https://platform.claude.com/cookbook/coding-prompting-for-fr... Before: bland After: bland with gradients
Gradients fixed it. They fix everything.
Claude Cookbook
81–90 of 182 posts
Re: Claude Cookbook
#82Earlier quoted context omitted.
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 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.
I've see people write "broooo pleaseeee!" into the box. Something about the universe providing better fools.
Re: Claude Cookbook
#83This is definitely controversial, but I think the best CLAUDE.MD is no CLAUDE.MD at all.
Every time I found myself wanting to put information into that file, I asked myself "Why isn't this already obvious from the code itself?"
I don't need to tell the agent my tech stack, what DB access library I'm using, the way in which I write my tests, etc. Why? Because it's all very clearly spelled out within the code itself. I've gone great lengths to make sure that my fairly complex domain can be understood by a person with little domain knowledge, which means it should certainly be understood by a tool that has a wealth of it.
Re: Claude Cookbook
#84Immensely disappointed; I expected an actual cookbook.
Re: Claude Cookbook
#85Earlier quoted context omitted.
As part of a previous job I needed to audit internal AI usage from a largely non-technical employee population. The prompts were, predictably, really bad. Broken English, sentence fragments, vague requests, lack of context. Yet somehow, the users always got the answer they were looking for. It might have taken a few extra turns with questions from the model, but the end result was the same. It's humbling, but a flowe…
You call that a peasant prompt, but it's actually almost perfect. Couple notes, but it's 95% of the way there. "Can a dog eat sunflower seed" is probably the perfect version, just 1 extraneous word in this version. Unless the user wanted to know if a cat could eat sunflower seed or something.
I am tempted to try get me a lawyer dog
Re: Claude Cookbook
#86Gotta 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.
Not only that, but they change on a whim with new ideas on how to do things every few weeks.
Re: Claude Cookbook
#87Earlier quoted context omitted.
Isn't it clear that some people are better at working with/prompting LLMs than other people? Or is the idea that what you write to them and how you use them doesn't matter, it's all up to the model/harness? To me this seems clear, so then clearly this is a skill, which typically is called "prompt engineering". Specifically CoT or the other things you mention wasn't referred to as "prompt engineering" as far as I know…
I feel the same way about "prompt engineering" as I feel regarding the term "parkour" - you know, running and jumping on stuff. Are people really putting on their resumes that they are capable of reading and writing and appropriately defining and limiting context? That's all prompt engineering is - it's being able to communicate effectively and elucidate your objectives. Congratulations to all you English majors out…
Parkour is for the more energetic peripatetic.
Re: Claude Cookbook
#88Gotta 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.
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.
Re: Claude Cookbook
#89Earlier quoted context omitted.
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.
I've see people write "broooo pleaseeee!" into the box. Something about the universe providing better fools.
I do this often, I manage to get the results I’m looking for
Re: Claude Cookbook
#90Earlier quoted context omitted.
Isn't it clear that some people are better at working with/prompting LLMs than other people? Or is the idea that what you write to them and how you use them doesn't matter, it's all up to the model/harness? To me this seems clear, so then clearly this is a skill, which typically is called "prompt engineering". Specifically CoT or the other things you mention wasn't referred to as "prompt engineering" as far as I know…
It's not really a skill. The models are at this point smarter than you are, so the idea that you can prompt them "better" is laughable really when discussing frontier models. It's like imagining you could "prompt" Richard Feynman to be smarter at Physics. That is, for 99.9% of engineers, if you want the model to do a code review of your project, the best solution is to just ask Fable, "Hey Fable, do a code review of…
I find this very much untrue in my practice and my testing, where fable prompted to do a review found surface level issues, while prompting along the lines of "assume it's wrong, prove it's correct" found much more in depth and real issues.