I've recently lazied out big time on a company project going down a similar rabbit hole. After having a burnout episode and dealing with sole caregiver woes in the family for the past year, I've had less and less energy to piece together intense, correct thought sequences at work. As such I've taken to delegating substantial parts architecture and discovery to multiagent workflows that always refer back to a wiki-lik…
LLM Wiki – example of an "idea file"
81–90 of 109 posts
Re: LLM Wiki – example of an "idea file"
#82Earlier quoted context omitted.
> He really wants to shine, but how is this different than claude memory or skills? It isn't different. This just tries to reinvent the wheel that all mainstream coding assistants have been providing for over a year. Even ChatGPT rolled out chat memory in their free tier.
The difference obviously being, his way you own the memories; in what's currently deployed, it's the platform that owns them.
Re: LLM Wiki – example of an "idea file"
#83Re: LLM Wiki – example of an "idea file"
#84Earlier quoted context omitted.
Don't even try, after vibe coding, people seem to be adopting vibe thinking. "Model Collapse sounds cool, I'm gonna use it without looking up"
Vibe thinking... that's an interesting premise. I'll have to build up my new llm-wiki before I'll know what to think about "vibe thinking."
I'll spare you most of the slop but.. "The Case That I Am Abulafia: The parallel is uncomfortable and precise. [...]"
Yeah... It's fun though.
Re: LLM Wiki – example of an "idea file"
#85Re: LLM Wiki – example of an "idea file"
#86Isn’t this just kicking the can down the road? > but the LLM is rediscovering knowledge from scratch on every question Unless the wiki stays fully in context now the LLM hast to re-read the wiki instead of re-reading the source files. Also this will introduce and accumulate subtle errors as we start to regurgitate 2nd-order information. I totally get the idea but I think next gen models with 10M context and/or 1000tp…
I use a home baked system based on obsidian that is essentially just “obsidian but with structured format on top with schemas” and I deploy this in multiple places with ranges of end users. It is more valuable than you think. The intermediary layer is great for capturing intent of design and determining when implementation diverges from that. There will always be a divergence from the intent of a system and how it ac…
Re: LLM Wiki – example of an "idea file"
#87Re: LLM Wiki – example of an "idea file"
#88I've recently lazied out big time on a company project going down a similar rabbit hole. After having a burnout episode and dealing with sole caregiver woes in the family for the past year, I've had less and less energy to piece together intense, correct thought sequences at work. As such I've taken to delegating substantial parts architecture and discovery to multiagent workflows that always refer back to a wiki-lik…
> I miss thinking harder Me too, and I wonder where this will take us; I worry about losing the ability to think hard.
Re: LLM Wiki – example of an "idea file"
#89This list is also part of my own contender in this race: https://zby.github.io/commonplace/ - my own LLM operated knowledge base (this is the html rendering of that KB - there is also the github repo linked there).
The main feature is that I use it to build a theory about such systems - and the neat trick is that llms can read this theory and implement it so the very theory works as an LLM runtime too.
It works for me - but it has some rough edges still - so I guess it is not for everyone.
Re: LLM Wiki – example of an "idea file"
#90I would be interested in trying to make the models go into more of a research mode and organize their knowledge inside it, but I've found this turns into something like LLM soup.
For coding projects, the best experience I have had is clear requirements and a lot of refinement followed through with well documented code and modules. And only a few big 'memories' to keep the overall vision in scope. Once I go beyond that, the impact goes down a lot, and the models seem to make more mistakes than I would expect.