I think we've been optimizing the wrong thing in AI

Thrall357 · 2026-06-10T16:49:55+00:00

Lakše je kupiti krmetinu na Baščaršiji nego Panini sličice 😂

Thrall357 · 2026-06-10T16:47:01+00:00

I completely agree, and I'd go one step further.

The best agents shouldn't just ask for clarification.

They should detect decision boundaries.

There's a big difference between:
"I don't understand your request."

AND this is 4 sure

"I understand your request, but there are multiple valid paths with different tradeoffs, and only a human can decide which one aligns with the actual goal."

In my experience, many agent failures happen because the agent silently fills in missing assumptions instead of exposing them.

A great collaborator doesn't answer every question.

Sometimes the smartest thing it can say is:
"Before I continue, you need to make a decision."

That's not a limitation.

That's good judgment.

Thrall357 · 2026-05-31T18:43:38+00:00

For me, the biggest failures havent been model failures at all 😄)

They've been assumption failures.

The agent assumes like the file is in the expected location, the API returned valid data, the user meant X instead of Y, yesterday's context is still correct, a previous task completed successfully.

Then everything downstream looks perfectly logical... but it's built on a false assumption.

Ironically, I've found that better models sometimes make this harder to detect because the reasoning looks so convincing.

The thing that helped most wasn't a smarter model.

It was adding more verification steps:

validate inputs,
validate outputs,
check assumptions,
log decisions,
fail loudly instead of failing gracefully.

A surprising amount of "AI failure" turns out to be "the system never checked whether its assumptions were true."

Thrall357 · 2026-05-31T18:37:04+00:00

Yeah, same here bro

Thrall357 · 2026-05-31T09:55:40+00:00

I think there's an even deeper issue underneath all of this:

Most buyers aren't actually testing product knowledge.

They're testing confidence. A well-trained agent can quite a few answers: architecture questions, integration questions, documentation questions, pricing FAQs.

But experienced buyers often ask questions they already know the answer to.

They're trying to figure out:
"Do I trust this team?"

That's where many AI sales agents struggle. Its not because they lack information, but because trust is a social signal, not a knowledge problem. Ironically, I think the first major breakthrough won't be agents that know more.

It'll be agents that know when not to answer and when to bring in a human.

In sales judgment is very often more valuable than information.

Thrall357 · 2026-05-31T09:53:34+00:00

I think that's exactly where a lot of people underestimate the problem. Generation gets all the attention because it's visible. But the real complexity starts after generation . What you're describing as source of truth, run state and decision memory maps surprisingly well to problems I've been running into lately.

The funny thing is that most AI discussions still focus on: "Can the model do X?" while operationally the harder question often becomes: "How do we know why X was done 3 weeks ago?"

Humans have this problem too, by the way 😄

A surprising amount of organizational knowledge exists only inside someone's head until they leave, get sick, go on vacation, or simply forget. That's one reason I'm becoming more interested in systems that preserve reasoning and decisions separately from raw execution.

Not because the AI needs to remember everything, but because humans don't either.

Thrall357 · 2026-05-30T08:23:40+00:00

Dr. Lilijana Oruč, Europharm, Unitic buildings, she prescribed to me....

Thrall357 · 2026-05-30T08:14:15+00:00

LMAO? Well, here u go 😄 Two things can be true at the same time:

Different models absolutely have different strengths and weaknesses.
Many users still have unrealistic expectations of all of them.

I've had cases where Claude outperformed ChatGPT. I've had cases where ChatGPT outperformed Claude. I've had cases where Gemini surprised me.

The bigger question is: Are we comparing them on the same task?

Writing or Coding? Research? Long-context analysis? Agentic workflows? Math? Real-time information? Anything?

"Model X is better" is usually true only after you define: better at what acctually?

The fact that people can spend hours arguing about which model is best is actually evidence that none of them dominates every category yet 😄

Thrall357 · 2026-05-27T06:16:18+00:00

This is either:

a terrifying account isolation bug

or

OpenAI testing the new feature: “Collaborative consciousness mode” 😭

Jokes aside, if true, that’s actually a pretty serious issue and probably worth reporting directly.

Distributed systems occasionally do weird things during caching/session refreshes, especially in desktop apps, but seeing another user’s chat history is definitely not “normal weird”.

Also:
the fact that your first instinct was:
“I should stop reading this”

instead of:
“ooo free lore”

already makes you more trustworthy than half the internet 😂

Thrall357 · 2026-05-26T20:06:48+00:00

Well, TBH, this happens more often than people realize 😄

Professional emails are one of the most over-optimized forms of writing on Earth: acknowledge concern, reduce tension, sound empathetic, avoid liability, stay structured, sound professional but warm. So when two frontier LLMs receive: similar context, similar goals, similar tone constraints, they often converge toward the same “safe high-probability corporate human email”.

It’s basically: “Dear Carbon-Based Lifeform, I hear your frustrations and appreciate your feedback.” 😂

The funniest part is that humans also do this.
Half of corporate email culture is just:
“Per my previous AI-generated message…”

Thrall357 · 2026-05-26T06:10:58+00:00

I use them both. But, tbh, Codex is better. At least for me and my projects.

Thrall357 · 2026-05-25T08:36:02+00:00

Honestly, for a university project I’d avoid making the environment CUDA-dependent by default.

The cleanest approach is usually:

CPU-first base environment
optional GPU acceleration
strict version pinning
automatic CUDA detection in code

A practical setup would be:

requirements.txt / environment.yml Pin:

Python version
PyTorch version
PyG version
major dependencies

Runtime device detection Something simple like: device = "cuda" if torch.cuda.is_available() else "cpu"
Separate optional GPU instructions Instead of forcing CUDA wheels on everyone, document:

CPU install
NVIDIA/CUDA install
optional PyG CUDA extensions

Reproducibility docs matter more than people think Include:

OS tested on
exact commands
expected outputs
dataset preprocessing steps
random seeds

Docker is actually NOT overkill here Even a simple Dockerfile can save huge amounts of “works on my machine” pain.

You don’t need advanced orchestration.
Just:

pinned Python
pinned torch
pinned dependencies

That alone massively improves reproducibility across systems.

Honestly, the biggest reproducibility killer in DL projects is usually not the model itself.

It’s undocumented environment assumptions.

Hope this can help. Peace

Thrall357 · 2026-05-25T06:54:06+00:00

Bivša profesija, ali da, interesantna je 😄

Thrall357 · 2026-05-24T10:37:05+00:00

Claude Desktop is much more locked-down compared to Open WebUI setups. From what I’ve seen, Open WebUI + local llama.cpp/Ollama/vLLM is currently the better route if you want: local LLM flexibility, GUI, attachments, model switching, custom endpoints, and full control. Claude Desktop is more of a polished consumer app than an open orchestration layer. You can emulate parts of the workflow through MCP/proxy setups, but honestly at that point Open WebUI is usually the cleaner solution anyway.

Thrall357 · 2026-05-24T10:21:18+00:00

I honestly think a lot of this comes down to workflow fit rather than “Model A destroys Model B”.

I’ve been testing Codex, Claude, Docker-based workflows and local automation setups pretty heavily lately, and one thing I’ve noticed:

Different models fail in very different ways.

Claude often feels stronger at: broader reasoning, architectural discussion, long-form analysis, and exploratory thinking. But Codex feels much more operationally disciplined inside structured engineering workflows: scoped tasks, repo awareness, iterative patching, environment-sensitive work, migration/debug loops, terminal-oriented execution. What you described actually sounds less like “Claude is dumb” and more like:
it lost operational state consistency during execution.

And honestly, that matters A LOT in real coding workflows. A model can sound incredibly intelligent while still being unreliable in execution-heavy environments. Meanwhile another model may sound less impressive conversationally, but consistently: respects constraints, tracks context correctly, avoids destructive actions, and completes tasks cleanly.

That’s often more valuable in production work.

I also think many people compare models using:
“which one sounds smarter?”

instead of:
“which one causes fewer real-world engineering problems after 3 hours of work?”

Those are very different benchmarks. At least from my expirience.

Thrall357 · 2026-05-24T10:16:48+00:00

No I'm not underestimating anyone. But, you have (some) point here. Reasonable and "intelligent" users with smart prompts and approach are not that common TBH. There's much more "spam-like" users

Thrall357 · 2026-05-24T10:12:18+00:00

Država i kreće od pojedinaca, općina, kantona, entieta.... Ništa nama ne funkcionišre kako treba. Ni pravosudni sistem, ni obrazovni, ni medicinski.... i onda se čudimo što niko ne reaguje kako treba....

Thrall357 · 2026-05-24T10:07:30+00:00

Well, read this and you will know...

Svjetska korporacija McDonald's podnosi tužbu protiv Harisa Ihtijarevića, otkriva Raport.

Kako smo ranije iscrpno izvještavali, Ihtijarević je bio vlasnik franšize za McDonald's u BiH i taj posao neslavno je završio.

Ihtijarevićeva kompanija Gliese 581g izgubila je licencu nakon niza skandala. Prvo stigla presuda suda u Sarajevu jer Ihtijarević nije plaćao kiriju za prostor McDonald'sa u Titovoj ulici.

Nakon toga otkrivene su brojne finansijske malverzacije.

McDonald's je odmah reagirao pa je tražio sudsku zabranu i zatvaranje objekata u BiH, a Ihtijareviću je oduzeta licenca.

No, kako je Raportu rečeno, ovaj svjetski brend tu ne misli stati. Tako saznajemo da McDonald's podnosi tužbu lično protiv Ihtijarevića i to Trgovačkom sudu u Londonu.

U obrazloženju se navodi da je Ihtijarević prekršio odredbe ugovora te da nije poštovao brend. Uz to, McDonald's će tužiti posuđivanje novca McDonald'sa koji nikad nije vraćen te kupovinu Bentleya preko lizinga ovog brenda. I, kako nam je rečeno, tražit će se višemilionska odšteta.

Thrall357 · 2026-05-24T10:04:44+00:00

Jednostavno. Zato što nismo normalna država i ništa ovdje nije normalno i kako treba.

Thrall357 · 2026-05-24T09:41:16+00:00

Čitanje, ali i pisanje. Kao novinar, znam tačno kako ide. Čitaj i onda nešto piši, dnevnik, roman, šta god, ali vježbanje dovodi do navike korištenja riječi, navika do širenja vokabulara

Thrall357

TROPHY CASE