RT @praveenTweets: Agentic AI adoption is on fire at @Uber, and it’s changing the way we build, not just in engineering, but across the ent…
— Abhay 🇸🇬🇮🇳 (@Abhay08)
Jul 9, 2026
If you have ever led large teams you will immediate know what this means and how ineffective 1:1s are in needle moving teams. Do it only if required, never pollute your calendar with weekly 1:1s https://t.co/wL0kitZhaT
— Abhay 🇸🇬🇮🇳 (@Abhay08)
Jul 6, 2026
@mignano Agree on value being created at the routing layer as this has been a biggest gap I see for enterprises and forward deployed engineers who are setting the rails in enterprises. My take https://t.co/OmwlHJx7VR
— Abhay 🇸🇬🇮🇳 (@Abhay08)
Jul 6, 2026
RT @philhchen: https://t.co/oMoEAYkqGl
— Abhay 🇸🇬🇮🇳 (@Abhay08)
Jul 4, 2026
Every time you send a prompt to an AI app, something behind the scenes has to decide which model inference server actually answers it. Most people never think about this. But that decision — the “router” — is quietly turning into one of the most important pieces of the AI stack. This is a walkthrough of what routers actually do today, what’s still shallow about them, and where the smart money says they’re headed next.
🚴🎧 over 2x rides. Getting rack scale system built in this short of time is no joke. Beats all the BS peddled where silicon is only for grey haired. https://t.co/Jv8KOWeyrx
— Abhay 🇸🇬🇮🇳 (@Abhay08)
Jul 2, 2026
TPU Deep dive
https://t.co/lKvhLNDZ4A
— Abhay 🇸🇬🇮🇳 (@Abhay08)
Jun 29, 2026
#3 Token prices are heading to ~1/10th of today’s.
Compute scarcity props prices up while consumers (unprofitable) eat half the supply.
As efficiency catches up: prices collapse, usage explodes – Jevons paradox. The durable moat becomes memory + context aka The Harness, not the— Abhay 🇸🇬🇮🇳 (@Abhay08)
Jun 26, 2026
#2 Consumers tolerate false positives. Enterprises tolerate zero.
That one gap explains the whole market.
Frontier models chase consumer breadth (brand + post-training data). Real agentic enterprise value needs depth, context, memory — that’s where the moat forms.— Abhay 🇸🇬🇮🇳 (@Abhay08)
Jun 26, 2026
https://t.co/qMSxphnGU9 The breadth of topics and how masterfully Nikesh navigates is just fabulous.
#1 Physical AI is a depth problem, not breadth.
No consumer use case = no crowdsourced training data. The model that flies planes ≠drives cars ≠runs factories.
Waymo proves— Abhay 🇸🇬🇮🇳 (@Abhay08)
Jun 26, 2026