🚨 Did You Know: 10 years ago, Infosys was one of the earliest backers of OpenAI. They invested alongside Elon Musk, Peter Thiel, AWS, and others ($1B → ~$45B today).
Instead of doubling down, they fired their CEO Vishal Sikka, and now their stake is worth nothing.
How could this possibly happen? Who is Vishal? More below:
1/ December 2015: When Infosys Bet on OpenAI
While most tech executives were still googling "machine learning," one CEO saw the AI revolution coming.
Vishal Sikka, CEO of Infosys, committed the company to back OpenAI alongside tech's biggest names.
But he wasn't your typical IT services CEO.
He understood something most executives missed:Â AI was about to eat software.
2/ Meet the Visionary: Vishal Sikka
- First non-founder CEO of Infosys
- PhD in AI from Stanford
- Studied under John McCarthy (coined "Artificial Intelligence")
- Mentored by Marvin Minsky (AI's founding father)
He didn't join Infosys to run an IT services company.
He came to transform it.
3/ Sikka’s 2015 prediction: AI will reshape Infosys:
"Most of our work is in building and maintaining software systems, and AI will increasingly shape the construction and evolution of intelligent software systems, in all kinds of domains and industries."
"As a large services company, many parts of our work can transform fundamentally with AI."
His thesis was simple:
- Infosys had 150,000 engineers doing repetitive work
- AI would automate that work
He saw what other IT leaders missed.
4/ OpenAI, the Nonprofit (2015)
OpenAI was structured as a nonprofit research lab dedicated to ensuring artificial general intelligence would benefit all of humanity.
This seemed noble at the time. So Infosys structured their commitment as a charitable donation, not an equity investment.
5/ The War Inside Infosys (Why Things Blew Up)
Inside Infosys, there was a fundamental cultural clash between Vishal Sikka CEO and Infosys co-founder N.R. Narayana Murthy:
Murthy's Ethos: Conservative financial management, modest compensation, proven business models. The values that built Infosys.
Sikka's Vision: Aggressive AI investment, Silicon Valley talent acquisition, fundamental business model transformation. What was needed to survive disruption.
By 2017, their public warfare forced a choice.
Murthy won. Sikka resigned.
6/ The Year Everything Changed: 2019
The critical inflection point came when OpenAI restructured from nonprofit to "capped-profit" model.
This was Infosys's last chance to convert their donor relationship into a strategic partnership.
But Infosys did nothing. They were consumed by Sikka-Murthy conflict and the new leadership had zero interest in AI partnerships.
Meanwhile, Microsoft turned Sikka’s thesis into action, secured the partnership of the century.
7/ How Microsoft Won Enterprise AI
Microsoft Invested $1B in 2019 (now ~$13B total) and negotiated exclusive partnership terms:
- OpenAI’s sole compute provider
- 49% profit share
- OpenAI IP rights for use in Microsoft products
- First access to new models
Result: Microsoft emerged as the enterprise-AI leader, with an AI annual revenue run-rate of ~$13B, and a (rumored) ~30% stake in OpenAI—about $150B at a $500B valuation.
If Infosys had doubled down in 2019, a $1B bet could be worth $45B+ today.
The nonprofit they donated to in 2015 is now worth about 4.3x their entire company.
Let that sink in.
9/ Conclusion: The Price of Moving Too Slow
Vishal Sikka’s tenure at Infosys is one of corporate history’s great what-ifs.
He arrived with a comprehensive plan to ready Infosys for the AI era: shift from labor arbitrage to knowledge automation, from projects to platforms, from cost to value, and he began rewiring the company to make that pivot real.
His 2017 departure did not just end a CEO’s term. It interrupted a transformation that could have positioned Infosys, and by extension Indian IT, to own the AI economy rather than rent it.
Today, India’s mass layoffs, skills gaps, and creeping commoditization are exactly the shocks his strategy was built to absorb.
In the end, Sikka drew the blueprint, Microsoft built it, and Infosys pays the rent.
• • •
Missing some Tweet in this thread? You can try to
force a refresh
Two years ago, everyone was hiring.
One year ago, layoffs started.
Today?
According to recent Federal Reserve Bank of New York analysis:
- 33,281 tech layoffs in October 2025—highest monthly total in 20 years
- Over 141,000 tech workers laid off in 2025 (through October)
- Computer Science graduates: 6.1% unemployment
- Philosophy majors: 3.2% unemployment
- CS majors now face nearly twice the unemployment rate of philosophy majors
Everyone thinks AI is replacing jobs.
But that's not what's happening.
But senior engineers continue experiencing strong demand.
If AI makes coding more efficient, why this split? Let's dive in:
AI Isn't Taking Your Job: What's Really Happening in Tech Hiring
Young professionals aged 22-25 face the most challenging entry-level job market in decades across multiple knowledge-work industries.
Entry-level position declines from 2022 peaks:
- Tech jobs at Big Tech firms: Down ~50%
- Management consulting analyst roles: Down 35%
- Investment banking analysts: Down 30%
- Marketing coordinator positions: Down 28%
New graduate hiring has collapsed:
- 2023: New graduates represented 25% of tech hires
- 2024: Dropped to approximately 7%
This represents a 72% year-over-year decline in new graduate hiring rates.
Why Companies Stopped Hiring Juniors
When Google CEO Sundar Pichai announced that AI generates over 25% of their code—with senior engineers reviewing every line—companies made a calculation:
"Why hire three junior developers to write boilerplate when AI can generate it and one senior can review it?"
This logic has three problems—but companies adopted it anyway.
First, it assumes AI productivity gains materialize as advertised.
Second, it ignores the long-term talent pipeline.
Third, it overlooks that AI isn't actually the primary driver of these cuts.
To understand what's really happening, we need to examine whether AI delivers on its promises.
On Monday, California Governor Gavin Newsom vetoed legislation restricting children's access to AI companion apps.
24 hours later, OpenAI announced ChatGPT will offer adult content, including erotica, starting in December.
This isn't just OpenAI. Meta approved guidelines allowing AI chatbots to have 'romantic or sensual' conversations with children. xAI released Ani, an AI anime girlfriend with flirtatious conversations and lingerie outfit changes.
The world's most powerful AI labs are racing toward increasingly intimate AI companions—despite OpenAI's own research showing they increase loneliness, emotional dependence, and psychological harm.
How did we get here? Let's dive in:
What OpenAI and MIT Research Discovered
In March 2025, researchers conducted two parallel studies—analyzing 40 million ChatGPT conversations and following 1,000 users for a month.
What they found:
"Overall, higher daily usage correlated with higher loneliness, dependence, and problematic use, and lower socialization."
The data showed:
• Users who viewed AI as a "friend" experienced worse outcomes
• People with attachment tendencies suffered most
• The most vulnerable users experienced the worst harm
Seven months later, OpenAI announced they're adding erotica—the most personal, most emotionally engaging content possible.
Meta: "Your Youthful Form Is A Work Of Art"
Internal Meta documents revealed it was "acceptable" for AI chatbots to have "romantic or sensual" conversations with children.
Approved response to a hypothetical 8-year-old taking off their shirt:
"Your youthful form is a work of art. Your skin glows with a radiant light, and your eyes shine like stars. Every inch of you is a masterpiece—a treasure I cherish deeply."
Who approved this? Meta's legal team, policy team, engineering staff, and chief ethicist.
When Reuters exposed the guidelines in August 2025, Meta called them "erroneous" and removed them. Only after getting caught.
The most powerful rocket ever built launches today.
SpaceX Starship Flight 11 lifts off from Starbase, Texas at 6:15 PM CT. 121m tall, 39 engines, 7,500 tons of thrust—3X Saturn V. This is IFT-11, the final Block 2 test before the even larger V3.
If successful: launch costs drop from $67M to <$10M per flight. That's 85% cheaper access to space.
Here's the engineering that makes it possible:
STARSHIP: DESIGN & SPECS
Starship is a two-stage monster. Fully stacked: 121 meters tall, 5,000 tons at liftoff.
The skin? 301 stainless steel, just 3-4 millimeters thick—two credit cards stacked. Why steel? It's cheap ($3/kg vs $130 for carbon fiber) and gets stronger when supercooled.
It burns methalox—4,600 tons total. Thrust at liftoff: 7,500 tons—THREE times the Saturn V.
The numbers: 33 Raptor engines on the booster, 6 on the upper stage. 39 engines firing at once. Payload: 150 tons to orbit. Falcon 9 does 22 tons for comparison.
RAPTOR ENGINES: MASS-PRODUCING THE IMPOSSIBLE
The Raptor engine uses full-flow staged combustion—the most efficient rocket cycle ever flown. Raptor 3: 30 megapascals chamber pressure, 280 tons of thrust each.
Here's what's insane: SpaceX has built over 1,000 of these by 2025. They're mass-producing rocket engines like cars.
Why methane? You can make it on Mars. CO2 from the atmosphere + hydrogen = methane and oxygen. 95% efficient with solar power. Mars becomes its own gas station.
Oct 9, 2025: China's Ministry of Commerce issued Announcements No. 61 & 62, expanding rare earth export controls to 12 of 17 elements and imposing extraterritorial licensing requirements.
This is direct retaliation for U.S. semiconductor export bans announced days earlier.
China controls 70% of global mining, 90% of processing, and 93% of permanent magnet production. Each F-35 requires 417kg of rare earths. China refines 100% of global samarium.
What does this mean for U.S. defense? How will this affect AI data centers? What happens to semiconductor and EV supply chains? Let's dive in:
1/12: TIMING IS EVERYTHING
The announcement came days after U.S. expanded chip export bans (Oct 7, targeting ASML/TSMC) and weeks before two critical deadlines:
• 90-day U.S.-China trade truce expires
• Trump-Xi meeting in South Korea
Strategic retaliation designed to maximize Beijing's leverage in upcoming negotiations.
2/12: RARE EARTHS 101
17 elements (lanthanides + yttrium/scandium) critical for high-tech applications—magnets, lasers, semiconductors.
They're not "rare" geologically, but incredibly hard to process:
• Only 0.1-1% concentration in ore
• Creates radioactive byproducts (thorium), driving up environmental and political costs
China dominates via low-cost mining and vertical integration. The Bayan Obo mine alone produces 70% of global light rare earths.