It's possible I invented skills before they were common. I've always had some instructions in agents.md that are something like "when working with typescript, read prompts/conventions.ts.md, when working with our fooBar module, read prompts/foobar.md"
I'm not sure if this differs greatly from skills. Maybe my wording makes these "skills" less likely to be read at the correct times, but I haven't seen an issue.
Most guidance I’ve read, and experienced success with, is keeping a lean agents.md file and building out a tree of docs or skills that an agent can navigate via progressive disclosure.
I try to keep agents/Claude.md as tiny as possible. With high level "truths" that don't change. Stack used, invariants, file structure, and some scripts.
Skills are more for things you do often. I run mutation tests, type check,linting,etc. I _could_ just prompt and copy/paste the same prompt each time I need to, or I can just run /tests.
I also have skills for specialized tasks I need every once in a while, like a ux skill, a text skill optimized for xyz, etc.
Depends on how much information and details you have. The agents.md always goes into context. Detailed testing or process information might be excessive, when agent is working on UI. Skills are pulled when needed.
I handle the context problem by splitting the details to dozens of small md files. Agents.md acts as a router that directs the llm to correct documentation file/folder according to the task at hand.
This documentation is its own git repo, and the agents.md file has an explicit instruction to update the docs when it has learned something general that can be useful in future sessions. I then occasionally review and prune those docs.
The description in the front-matter (at the top of the skill markdown file) is the only thing in the context and used by the agent to determine when to read in the rest of the skill file.
skills are just an agents.md broken up into chunks so you can manage and share them separately. unfortunately there's no real good workflow for managing or sharing them separately, so most people end up treating them exactly the same way they do agents.md.
It’s always a hassle trying to find a time for our friend group to hang out, it can seemingly go on for hours. Everyone shares what days they’re available, someone suggests a time, it works for all but one, and the process starts again. That works! Makes the process way easier: when you set your availability it highlights time blocks that works for everyone.
It was a fun use of bitmasks; all availability is stored in 30 minute blocks (0001110000 would represent 1.5 hours available in 5 hours total) and then I use the AND operator across them all to find matching slots.
My problem with hard mode is it leaves a lot up to luck. If it was 3 letters and ended in “at” it could be pat, mat, bat, hat, cat, rat, sat, etc. so all you can do is to pick one and hope for the best.
Ai generate with human in the loop, so hard to say it’s not while also saying it’s terrible.
Definitely the fact that I have ai makes it more fesable for me to actually publish something rather than spednign years on copy I can spend time on code and outsource copy
The only way to get better at writing is by writing.
I’d rather read a less polished but clearly human written article than something clearly written by AI. If I can’t tell I can’t tell.
Use it for editing or as a review but the weird hyperbolic AI stuff makes me instantly close an article. I barely got past the intro:
ONE ATTRIBUTE. EXACT BEHAVIOR.
The markup says what happens.
Start with local behavior. Add the server only when the interaction needs to cross the wire. The attribute is moo= — in case you were wondering what the ox says.
Your onto something here, thanks - the title and the section where the things I’ve spent more time on than the rest
I mean this „ Behavior, right where it happens.
moo= for reactive signals and ordinary JavaScript on the element itself. Datastar SSE when the interaction has to cross the wire and patch HTML and state.”
Still feels bad but I know I went trhu it couple of times.
Not so much with the new sample you give here.
I only shared because it might very well be cool stuff but if people are tired of AI writing and close it like me then it’s a lost opportunity. Not publishing at all is a bigger loss though, so it’s a tricky balance.
Agree. AI generated is not bad if it's well directed and audited in a loop by a human in good detail. I won't discard a project because a tool has been used. That's extremism. I'll take a look at the project first.
Hope you’ll like it. At least concepts, I know htmx live or datastar are more mature so there’s no discussion about it.
Would you have any hints what to avoid for „next time”?
Should I just make this absurdly small and make much less polished approach even for this kind of project?
Honest question. Will try to work on anything you suggest <3
> and it's likely producing better output to keep a human in the loop rather than trying to solve the world independently and making multiple incorrect assumptions.
I was just discussing this with a co-worker yesterday. I would really like a model (or harness?) that worked with me instead of for me. Walk me through its choices and decisions, let me correct it and guide it along. I would be way more confident in it's output, I would be more familiar with the changes that are being made, and it would make reviewing the final code way easier since I was making the decisions along side it. I'm sure it would also reduce the "brainrot" we're all going to experience the more we hand work to these models.
does "Superpowers" exist outside of the Claude ecosystem? I feel like I've become hooked on this workflow - honestly I could take or leave the models ... it's the workflows and the way that they essentially create tightly focused loops over multiple sessions that I've becoming fairly dependent on.
Aside from the skills mentioned, I recently found that asking the model to create a simple HTML presentation to walk you through it's proposed design can do wonders. Fine tune your prompt to your liking (language style, what to include, what not, etc). Then, read that thing thoroughly, and keep asking questions and iterating on the plan until you fully understand what's about to be built, and are happy with it.
both contracts have over 10 years of experience with Elixir and one of them have written a widely used library. I think you are tad out of touch with the job market and with where agentic coding is right now.
Possibly, but I’m a senior software engineer that’s been writing Elixir for the last 5 years and has been experimenting with and using AI for the last 12-18 months.
Congrats on being one of the mythical developers that manages to get AI to write perfect code consistently!
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