Ruben, this is the kind of write-up that makes people stop doomscrolling and actually look up.
What hit me most is the “two exponentials” framing. Capability is sprinting, adoption is jogging, and that gap is where the opportunity and the whiplash both live. Also, the verifiable vs non-verifiable split is the clearest explanation I’ve seen for why “coding first” is not a hot take anymore. It’s just physics.
My only pushback is how easily readers will treat the 1–3 year line as fate instead of a forcing function. The actionable takeaway is not panic. It’s urgency plus agency. Build judgment, taste, and the ability to direct systems, because tasks are becoming cheap.
This one is worth sharing to anyone still treating AI like a “maybe later” tool. That window is already closing.
The reality is they lost the narrative on agentic once Clawbot dropped, so now they are back to AGI. Let’s be real, AI is predictive text on steroids, that’s it. I like Anthropic and Claude as a product, but all this AGI talk is marketing to validate their valuations.
My thoughts exactly. They are fear mongering so that they can keep the bubble from bursting. But all it takes is one stakeholder from sweating a little bit and scaling back
I find it wild how “near the end of the exponential” sounds like things slowing down, when in practice your breakdown makes it feel more like standing at the base of a vertical wall that suddenly appeared in front of the whole economy.
The two-curve framing (capabilities vs. diffusion) is especially clarifying; it explains why people’s lived experience still feels incremental even as lab demos cross thresholds like end-to-end software engineering in 1–2 years.
What sticks with me most is the idea that the real bottleneck now is not raw intelligence but organizational judgment and culture: who learns to direct a “country of geniuses in a data center” without blowing their own feet off.
Ruben, this is the kind of write-up that makes people stop doomscrolling and actually look up.
What hit me most is the “two exponentials” framing. Capability is sprinting, adoption is jogging, and that gap is where the opportunity and the whiplash both live. Also, the verifiable vs non-verifiable split is the clearest explanation I’ve seen for why “coding first” is not a hot take anymore. It’s just physics.
My only pushback is how easily readers will treat the 1–3 year line as fate instead of a forcing function. The actionable takeaway is not panic. It’s urgency plus agency. Build judgment, taste, and the ability to direct systems, because tasks are becoming cheap.
This one is worth sharing to anyone still treating AI like a “maybe later” tool. That window is already closing.
The reality is they lost the narrative on agentic once Clawbot dropped, so now they are back to AGI. Let’s be real, AI is predictive text on steroids, that’s it. I like Anthropic and Claude as a product, but all this AGI talk is marketing to validate their valuations.
My thoughts exactly. They are fear mongering so that they can keep the bubble from bursting. But all it takes is one stakeholder from sweating a little bit and scaling back
I find it wild how “near the end of the exponential” sounds like things slowing down, when in practice your breakdown makes it feel more like standing at the base of a vertical wall that suddenly appeared in front of the whole economy.
The two-curve framing (capabilities vs. diffusion) is especially clarifying; it explains why people’s lived experience still feels incremental even as lab demos cross thresholds like end-to-end software engineering in 1–2 years.
What sticks with me most is the idea that the real bottleneck now is not raw intelligence but organizational judgment and culture: who learns to direct a “country of geniuses in a data center” without blowing their own feet off.