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Dzugaru commented on Ask HN: Any real OpenClaw (Clawd Bot/Molt Bot) users? What's your experience?    · Posted by u/cvhc
bobjordan · a month ago
I spec out everything in excruciating detail with spec docs. Then I actually read them. Finally, we create granular tasks called "beads" (see https://github.com/steveyegge/beads). The beads allows us to create epics/tasks/subtasks and associated dependency structure down to a granular bead, and then the agents pull a "bead" to implement. So, mostly we're either creating spec docs and creating beads or implementing, quality checking, and testing the code created from an agent implementing a bead. I can say this produces better code than I could write after 10yrs of focused daily coding myself. However, I don't think "vibe coders" that have never truly learned to code, have any realistic chance of creating decent code in a large complex code base that requires a complex backend schema to be built. They can only build relatively trivial apps. But, I do believe what I am building is as solid as if I had a millions of dollars of staff doing it with me.
Dzugaru · a month ago
But how is that less work and allows you to do that in Disneyland with your kids? For me, personally, there is little difference between "speccing out everything in excruciating detail in spec docs" and "writing actual implementation in high-level code". Speccing in detail requires deep thought, whiteboard, experimentation etc. All of this cannot be done in Disneyland, and no AI can do this at good level (that's why you "spec out everything in detail", create "beads" and so on?)
Dzugaru commented on Vibe Code Warning – A personal casestudy   github.com/jackdoe/pico2-... · Posted by u/jackdoe
csallen · 4 months ago
I'm not sure. I think it's asymmetric: high upside potential, but low downside.

Because when the AI isn't cutting it, you always have the option to pull the plug and just do it manually. So the downside is bounded. In that way it's similar the Mitch Hedberg joke: "I like an escalator, because an escalator can never break. It can only become stairs."

The absolute worse-case scenario is situations where you think the AI is going to figure it out, so keep prompting it, far past the time when you should've changed your approach or gfiven up and done it manually.

Dzugaru · 4 months ago
This is so far from an absolute worst-case scenario.

You could have a codebase subtly broken on so many levels that you cannot fix it without starting from scratch - losing months.

You could slowly lose your ability to think and judge.

Dzugaru commented on A high schooler writes about AI tools in the classroom   theatlantic.com/technolog... · Posted by u/dougb5
greenspam · 6 months ago
Imagine back in the days when calculators were just invented. An 8 year old kid might have the similar complain: “my classmate finished a 4 digits number multiplication problem in 5 seconds which generally took 1mins.” People might say, in the long term, the kid who cheated would be less proficient in arithmetic, which turned out to be true. But when you think about it, it seems not the end of the world when most high schooler in US cannot do complicated arithmetic quickly and accurately without a calculator.
Dzugaru · 6 months ago
I have a feeling this is somehow different. The tool is broad enough, that I don't have to think myself in a wide variety of tasks, not just one. Which hurts my intelligence way more.
Dzugaru commented on OpenAI Progress   progress.openai.com... · Posted by u/vinhnx
Joeri · 7 months ago
LLMs are not people, but they are still minds, and to deny even that seems willfully luddite.

While they are generating tokens they have a state, and that state is recursively fed back through the network, and what is being fed back operates not just at the level of snippets of text but also of semantic concepts. So while it occurs in brief flashes I would argue they have mental state and they have thoughts. If we built an LLM that was generating tokens non-stop and could have user input mixed into the network input, it would not be a dramatic departure of today’s architecture.

It also clearly has goals, expressed in the RLHF tuning and the prompt. I call those goals because they directly determine its output, and I don’t know what a goal is other than the driving force behind a mind’s outputs. Base model training teaches it patterns, finetuning and prompt teaches it how to apply those patterns and gives it goals.

I don’t know what it would mean for a piece of software to have feelings or concerns or emotions, so I cannot say what the essential quality is that LLMs miss for that. Consider this thought exercise: if we were to ever do an upload of a human mind, and it was executing on silicon, would they not be experiencing feelings because their thoughts are provably a deterministic calculation?

I don’t believe in souls, or at the very least I think they are a tall claim with insufficient evidence. In my view, neurons in the human brain are ultimately very simple deterministic calculating machines, and yet the full richness of human thought is generated from them because of chaotic complexity. For me, all human thought is pattern matching. The argument that LLMs cannot be minds because they only do pattern matching … I don’t know what to make of that. But then I also don’t know what to make of free will, so really what do I know?

Dzugaru · 7 months ago
There is no hidden state in a recurrent nets sense. Each new token just has all the previous tokens and that’s it.
Dzugaru commented on Gemini with Deep Think achieves gold-medal standard at the IMO   deepmind.google/discover/... · Posted by u/meetpateltech
Dzugaru · 8 months ago
Most critical piece of information I couldn’t find is - how many shot was this?

Could it understand the solution is correct by itself (one-shot)? Or did it have just great math intuition and knowledge? How the solutions were validated if it was 10-100 shot?

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Dzugaru commented on Measuring the impact of AI on experienced open-source developer productivity   metr.org/blog/2025-07-10-... · Posted by u/dheerajvs
furyofantares · 8 months ago
I'm specifically talking about greenfield work. I do a lot of game prototypes, it definitely does that at the very beginning.
Dzugaru · 8 months ago
This is really interesting, because I do gamejams from time to time - and I try every time to make it work, but I'm still quite a lot faster doing stuff myself.

This is visible under extreme time pressure of producing a working game in 72 hours (our team scores consistenly top 100 in Ludum Dare which is a somewhat high standard).

We use a popular Unity game engine all LLMs have wealth of experience (as in game development in general), but the output is 80% so strangely "almost correct but not usable" that I cannot take the luxury of letting it figure it out, and use it as fancy autocomplete. And I also still check docs and Stackoverflow-style forums a lot, because of stuff it plainly mades up.

One of the reasons is maybe our game mechanics often is a bit off the beaten road, though the last game we made was literally a platformer with rope physics (LLM could not produce a good idea how to make stable and simple rope physics under our constraints codeable in 3 hours time).

Dzugaru commented on Seven replies to the viral Apple reasoning paper and why they fall short   garymarcus.substack.com/p... · Posted by u/spwestwood
Dzugaru · 9 months ago
> just as humans shouldn’t serve as calculators

But they definitely could and were [0]. You just employ multiple, and cross check - with the ability of every single one to also double check and correct errors.

LLMs cannot double check, and multiples won't really help (I suspect ultimately for the same reason - exponential multiplication of errors [1])

[0] https://en.wikipedia.org/wiki/Computer_(occupation)

[1] https://www.tobyord.com/writing/half-life

Dzugaru commented on What was Radiant AI, anyway?   blog.paavo.me/radiant-ai/... · Posted by u/paavohtl
ednite · 9 months ago
Interesting read. Got me thinking, I’d love to see what happens when modern AI meets open world simulation. Not just prettier graphics, but actual reasoning NPCs. Imagine arguing with a World of Warcraft innkeeper about the price of ale. Priceless.
Dzugaru · 9 months ago
Not possible, because can't be guardrailed with 100% accuracy. You'll ask it something outside of the Warcraft world (e.g. US politics), and it'll happily oblige. I imagine NPCs will generate really weird immersion breaking stuff even if you cannot freeform interact with them anyway.

Not to mention the current token cost.

Dzugaru commented on AI predicts earthquakes with unprecedented accuracy   scitechdaily.com/artifici... · Posted by u/xrd
langcss · 2 years ago
Leave. If you live in such an area it would be a way of life. You probably have a spare toothbrush at someone else's house already. Unless you have a bunker or something that is considered safe.
Dzugaru · 2 years ago
Used to live near Japan, in a 5-story concrete building. We had so many earthquakes, the things were getting thrown off the shelves multiple times a year. There is nowhere to leave for a week. And there is a very slim chance anything would collapse, because the buildings are specifically built to withstand up to around 9 richter.

u/Dzugaru

KarmaCake day515June 19, 2016View Original