@sajithpai's India 1/2/3 framework by is an overly simplistic and one-dimensional way of looking at Indian consumer behaviour that is unrealistic. India 1 and 2 aren't different people, they're the SAME person making different decisions based on ANXIETY, not income. Explained:
@sajithpai 4) Zomato solved time anxiety. iPhone on EMI solved status + financial risk. Jio solved money anxiety. You win by solving one anxiety, not by targeting income brackets. This framework was built for pitch decks, not customers. Time to burn it down.
OPENAI IS FALLING APART IN REAL TIME
I've watched companies implode for decades.
This one has all the warning signs.
OpenAI declared "Code Red" in December.
Altman sent an internal memo telling employees to drop everything because Google's Gemini 3 is eating their lunch. Salesforce CEO Marc Benioff publicly ditched ChatGPT for Gemini after using it for two hours.
ChatGPT traffic fell in November. Second month-over-month decline of 2025. Meanwhile Gemini jumped to 650 million monthly active users.
The company that was supposed to build AGI can't keep its chatbot competitive.
But the real story is the money...
OpenAI lost $12 BILLION in a single quarter according to Microsoft's own fiscal disclosures.
Deutsche Bank estimates $143 billion in cumulative negative cash flow before the company turns profitable.
Their analysts put it bluntly: "No startup in history has operated with losses on anything approaching this scale."
They're burning $15 million per day on Sora alone.
$5 billion annually to generate copyright-infringing memes.
Even Sora's lead engineer admitted the "economics are currently completely unsustainable."
Here's the big math problem nobody wants to discuss:
It's going to cost 5x the energy and money to make these models 2x better.
The low-hanging fruit is gone.
Every incremental improvement now requires exponentially more compute, more data centers, more power.
Reports suggest OpenAI's large training runs in 2025 failed to produce models better than prior versions.
GPT-5 launched to widespread disappointment. Users called it "underwhelming" and "horrible." OpenAI had to restore GPT-4o within 24 hours because users preferred the old model.
Altman had promised GPT-5 would make GPT-4 feel "mildly embarrassing." Instead, users complained it was worse at basic math and geography.
They've released GPT-5.1, GPT-5.2 since.
Same complaints each time: too corporate, too safe, robotic, boring.
The talent exodus makes this even worse:
CTO Mira Murati. Gone.
Chief Research Officer Bob McGrew. Gone.
Chief Scientist Ilya Sutskever. Gone.
President Greg Brockman. Gone.
Half the AI safety team departed. Multiple executives reportedly cited "psychological abuse" under Altman's leadership.
And now Elon Musk is suing for up to $134 billion.
A federal judge just ruled the case goes to jury trial in April. There's "plenty of evidence" that OpenAI's leaders promised to maintain the nonprofit structure that Musk funded.
Musk provided $38 million in early funding based on those assurances. Now he wants his share of the $500 billion valuation.
OpenAI called it "harassment." But the judge disagreed.
Here's what I think happens next:
The AI hype cycle is peaking.
The diminishing returns are becoming impossible to hide.
Competitors are catching up.
The lawsuits are piling up.
OpenAI needs to generate $200 billion in annual revenue by 2030 to justify their projections.
That's 15x growth in five years while costs keep exploding.
Even Sam Altman admitted investors are "overexcited" about AI.
His exact words: "Someone is going to lose a phenomenal amount of money."
If I were running an AI startup with good traction right now, I'd be looking for an exit. Sell into the hype before the music stops.
My positioning:
I'm not touching OpenAI-adjacent plays at these valuations. The risk profile is astronomical.
If you're exposed to the Magnificent 7 through AI infrastructure bets, consider trimming. The gap between promised revolution and delivered reality has never been wider.
The smart money is rotating into sectors where valuations actually reflect fundamentals.
Small and mid-caps are trading near decade lows relative to Big Tech while earnings growth is only marginally lower.
Markets can price risk. But they can't price chaos.
And OpenAI is chaos dressed up in a $500 billion valuation.
if you’re an early stage founder you best believe that the equity you hold or the esops you’re so tied to are much much much closer to 0 than their paper value.
if you find good talent, pay them generously. give them great upside. your majority is useless if you don’t align incentives for all. 90% of 0 is 0. 33% of $10mn is $3.33mn.
all will nod in agreement. but in practice most fail. and then you’ve got disparities & ego blows to deal with for the rest of your journey. you won’t create a $1bn outcome holding 90% of a company (or) being anal about the extra 0.5% your founding member is asking for.
whether notional money or cash in bank; don’t hoard.
suffered, witnessed, now practising right.
in limited testing, Deep research can completely replace me for researching things i know nothing about to start (its honestly probably much better and certainly much faster). Even for long reports on things i am fairly knowledgeable about, it competes pretty well on quality (i had it reproduce some recent research i did with a few back and forth prompts and compared notes). i am honestly pretty shocked how polished the experience is and how well it works.
I have my gripes but i will save them for later. For now, i will just say that i am incredibly impressed with this release.
@heyCharafeddine I've found that perplexity has disappointed me and given inaccurate information and sources on multiple occasions, so I've stopped using it now and switched to asking chatgpt to state its sources
The UK & Europe's house is on fire and instead of investing in fire engines and manning the pumps, we're arguing about the regulatory requirements of fire hoses and taxing the firemen more to enter the house.
https://t.co/1DvSs4vcrM