https://github.com/chr15m/runprompt

I must say, the new smart bricks with all sorts of sensors(color, gyro, distance etc) triggers the inner child in me. I can’t wait to get them for my kiddo and teach him how that magic actually works beneath.

The regular LEGO at this points feels “just plastic” and I won’t feel bad offloading that purchase to AliExpress.

Comments URL: https://news.ycombinator.com/item?id=47320320

Points: 1

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If anyone has more AI tokens or spare time with mental energy to burn… go for it :-)

I am building my own assistant as an AI harness - that is definitely getting sandboxed to run only as a VM on my Mac.

I have this in my shell rc.

   # bun

   export BUN_INSTALL="$HOME/.bun"

   export PATH="$BUN_INSTALL/bin:$PATH"

   alias my-omp= "bun/Users/aravindhsampathkumar/ai_playground/oh-my-pi/packages/coding-agent/src/cli.ts"

1. git pull origin main

2. bun install

3. bun run build:native

every time I pull changes from upstream.

Until yesterday, this process was purely bliss - my own minimal custom system prompt, minimal AGENTS.md, and self curated skills.md. One thing I was wary of switching from pi to oh-my-pi was the use of Rust tools pi-native using NAPI. The last couple of days whatever changes I pulled from upstream is causing the models to get confused about which tool to use and how while editing/patching files. They are getting extremely annoyed - I see 11 iterations of a tool call to edit a damn file and the model then resorted to rewriting the whole file from memory, and we al know how that goes. This may not be a bug in oh-my-pi per se. My guess is that the agent developed its memory based on prior usage of the tools and my updating oh-my-pi brought changes in their usage. It might be okay if I could lose all agent memory and begin again, but I dont want to.

I'm going to be more diligent about pulling upstream changes from now on, and only do when I can afford a full session memory wipe.

Otherwise, the integrations with exa for search, LSP servers on local machine, syntax highlighting, steering prompts, custom tools (using trafilatura to fetch contents of any url as markdown, use calculator instead of making LLM do arithmetic) etc work like a charm. I haven't used the IPython integration nor do I plan to.

https://github.com/can1357/oh-my-pi

More of a batteries included version of pi.

Website: https://hobbyboard.aravindh.net

GitHub: https://github.com/aravindhsampath/hobbyboard

I want to do a show HN later this week.. but here might be a softer launchpad :-)

2. Access to my TODO list on Apple Notes and basically remind my ADHD brain that I ought to be doing something and not let it slip because it is uninteresting.

3. Have access to all models via API keys I configure and maintain a "research journal" of all the things I go to LLMs for - "research of bike that fits my needs" whatever and figure out if there needs to be a TODO about them and add if I say yes.

4. View my activity as a professional coach and nudge me into action "Hey you wanted to do this at work this year, but you haven't begun.. may be it is time you look at it Thursday at 3 PM?"

5. View my activity as a mental health coach and nudge me like "hey you're researching this, that and blah while X, Y and Z are pending. Want me to record the state of this research so you can get back to doing X, Y and Z?" or Just talk to me like a therapist would.

6. Be my spaghetti wall. When a new idea pops into my head, I send this secretary a message, and it ruminates over it like I would and matures that idea in a directory that I can review and obsess over later when there is time..

As you see, this is quite personal in nature, I dont want hosted LLMs to know me this deeply. It has to be a local model even if it is slow.

1. These llms are smart and dumb at the same time. They make a phenomenal contribution in such a short time and also do a really dumb change that no one asked for. They break working code in irrational ways. I’ve been asking them to add so many tests for all the functions I care about. This acts as a first guard rail when they trip over themselves. Excessive tests.

2. Having a compiler like Rust’s helps to catch all sorts of mines that the llms are happy to leave.

3. The LLMs don’t have a proper working memory. Their context is often cluttered. I find that curating that context (what is being done, what was tried, what is the technical goal, specific requests etc) in concise yet “relevant for the time” manner helps to get them to not mess up.

Perhaps important open source projects that choose to accept AI generated PRs can have such excessive test suites, and run the PRs through them first as a idiotic filter before manually reviewing what the change does.

I learned of a name to how I have been at 32 years of age, and got formally diagnosed at 39. The trigger was my 6 year old acting like I did when I was 6 and seeing how much of a struggle it is for him and others around him.

Been titrating medication and reworking how I approach my work and personal life the last few months.

The thing about constant stream of ideas, micro ideas, while life pulls in different directions- kids, partner, social life, home needs etc is the struggle I am working on to manage better.

It sounds like we could share notes. Would you be interested to communicate over a private message? I’m based in the Netherlands.

P.s. I’ve got nothing to sell, influence or creep about. Genuinely someone on the same boat and I thought it would be nice to communicate with someone who can relate.

If you’d prefer - my email is aravindh at fastmail com