sdesol

6 ms·

1.
by sdesol 29d ago
I think being able to A/B test price is invaluable for them. They can't cut prices by 50% and hike it again. By letting others slash the price, they can tell if it is worth it or not to do this officially.
2.
by sdesol 2mo ago
This is self promotional but I am working on making pi extremely enterprise ready with: https://github.com/gitsense/pi-brains/tree/staging The README is being worked on but the three videos should give you a
3.
by sdesol 2mo ago
The solution that I am working on is designed to leverage cheap LLMs (think MiMo, GLM, etc.) to build cheap context to reduce tokens, but most importantly to keep the context clean. https://github.com/gitsense/chat&#x2F
4.
by sdesol 2mo ago
> Claude Code has largely won individual developer mindshare and has been on top ever since it came out. Claude Code's success is not due to the agent but because the model is considered the best for programming and is very heavily
5.
by sdesol 2mo ago
> you can use /tree to go back before the compaction This is really a killer feature in my opinion. I'm currently working on pi brains extension that is designed to solve the compaction issue I have, which is, I don't know
6.
by sdesol 2mo ago
I am curious as to how this protect works. I am currently working on a pi brain extensions and one of the commands that I will support is: /brains inspect that will let you inspect a session and one of the features is the ability to re
7.
by sdesol 2mo ago
My extension for pi https://github.com/gitsense/pi-brains solves the too many skills problem and it can be adapted to work with any coding agent that supports hooks like Claude and Codex. You can find a simple example
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by sdesol 2mo ago
There are some additional things I need to implement first but I do have a hands on repo that you actually try at https://github.com/gitsense/gsc-rules-demos One of the rules shows how you can inject information when y
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by sdesol 2mo ago
> A lot of people want a use case. I think the issue is, on the surface this is very much a "watch this non-deterministic actvity" but I can see the value in it. This is self promotional but I am working on a "Brain"
10.
by sdesol 2mo ago
> I may try moving it all to Pi, but I wonder if I should learn how to better configure the things there. Honestly if the difference was marginal, I would move to Pi. I just tried layzpi and I had the agent write/compile a hello wor
11.
by sdesol 2mo ago
What was lacking? This is self promotional but I am working on https://github.com/gitsense/pi-brains which is designed around the Pi philosophy of less is better by focusing on ondemand context/guidance. I won&#x2
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by sdesol 2mo ago
I think that would be implied by "how did you arrive at the code". I think the conversation will revove around how did you "guide" things.
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by sdesol 2mo ago
> One of the most annoying things I've seen AI do is accidentally pull in old requirements and start building off of them. This is actually the reason for me wanting to create what I call "Brain checkpoints". After chatti
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by sdesol 2mo ago
I think it makes no sense to share the conversation but I do think developers will be required to provide lessons, notes and checkpoints in the conversation. What I think will happen is you will be required to run the conversation through a
15.
by sdesol 2mo ago
> Nobody wonders out loud how a senior developer arrives at the result he does without an AI; they care that his deliverable is high quality and meets whatever standard/requirement exists. I think the issue that many may not want to
16.
by sdesol 2mo ago
> Has anyone tried teaching the agents to use jj or gitbutler-cli to do their ideas of lightweight branches? This is very trivial if your coding agents supports hooks like Pi. I have demo repo that goes over how rules work at https:&#x2
17.
by sdesol 2mo ago
This is what I am doing with my pi-brains extension for pi https://github.com/gitsense/pi-brains I will make another update by the end of this week that contains what I call "brain checkpoints" that will make
18.
by sdesol 2mo ago
> now they can generate one in a few minutes and send it out for review. I think we will very soon move to a prove to me you've read it protocol and/or introduce speed bumps to slow things down.
19.
by sdesol 2mo ago
Would usuability (for what herdr is optimized for) not be the bigger use case for users? I never heard of this project but in 5 minutes I got the features that I wanted without having to introduce muscle memory. I just wanted a dead simple
20.
by sdesol 2mo ago
It is not about me liking it or not. The word threaten comes with implications. This means they acted in hostile manner based on your words.
21.
by sdesol 2mo ago
> got essentially threatened by leadership for not using AI. This sounds made up or your workplace is rather odd to say the least. Maybe english isn't your first language and "threatened" is not the correct word?
22.
by sdesol 2mo ago
> I can't imagine what the point of autogenerating agent context could be I have a fork of the OpenAI Codex repo at https://github.com/gitsense/smart-codex that shows why you may want to autogenerate agent cont
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by sdesol 2mo ago
Honestly this is where I would have fable generate a checklist and you just monitor opus to ensure it is going through the checklist. I think ignore is often the result of a context that is not focused enough.
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by sdesol 2mo ago
Why aren't the teams using shared checks? Are the codes in different repos?
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by sdesol 2mo ago
> I even have "don't overrule me without asking" in my global AGENTS.md, and it simply doesn't do that. You really need to look into hooks based on your coding agent. This is very much a solved problem as I demonstrat
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by sdesol 2mo ago
Better a round trip than bad/incorrect results. Also, the cache should kick in so the cost will be minimal.
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by sdesol 2mo ago
> they still need tool-trial-and-error dance after injecting them? It honestly depends on the model. For my pi-brains extension for pi https://github.com/gitsense/pi-brains I've found after the first hook injec
28.
by sdesol 2mo ago
The article doesn't go into how they managed the AI context when implementing things but I would not be surprised if it was done in a methodical way, 80% - 90% of the test could have passed.
29.
by sdesol 3mo ago
This is a hard problem, but one worth solving, I think, since it means less tokens and better AI reasoning. I believe LLMs are good enough that, if given the right context, it can very much solve almost all tasks. If this works, it means we
30.
by sdesol 3mo ago
> So I want to say there's still a lot of value in context engineering though it seems to diminish with each model release I can't see how it would diminish unless you are literally working on public domain stuff. Unless stuffi

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