Gotta be honest, almost every "how to use AI" resource seems pointless to me. I'm either going to ask the AI how to do it, or if it's about using the AI then we can just bake it into the harness or wait for Anthropic/OpenAI to do it for me because they're always trivial.
All of these resources on agentic workflows, managing agent memory, harness engineering, etc. appear to just be theatre to me.
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.
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.
If the bar is knowing how to type a question into a box, I'm confident almost everyone is better off starting with that then reading a "cookbook" that starts with installing python packages.
After all this effort of not opening the models, then trying to forbid people to use open models and all the rubbish their CEO keeps talking about common people I am done with Anthropic.
I can't use it on good faith
Same goes for grok, chat gpt and others all involved in killing people and monopolising the market.
I've been cooking with the help of LLMs a few times a month for over a year now. It's worked out well 9/10 times.
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.
One of the most satisfying and useful applications for AI is handing it the URL for a recipe (replete with 8 paragraphs of useless introductory text, 2 paragraphs dedicated to how to refrigerate the meal, 9 inline advertisements and a mid-scroll ad) and having it return the actual recipe in Markdown in an Obsidian folder.
I have actually cooked with LLMs, specifically Gemini, few times this year.
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.
All of these resources on agentic workflows, managing agent memory, harness engineering, etc. appear to just be theatre to me.
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
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.
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.
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
Before: bland
After: bland with gradients
Other AI labs also tend to publish examples and cookbooks on GitHub and Hugging Face, so it's always worth keeping an eye on those as well.
I can't use it on good faith Same goes for grok, chat gpt and others all involved in killing people and monopolising the market.
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'm not enough of a designer to be able to point exactly at what makes it so, but Claude does seem to have a somewhat limited repertoire of styles.
Maybe if you could point more precisely at the required changes, you could discourage it?
OpenAI's started in June 2022 https://github.com/openai/openai-cookbook/commit/535f545be7e...