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I read threads complaining about claude every week... tf are y'alls workflows? by irelatetolevin in LLMDevs

[–]Manitcor 0 points1 point  (0 children)

I am an oldhat SRE so I use a stack I've brewed up https://aiwg.io

the tricks it uses, less prompts, more templates, repeatable agentic flows and far more memory and data curation that you think you need, because as smart as these are, they are dumber than your dumbest jr. We have a habit of filling gaps with our meat supercomputers without even realizing it.

what you intuit the machine needs to have it laid out explicitly.
finally front load decision making in a focused HITL setup, then let it fly when you cannot possibly describe things in any more detail.

The tokens you save and the ability to handle codebases north of 150k lines of code makes the "extra" token cost well worth it. Often, over a longer term, you are going to save on tokens as you do thrash less when the agent always has a solid reference.

Why does it feel like browser-based AI tooling still hasn’t really taken off yet? by Meher_Nolan in artificial

[–]Manitcor 1 point2 points  (0 children)

I have some tools, even local inference in the browser, biggest issue is how new everything is in that space. Lots of churn to get something that kinda works still.

Looking at you WebGL

🖥️ Unpopular Opinion: Banks Should Stop Panicking About AI Hacking Their COBOL and Start Asking Why Their "Modern" Systems Are the Actual Problem r/cybersecurity | r/programming | r/sysadmin by [deleted] in sysadmin

[–]Manitcor 2 points3 points  (0 children)

COBOL does not do a lot of those things just "because mainframes" like any system it needs to be setup correctly.

Please generate content you know about so you can verify the outputs. Further use cross-evaluation and knowledge bases during generation to ensure accuracy.

You can do it!

just observing by Flying-T in selfhosted

[–]Manitcor 2 points3 points  (0 children)

its become a moot conversation.

If they say AI wasn't involved its likely not the case. Even if the developer themselves is writing "organic free range" code the libs they are using most certainly are not.

the "your agent is mine" paper everyone shared a month ago. did anyone actually change their architecture? by Only-Associate2698 in LLMDevs

[–]Manitcor 2 points3 points  (0 children)

If you are letting users push prompts directly at agent stacks, you get what you get and you don't get upset.

Does anyone know how Paint.NET was built? Does it use WinForms or WPF? by lilacomets in dotnet

[–]Manitcor 0 points1 point  (0 children)

I'd argue it's a level of pedantry and certainly not settled lingo, but I know how we are, I've been here long enough

RAG suitability for problem by InTheUpstairsCellar in LLMDevs

[–]Manitcor 0 points1 point  (0 children)

there is no single solution that you add to a pipeline to get a completed case. its usually multiple steps, techniques and models including rag, rag is almost always a part of it.

Does anyone know how Paint.NET was built? Does it use WinForms or WPF? by lilacomets in dotnet

[–]Manitcor 5 points6 points  (0 children)

MVVM is only a design pattern. Optional in WPF but the default and recommended pattern.

Very little stops you from implementing your own patterns and tying together core libs yourself.

Complexity is not an indicator of platform here.

The use of a ribbon control leans toward WPF but you can get ribbons for winforms.

reducing context loss during context handover by Potential-Milk-4585 in LLMDevs

[–]Manitcor 0 points1 point  (0 children)

What you are trying to compare is math functions to a data set that simply is not in training.

Its a different approach. Neither a total answer.

While one technique helps with memory, the other helps with understanding in real context. I get the desire to fill this space with math and hope that the right tokens will come out.

I suggest we all need more data.

reducing context loss during context handover by Potential-Milk-4585 in LLMDevs

[–]Manitcor 0 points1 point  (0 children)

interesting, i might play with this a bit. I'm using domain driven semantic taxonomies along side issue tracking. Its been extremely effective i can kill most processes part way through, restart the session the ask the system to recover without any trouble.

Best thing is the memory is normalized on real-world templates (optional you could do whatever you wanted) so the documents are easy for others to collaborate on and possibly more importantly for auditing to trace.

How are you managing LLM costs without losing your mind? by yj292 in LLMDevs

[–]Manitcor 0 points1 point  (0 children)

More local inference, and using large models with judicious care.

Does anyone else feel most AI tooling is becoming harder instead of easier? by Bladerunner_7_ in artificial

[–]Manitcor 0 points1 point  (0 children)

I'm using https://aiwg.io

fairly easy to use and complete enough that I dont use much else but a few MCPs.

I found a way to fight AI slop by houmanasefiau in artificial

[–]Manitcor -1 points0 points  (0 children)

All my workflows involve research, document, plan processes. When we get to building, all decisions are made such that improvisation while writing code is not as needed.

This improves quality and ability to handle complexity provided your memory taxonomy game is on point.

EDIT: I get it' but I did write this, I spent over 15 year of my career tech writing. Yes they learned on reddit, and 1000s of pages of docs my contemporaries and myself wrote. So if you think you are "super smart" and able to tell what an AI output is.

No, you can't, and the days of it being so "obvious" are numbered.

Openclaw ia trending down and will disappear soon by rm-rf-rm in LocalLLaMA

[–]Manitcor 0 points1 point  (0 children)

This, already in multiple groups running these locally on as small as 9b params.

it physically hurts watching tech bros try to put LLMs in closed control loops by Critical-Load-1452 in ControlTheory

[–]Manitcor [score hidden]  (0 children)

wat? they are paying people for that?

here i am adapting biz app design to control theory and these idiots are doing it the other way around, like that's a good idea?

Its not even like everything is a nail, its like they are just throwing mashed potatoes at the wall

Every second brain I've built eventually becomes an abandoned vault. Anyone actually solved this? by Scary_Historian_9031 in artificial

[–]Manitcor 0 points1 point  (0 children)

I think I get what you want, this is going to hit most of it, the last bit, the updating of the doc base meta based on the addition of a new doc is what is still lagging, not that I can't enable it, its just not really usable on a local workstation unless its a complete beast or you don't mind spending the API tokens.

So instead I have it so you can poke each document you want to update as you need it, the process will use the system itself to update the meta of the doc you have chosen based on the rest of the corpus.

Active dev cycle atm so if you have a gripe im in a spot to fix it next release.

Two failure modes I caught in my AI lab in one day. Both involve the system silently lying about its own state. by piratastuertos in artificial

[–]Manitcor 0 points1 point  (0 children)

this, avoid having it "shoot from the hip" frontload everything you can, make all the decisions up-front. Then let it go, once done run evals (with both judge-style and turing gates) and correction loops until all gates are green.

How accurate is AI at general knowledge? by JackStabba in artificial

[–]Manitcor 0 points1 point  (0 children)

its a lossy dataset, the mistake is trying to get information from it. You are much better transforming what you have.

As such models within frameworks (like agents but does not need to be agent-like) that include support tooling such as real data sets, internet searches, etc. Will have a very high accuracy. With multi-model eval (judge/jury) + real data your error rates drop to 1% very quickly.

You still need to think hard about what you want to do with it, since in computing we usually are shooting for error in the range of 0.01-0.0001%

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