what happens.

Works surprisingly well, can even tell it "I have so and so ingredients in my pantry, I want a keto-friendly meal, what can I make?" followed with some narrowing down dialogue-style.

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.

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

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.

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.

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

Now process engineering is more important than prompt engineering.

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.

Just use the vanilla settings.

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.

OpenAI's started in June 2022 https://github.com/openai/openai-cookbook/commit/535f545be7e...

I have been using Magic Patterns which is very good at generating initial prototypes, especially when driven by an agent familiar with it's facilities and constraints.

I assume the service is just a wrapper plus scaffolding but I like it. You have to push it though to get anything particularly creative but it's good at standard front end designs.

https://www.magicpatterns.com/

That's not necessarily what you're after because I only use it for piloting stuff, not for adhoc feature addition and fixes.

My system CLAUDE.MD spells out my preferences in stack and architecture, and how I expect the agent to interact with me.

I have it generate a summary doc in large repos so it doesn't need to slurp in the world to review a PR or work on a corner of it.

This is to say, Anthropic seems to be going down the path you are describing to make the CLAUDE.MD unnecessary. But I think that's the Claude Code harness.

If you're just having an agent produce code, then I'd agree. I'd argue that any additional context it might need ought to be included in README.md anyways, just like a human.

But I have projects where agents do more than just code, and retaining context about how I want the agents to operate, keeping track of gotchas, avoiding unnecessary steps in the future, etc., just ends up going into CLAUDE.md. It's not for me; it's for the agents. I also never edit this file directly. I may review it every once in a while to make sure there isn't anything weird in there, but I leave it to the agent to add what it thinks is necessary (or I'll tell it that something will be relevant in the future and that it should add it, etc.).

Although even this pattern isn't necessarily future-proof. Seems like skills are kind of taking that role. Still, I end up with a CLAUDE.md in these kinds of scenarios to catch all the little pieces of context that don't fit nicely anywhere else.

You're probably burning tokens. A markdown file with a summary, structure of your project, rules, and even goals prevents Claude from hunting for and reading files over and over. Each new session (or after compact) would be starting from scratch. I take it a step further and create a HANDOFF.md file between compacting that gives the next session full context of what was done and how to continue.

Also:

"Treat CLAUDE.md as the place you write down what you’d otherwise re-explain. Add to it when:

Claude makes the same mistake a second time

A code review catches something Claude should have known about this codebase

You type the same correction or clarification into chat that you typed last session"

https://code.claude.com/docs/en/memory#claude-md-files

Personally I prefer the before shots all the way down.

"Use a black background and this hideously wide font!"

[1]: https://github.com/anthropics/claude-code/blob/main/plugins/...