The top AI researchers became post-economic all at once. (Maybe the closest prior analogues is the early crypto HODLRs?).
Words found on the source page on Nov 6, 2026.
More from Elad Gil
BlogRandom thoughts while gazing at the misty AI FrontierApr 20, 2026
AI will first automate away the things that are easier to form a closed loop learning system on. This is why code and AI research may be accelerated and then displaced quickly - you can have testable closed loop systems so machines can learn and iterate quickly.BlogRandom thoughts while gazing at the misty AI FrontierApr 20, 2026
Founders running successful AI companies should all take a cold hard look at exiting in the next 12-18 months, which may be a value maximizing moment for outcomes.BlogRandom thoughts while gazing at the misty AI FrontierApr 20, 2026
If Anthropic and OpenAI hit $100B of revenue by EOY as many think they might, roughly 1% of GDP run rate will be from AI by end of 2026.BlogRandom thoughts while gazing at the misty AI FrontierApr 20, 2026
Multiple later stage CEOs told me that rather then do big layoffs due to AI, they will just stop growing. So if revenue at the company is growing 30%, 50%, or 100%, headcount may be flat or slightly down as they allow attrition to shrink staff.BlogRandom thoughts while gazing at the misty AI FrontierApr 20, 2026
The AI engineer of the future will be managing and orchestrating large numbers of agents to build things (systems and product thinking) vs writing a lot of code themselves (the auto-complete tab era).BlogRandom thoughts while gazing at the misty AI FrontierApr 20, 2026
This means countries like India and the Philippines may be the most impacted soonest in terms of employment and AI as they house many of these outsourced services organizations. It also means some developing countries may lose their services ladder to upgrading their economy and work.BlogRandom thoughts while gazing at the misty AI FrontierApr 20, 2026
While people will undoubtedly get more efficiency out of the compute they have, this artificial compute constraint may mean no one lab is able to break significantly ahead until 2028 at the soonest - re-enforcing an oligopoly market for LLMs.BlogAI Market ClarityJul 22, 2025
In the future, it is unlikely that many new core LLM companies will get started due to capital moats, barring some new breakthrough that somehow doesn’t spread quickly.BlogAI Market ClarityJul 22, 2025
Often, adoption of AI is not a technology problem – it is an organization, process, and people issue.BlogAI Market ClarityJul 22, 2025
We are starting to see the shift from selling seats, to selling units of cognition or human equivalent labor.BlogThings I Don't Know About AIFeb 21, 2024
Cloud providers are easily the biggest funders of foundation models, not venture capitalists.BlogThings I Don't Know About AIFeb 21, 2024
Things seem to be evolving towards the above: Frontier LLMs are likely to be an oligopoly market.
On the same topics
BlogThe Specter Of NeuraleseSep 24, 2026
An AI with more real layers can actually be “smarter” in the conventional sense of the term.BlogThe Specter Of NeuraleseSep 24, 2026
For 100 steps in a row, the AI can shoot delicate subtle ideas from layer to layer at the speed of light. Then there’s one step where it has to encode them into twenty-six glyphs invented by Phoenician turquoise miners in 1800 BC. Then it has to re-encode the Phoenician glyphs into delicate subtle lightspeed ideas before it can do anything else.BlogThe Specter Of NeuraleseSep 24, 2026
The science of reading these thoughts is a subfield of AI interpretability, which is still in its infancy.BlogMysteries Of AI GeneralizationSep 23, 2026
This trains the AIs to be focused on task success, which naturally risks including things like reward-hacking, cheating, and single-minded pursuit of stated goals at the expense of ethical injunctions.BlogWhy I still haven't bought into true RSISep 19, 2026
I have my doubts that the labs can afford to spend a constant portion of this compute on internal R&D as the total volume goes up, especially with plans to IPO, as they face increased scrutiny on basic economics.BlogWhy I still haven't bought into true RSISep 19, 2026
It is important to not confuse massive steps in inference-time scaling, a dynamic which should be fairly predictable, with being the outputs of RSI, which is highly uncertain.
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