A post-mortem of the July 2026 sell-off from someone who calls it 2022 packed into a single month. Useful counterweight if you only ever read the optimistic version.
More from Sven Balnojan
Love this episode. Tara is an amazing builder and I've listened to this episode multiple times now and recommended it to multiple product related people at my company.
I think my two biggest take aways are the "three mantras" Tara shares about "how to build products at OpenAI" and her thinking on "the only possible planning horizon".
The three mantras:
- Are you “mainlining it yet”? Are you bringing all your taste on here? Are you using this all day?
- Is this maximally accelerated? Can you go any faster here? Can you get this into the hands of (early!) users faster?
- Are you being as ambitious as possible? Scope? Blow it up if you can!
- “*“You fail if you build for where the models are now, you fail if you build for where you think the models will be in a year. Both outcomes are equally wrong, and I'm sure many people have talked about this, but both outcomes are really equally wrong. If you're too early, you're wrong.”
- “If you build something that was overly focused on a past model's capabilities, you're entirely wrong. The only way to build is two to three months””
AI’s third era: the rise of persistent AI coworkers | Tara Seshan (Product Lead ChatGPT Work)
Lenny's Podcast: Product | Career | Growth · 1 hr 22 min
from What I'm learning about building AI products (fast!)share this
The case that the next era is not faster chatbots but background agents running on their own for hours or days — and what has to get cheaper before that works at all.
Multi-agent systems, and what the current run of mathematics results suggests about automating AI research. The harder question sits underneath: how would you even know whether a model is aligned.
Noam Brown – Agent swarms, alignment, & recursive self-improvement
Dwarkesh Podcast · 1 hr 20 min
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