No PriorsNo Priors Ep. 144 | The 2026 AI Forecast with Sarah & Elad
At a glance
WHAT IT’S REALLY ABOUT
AI’s 2026 Outlook: Agents, Robotics, New Labs, and Real-World Impact
- Sarah and Elad look ahead to 2026, arguing that despite market volatility and hype cycles, AI’s real economic and professional impact is only in the early innings. They highlight rapid enterprise adoption in conservative fields like medicine and law, consolidation in key verticals, and an impending wave of robotics and self‑driving deployments that will test current hype. The conversation explores foundation model competition, “neo labs,” alternative architectures, and evolutionary approaches to AI, alongside capital markets dynamics such as IPOs, M&A, and infrastructure constraints. A series of guest predictions round out the episode, focusing on reasoning, agents, context-rich products, energy efficiency, AI drug discovery, and the broader social and political consequences of AI’s rise.
IDEAS WORTH REMEMBERING
5 ideasAI’s real impact is rising even as hype and skepticism oscillate.
The hosts argue that reports downplaying AI’s productivity gains miss the long diffusion curve; adoption in areas like coding, medical documentation, and legal work is already substantial and will compound over the decade regardless of short-term sentiment swings.
Professional services and conservative sectors are becoming leading AI adopters.
Doctors, lawyers, compliance, and accounting—historically slow to adopt tech—are embracing AI for documentation and decision support, suggesting that reasoning over unstructured data maps particularly well to high-value expert workflows.
Robotics and self-driving will face a reality check before unlocking major value.
Humanoid and semi-humanoid robots are expected to see small-scale deployments that won’t fully match the hype, creating a sentiment pullback similar to early self-driving; long term, self-driving and industrial robotics should still become highly consequential markets, likely with strong roles for incumbents like Tesla, Waymo, and Chinese firms.
Foundation model competition will hinge on capital, architectures, and evolution-like methods.
While scale and capital advantage push the field toward a few dominant labs, the hosts see room for alternative architectures (diffusion, SSMs, continual learning) and evolutionary or self-improvement approaches that more closely resemble specialized biological systems and may unlock new performance leaps.
Consumer AI is underdeveloped, leaving room for breakout agentic products.
Apart from chat-style interfaces, there are few truly novel consumer AI experiences; the hosts expect new agentic, context-aware products and hardware experiments (many of which may fail) and note that only a relatively small pool of truly elite consumer PMs may be capable of inventing enduring new interfaces before incumbents copy them.
WORDS WORTH SAVING
5 quotesThe reality of the technology will always take ten years to propagate, and people are getting enormous value out of AI already and they're gonna get way more out of it in the future.
— Elad
All the people who always never adopt technology are now adopting this stuff fast… physicians, lawyers, certain accounting types, compliance. I do think that's really notable and very under-discussed.
— Elad
There'll be a couple of anecdotal one-offs in science that will make people say, 'Look, science is solved,' and they'll realize science isn't solved, and then later science will be solved.
— Elad
I always thought that eventually you end up with evolutionary systems as really how you build AI… where you just evolve these systems with some utility function they’re evolving against.
— Elad
I did not believe that we were gonna see that many unique consumer experiences besides ChatGPT… but I am seeing magical experiences of really different consumer agent software that I actually want and will use.
— Sarah
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