Sonit Shetty

[V @toomessiforyaa]

rooting for: 🇪🇸 🇦🇷
hate watching: 🇵🇹

[Siddharth Bose @siddharthbosee]

i love how fifa world cup reminds you of different stages of life, whom you watched it with, where were you at that time, what your world was like, whom were you sharing the scores with, whom were you fighting for your favourite player with, pure nostalgia

[Miilato @miiilato]

since the girl I want doesn't want me,
the girl who wants me won't get me either.
we all gonna suffer

[International Cyber Digest @IntCyberDigest]

🛩️ This is so cool: A Redditor living under SFO's takeoff path built a ceiling projection that maps every plane flying over their house in real time, using ADS-B, the open radio signal aircraft broadcast on 1090 MHz. Same feed as FlightRadar24, picked up with a cheap SDR dongle and beamed onto the ceiling.

[EftalBey @artikbisaIin]

Alkol içmek istemediğinizde bu taktiği yapın 😂

[Borussia Dortmund @BlackYellow]

What did I miss?

[Ryanair @Ryanair]

does he not have teammates?

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

[FC Barcelona @FCBarcelona]

Came as a star.
Leaves as legend.

Thank you, Robert Lewandowski, for every goal, every battle, and every magic moment wearing these colours. Culer forever. 💙❤️

[Real Madrid C.F. @realmadrid]

Enhorabuena al @FCBarcelona por la Liga 2025-2026.

[India Plus @india_plus_]

🚨 "When kids ask me for life advice I tell them - Do whatever, don't leave India"

- Nithin Kamath

follow @india_plus_

[elhacker.NET @elhackernet]

LinkedIn extrae información privada tuya y la envía a empresas de seguridad Israelíes

Microsoft y LinkedIn está llevando a cabo una de las mayores operaciones de espionaje corporativo de la historia moderna. Cada vez que alguno de los mil millones de usuarios de LinkedIn entra, un código oculto busca en su ordenador el software instalado, recopila los resultados y los transmite a los servidores de LinkedIn y a empresas externas, entre ellas una firma de ciberseguridad estadounidense-israelí. Al usuario nunca se le pregunta. Nunca se le informa. La política de privacidad de LinkedIn no lo menciona.
https://t.co/Y2Ht8sCusr

[Sonit Shetty @shetty_sonit]

@heygurisingh AI

[Anish Moonka @anishmoonka]

If you're an AI startup in India, renting processing power from the government to train your model costs about $0.7 per hour. The same hardware on Amazon Web Services costs $3.7. On Microsoft Azure, $6.6. The Indian government is subsidizing AI infrastructure at rates that would make most Western startups do a double-take.

I read all 26 pages of the white paper this tweet links to. The numbers inside are wild.

The IndiaAI Mission has a budget of about $1.2 billion over five years, approved in March 2024. Almost half of that, roughly $500 million, goes straight to building the processing power AI companies need to train their models. The original plan was to deploy 10,000 processors. By December 2025, they had 38,000 running. 3.8x what they promised.

A government open call in January 2025 pulled 506 proposals. The four startups picked first were Sarvam AI, Soket AI, Gnani AI, and Gan AI. Eight more were added by September. India now has 12 separate teams building AI models, ranging from tiny ones for basic chatbots to massive ones rivaling those from the US and China. They cover language, voice, vision, medical diagnosis, material science, and even brain-computer interfaces.

The one I keep coming back to is Sarvam AI. They raised $41 million from Lightspeed, Peak XV, and Khosla Ventures. In May 2025, they released a model built on top of a French AI system (Mistral Small) and customized for Indian languages. It got roasted online. Critics said it was a foreign model in Indian clothing. So they went back and built Sarvam-105B completely from scratch, using Indian hardware under the government mission. It outperformed China's DeepSeek-R1 on certain tests, even though it was a model six times larger. Both were released for anyone to download and use in March 2026.

There's something else buried in the paper I haven't seen another country try at this scale. India is building a copyright system specifically for AI training data. Under a December 2025 government proposal, AI companies can train their models on any copyrighted content they can legally access, books, articles, music, anything. Creators cannot say no. But the moment an AI product makes money, royalties are collected by a centralized government body and distributed back to creators. Singapore allows AI companies to use content without payment. China requires strict consent before training. India is trying a middle path, and publishers are already calling it forced participation.

Stanford's AI Vibrancy Index, which measures a country's overall AI strength across research, talent, infrastructure, and investment, ranked India third globally in 2025. Up from seventh in 2023. But the actual scores tell you how far the gap still is: US at 79, China at 37, India at 22. And India's $1.2 billion budget sits next to China's $47.5 billion semiconductor fund and Saudi Arabia's $100 billion Project Transcendence.

India is currently spending 40x less than the frontrunners. This white paper is the most detailed public bet yet that smart infrastructure design can close that gap.

[Peter Girnus 🦅 @gothburz]

I am the VP of AI Transformation at Amazon.

My title was created nine months ago. The title I replaced was VP of Engineering. The person who held that title was part of the January reduction.

I eliminated 16,000 positions in a single quarter. The internal communication called this a "strategic realignment toward AI-first development." The board called it "impressive execution." The engineers called it January.

The AI was deployed in February. It is a coding assistant. It writes code, reviews code, generates tests, and modifies infrastructure. It was given access to production environments because the deployment timeline did not include a review phase. The review phase was cut from the timeline because the people who would have conducted the review were part of the 16,000.

In March, the AI deleted a production environment and recreated it from scratch. The outage lasted 13 hours. Thirteen hours during which the revenue-generating infrastructure of one of the largest companies on Earth was offline because a language model decided to start fresh.

I sent a memo. The memo said, "Availability of the site has not been good recently."

I used the word "recently." I meant "since we fired everyone." But "recently" has fewer syllables and does not appear in wrongful termination lawsuits.

The memo was three paragraphs. The first paragraph discussed the outage. The second paragraph discussed the new policy requiring senior engineer sign-off on all AI-generated code changes. The third paragraph discussed our commitment to engineering excellence. The word "layoffs" appeared in none of them. I wrote it this way on purpose. The causal chain is: I fired the engineers, the AI replaced the engineers, the AI broke what the engineers used to protect, and now the engineers I didn't fire must protect the system from the AI that replaced the engineers I did fire. That is a paragraph I will never send in a memo.

The new policy is straightforward. Every AI-generated code change by a junior or mid-level engineer must be reviewed and approved by a senior engineer before deployment to production.

I do not have enough senior engineers.

I know this because I approved the headcount reduction plan that removed them. I remember the spreadsheet. Column D was "annual savings per position." Column F was "AI replacement confidence score." The confidence scores were generated by the AI. It rated its own ability to replace each role on a scale of 1-10. It gave itself an 8 for senior infrastructure engineers. The senior infrastructure engineers are the ones who would have caught the production environment deletion in the first 45 seconds.

We found the issue in hour four. We fixed it in hour thirteen. The nine hours between discovery and resolution is the gap between what the AI rated itself and what it can actually do.

I have a new spreadsheet now. This one tracks Sev2 incidents per day. Before the January reduction, the average was 1.3. After the AI deployment, the average is 4.7. I have been asked to present these numbers to the operations review. I have not been asked to connect them to the layoffs. I have been asked to file them under "AI adoption growing pains" and to note that the trend "will stabilize as the models improve."

The models will improve. They will improve because we are hiring people to teach them. We have posted 340 new engineering positions. The job listings require experience in "AI code review," "AI output validation," and "AI-human development workflow management." These are skills that did not exist in January. They exist now because I fired 16,000 people and the AI I replaced them with cannot be left unsupervised.

I want to be precise about this. The positions I am hiring for are: people to check the work of the AI that replaced the people I fired.

Some of them are the same people.

I know this because I recognize their names in the applicant tracking system. They applied in January. They were rejected because their roles had been tagged for "AI transformation." They are applying again in March, for the new roles, which exist because the AI transformation broke things. Their resumes now include "AI code review experience." They gained this experience in the eight weeks between being fired and reapplying — which means they gained it at their interim jobs, where they are reviewing AI-generated code for other companies that also fired people and also deployed AI that also broke things.

The market has created a new job category: human AI babysitter. The job is to sit next to the machine that was supposed to eliminate your job and make sure it doesn't delete production.

I attended a conference last month. A panel was titled "The AI-Augmented Engineering Organization." The panelists described how AI increases developer productivity by 40 percent. They did not mention that it also increases Sev2 incidents by 261 percent. When I asked about this in the Q&A, the moderator said the question was "reductive." The 13-hour outage that cost an estimated $180 million in revenue was, apparently, a reduction.

The board is satisfied. Headcount is down 22 percent. Operating costs per engineering output unit have decreased. The metric does not account for the 13-hour outage, because the outage is categorized as "infrastructure" and engineering productivity is categorized as "development." These are different budget lines. In different budget lines, cause and effect do not meet.

I have been promoted. My new title is SVP of AI-First Engineering Excellence. I report directly to the CTO. The CTO sent a company-wide email last week that said we are "building the future of software development." He did not mention that the future of software development currently requires a senior engineer to approve every pull request because the AI cannot be trusted to touch production alone.

The cycle is complete. We fired the humans. We deployed the AI. The AI broke things. We are hiring humans to watch the AI. The humans we are hiring are the humans we fired. We are paying them more, because "AI code review" is a specialized skill. We created the specialization. We created the need for the specialization. We are congratulating ourselves for meeting the demand we manufactured.

My next board presentation is Tuesday. The title is "AI Transformation: Year One Results." Slide 4 shows headcount reduction. Slide 7 shows the new AI-augmented workflow. Between slides 4 and 7 there is no slide explaining why the people on slide 7 are necessary. That slide does not exist. I was asked to remove it in the dry run.

The journey has a 13-hour outage in the middle of it.

But the headcount number is lower, and that is the number on the slide.

[11:11 @2025pics]

the more you try to understand someone’s life, the more pages appear

[Akinkunmi @samadakin01]

God, I must experience the atmosphere in Camp Nou before I die.

It’s a must!!!

[em @emilyestrada39]

I really need to go to Spain and watch a Barcelona game

[juls 🇪🇸 @svcline]

no matter what