I wrote about the state of AI, why I’m concerned about the next few years, and the choices we need to make to keep the future in humanity’s hands. An Alien Mind: openai.com/index/an-alien-mi…

Welcome Claudeforce. ❤️

Here is my AI investing guide. Sitting here August 2026, my current best thoughts are as follows: 1. LPS (Land Power Shell) is still the most obvious and fastest path to cash on cash returns. Lots of value can be assembled and traded quickly at this layer. And as data centers get more pushback, energized land can explode in value. Very bullish here. I’ve stepped into this layer very aggressively. My partner @anitavlallian and I have acquired almost 6GW coming online in a ramp from today thru 2029 of grid power and behind the meter. 2. Silicon - I helped get @GroqInc off the ground in 2015 and we licensed it to @nvidia for $20B Dec2025. I won’t invest or incubate anything in this layer now. The perf demands of the chips are too high, manufacturing precision is too complex and supply chain influence to get adjacent components like memory isn’t possible for a startup anymore. Lots of capital will be wasted here chasing Groq and Cerebras’ success. Note that both startups made sense a decade ago when these constraints were much more modest. 3. Clouds - Clouds are very very lucrative but very hard to build and very expensive and technically complicated to maintain. And as alignment becomes a more important issue, I expect the clouds will be asked to build robust KYC and attest to it. This makes the risk:reward ratio skewed. I don’t want to be responsible when the USG says a cloud allowed a bad actor to do something bad because of poor KYC. 4. Models are complicated. The big open question is how much of the revenue being generated by them today is because of tokenmaxxing and poor model behavior. If it’s a lot, then the annualized revenues will diminish meaningfully even as token consumption inflects upwards. This is the big economic question at this layer. 5. Harnesses are where the action is and why I started @8090solutions two years ago. In a nutshell, the harness helps enterprises owns their proprietary context (what Alex Karp calls their ‘alpha’). This is an enterprise’s data, workflows, evals, and business rules. A harness that gives this to an enterprise is what creates very low model-agnostic switching costs, which further reinforces my views of #4 above. 6. Applications will be another long term winner along with harnesses. This is where the differentiation between “off the shelf” and “custom time and materials” melts away. Every company, with the right harness, can now imbue their alpha into the software that runs their company. I expect this to mean that “off the shelf” is largely replaced with custom software creating a huge opportunity to write these solutions for companies. Build once and sell repeatedly is a laggard GTM motion for a SaaS world that isn’t needed here. Think custom by design, alpha embedded, proprietary by nature. Fin. Good luck to all the players!

एक छोटी सी बात समझिए। जिस जगह प्रदर्शन हो रहा है उसके पास कनॉट प्लेस के हनुमान मंदिर समेत कई मंदिर हैं। यह मंदिर जनता के चंदे से चलते हैं। यह दीगर है श्री राम जन्मभूमि में चंदा लूट लिया गया। जंतर मंतर पर प्रदर्शन के दौरान पुलिस के लाठीचार्ज से बचने के लिए हजारों नौजवान हनुमान मंदिर गए, लक्ष्मी नारायण मंदिर भी गए। सभी जगह दरवाजा बंद कर दिया गया और फिर थक हार कर यह सभी गुरुद्वारे में पहुंचे। गुरुद्वारे के सेवादार दरवाजे के बाहर खड़े हो गए और पुलिस को भीतर नहीं आने दिया। अच्छा खाना दिया, सोने की जगह दी। मंदिरों ने अपना धर्म नहीं निभाया।