Eva Locusteanu

IT and AI consultant. Tweeting about AI, movies, pop culture, beautiful buildings, memes, sometimes politics. All opinions my own. 🇷🇴🇳🇱

[Eva Locusteanu @Eva27738146]

Turns out Data is the new sugar, not the new oil. Great article about “junk info” and how to fight it! https://t.co/UtLsiZ5U0F

[Indra @IndraVahan]

my job used to be turning raw data into actionable insights then AI happened and now it turns raw data into questionable insights

[“paula” @paularambles]

bucharest is actually doing pretty well tyvm

[Dale Chu @Dale_Chu]

“The students who cannot read a 20-page article today are the voters who will not be able to read a bill, or the jurors who cannot follow a closing argument, tomorrow.”

[Ethan Mollick @emollick]

I find debates over whether companies find AI useful to be odd at this point

I talk to leadership teams at lots of big firms, and it is pretty universal that they are getting obvious and real value. The challenges now are going from individual uses to firm-level & how to scale.

[Sr. Theresa Aletheia @pursuedbytruth]

This line 😭— “For an algorithm, an error is a flaw to be corrected; for a person, however, an error can be a catalyst for profound change.” — Pope Leo, #Magnificahumanitas

[Ben Dickson @bendee983]

There is no free lunch in AI (as in any other technology).

People who have been used to writing code manually know that a lot of learning comes from doing the actual work by yourself. But you’re also making progress at the speed of the humans mind.

Delegating the coding (and code review) to an LLM or AI agent gives you higher productivity at the expense of depriving you of the learning experience. (People who learn coding with AI agents from the get go won’t feel this dilemma.)

(This doesn’t account for the argument Ive been constantly making that blindly trusting an LLM’s output is a recipe for disaster.)

But this has been the story of technological progress through and through. You’re always giving away a bit of the past for higher productivity.

[Iyobosa Evbayowieru @theiyobosa]

@SuvanshSanjeev Where will the next set of Seniors come from?

[Skindie @skindie___]

If Claude code is so good why can’t it open the Strait of Hormuz

[hunter @3gpmh]

micro dosing hell by staying informed and educated

[Eva Locusteanu @Eva27738146]

💛

[kira 👾 @kirawontmiss]

"we reject the idea that the world can solve its problems through bombs."

[sarah @sahouraxo]

George Galloway:

The massacre of 167 girls, aged 7 to 12, at an elementary school in Iran is the greatest atrocity committed by the United States since the Vietnam War.

It is the largest mass killing of schoolgirls ever recorded in world history.

Yet no one is talking about it

[catherine ʕ•ᴥ•ʔ-☆ @wilhelmscreamin]

anyone who uses LLMs less than me is a stubborn luddite missing out on so much potential uplift. anyone who uses LLMs more than me has AI psychosis

[Yoel Nisanov @YoelNisanov]

@tunguz New CV format:

Skills:
– Can describe what I want in plain English.

[Alex Veremeyenko @alex_verem]

Anthropic's own researchers just proved that using AI to learn new skills makes you 17% worse at them.

and the part nobody's reading is more important than the headline.

the paper is called "How AI Impacts Skill Formation." randomized experiment. 52 professional developers. real coding tasks with a Python library none of them had used before. half got an AI assistant. half didn't.

the AI group scored 17% lower on the skills evaluation.

Cohen's d of 0.738, p=0.010.

that's a real effect.

and here's what makes it sting: the AI group wasn't even faster.

no significant speed improvement. they learned less AND didn't save time.

but the viral framing of "AI bad for learning" misses what actually matters in this paper.

the researchers watched screen recordings of every single participant.

they identified 6 distinct patterns of how people use AI when learning something new.

3 of those patterns preserved learning. 3 destroyed it.

the gap between them is enormous. participants who only asked AI conceptual questions scored 86% on the evaluation.

participants who delegated everything to AI scored 24%.

same tool. same task. same time limit.

the difference was cognitive engagement.

the highest-scoring AI users actually outperformed some of the no-AI group. they asked "why does this work" instead of "write this for me."

they generated code then asked follow-up questions to understand it. they used AI as a thinking partner, not a replacement for thinking.

the lowest-scoring group did what most people do under deadline pressure: pasted the prompt, copied the output, moved on. they finished fastest.

they learned almost nothing.

and here's the finding that should concern every engineering manager alive: the biggest score gap was on debugging questions.

the skill you need most when supervising AI-generated code is the exact skill that atrophies fastest when you let AI do the work.

the control group made more errors during the task. they hit bugs.

they struggled with async concepts. they got frustrated. and that struggle is precisely what built their understanding.

errors aren't obstacles to learning.
they ARE learning.

removing them with AI removes the mechanism that creates competence.

participants in the AI group literally said afterward they wished they'd "paid more attention" and felt "lazy."

one wrote "there are still a lot of gaps in my understanding."

they could feel the hollowness of having completed something without understanding it.

that's not a productivity win. that's debt.

this paper isn't an argument against using AI. it's an argument against using AI unconsciously.

Anthropic publishing research showing their own product can inhibit skill formation is the kind of intellectual honesty the industry needs more of.

the practical takeaway is simple: if you're learning something new, use AI to ask questions, not to skip the work.

the struggle is the product.

[ThePrimeagen @ThePrimeagen]

very cool study

very happy to see anthropic measuring the negatives as well. Honestly good for them

[Eva Locusteanu @Eva27738146]

‘When's the last time you talked to a user?’ w

[Ian Tracey @ian_dot_so]

https://t.co/6aIhogx6xt

[Balaji @balajis]

Much of any digital job is now preparing context for AI models.

Organizing files in folders, naming everything correctly, introducing things in the right order, and only then asking the AI to do something in clear written English.

[𝔗𝔯𝔲𝔱𝔥 𝔐𝔞𝔱𝔱𝔢𝔯𝔰 @politicsusa46]

For anyone who would like to hear Mark Carney’s outstanding Davos speech in full here it is. This is what true global leadership looks like.

Canada should be immensely proud today, because they are leading the fight back when others dare not.

🎥 TikTok - https://t.co/BExGV2YIDq

[Haider. @haider1]

Computer scientist Judea Pearl:

There are mathematical limits to LLMs that cannot be crossed by scaling alone

LLMs don't discover world models from raw data; they merely summarize the interpretations humans have already written down

"this path is not the way to get AGI"

[Eva Locusteanu @Eva27738146]

Missing the pharmacy 🤣

[BogdanMateescu3 @BogdanMateescu3]

Bucharest.
Anarcho-capitalism.