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Hot take… isn’t it kinda crazy that nobody is really using AI Agents? I don’t mean software engineers or AI early adopters. I mean “college friends talking about it in group chat,” the feeling you got when everyone started using Instagram or TikTok. These frontier AI models are *insane* (as are the harnesses & tool calls & the like). And every large tech co has an AI agents platform, not to mention all the YC startups doing vertical agents. Yet all of your friends and family outside of tech — who spend all day staring at their iPhones and get paid to work in browser tabs — don’t really care or find themselves using any AI agents yet. Yes ChatGPT, Claude, etc. are extremely popular… but if you look at the engagement data the vast majority of people are still using these aI chat tools like a glorified Google + Grammarly. That’s why the AGI labs are all pushing desktop apps for Codex, Cowork, etc. so hard to non-technical ppl. And yes exceptions for lawyers and customer service but even those have some asterisks and exceptions to rule. Look I’m not saying the ChatGPT moment for AI Agents is not coming… it most definitely is! Remember we pivoted from Arc to Dia precisely because we believe computing is going to be radically reimagined around these AI primitives. No doubt. But that’s my point: it’s just so surprising it hasn’t happened yet because all of the tech you’d need is there. Again if you stop for a second and think about it… for all the press and money and hype and models and crazy ARR numbers… this “AI Agent” moment does not *feel* like the other breakthrough tech moments we’ve lived through (e.g. think the shift to Stories via Snapchat & Instagram, or shift to on-demand via Uber/Airbnb/Doordash). Which is a long way of saying: if you can figure out the answer to “why” most people don’t care about AI agents yet (and have no enduring interest in using them) — especially since the models and harnesses are here and ready — the answer to that question will allow you to capture a lot of marketshare and make a lot of money in 2027. Theoretically, the tech is ready for AI Agents to totally transform how we work and live our lives… but alas the general public dgaf… that’s the generational puzzle to solve for the next 12 months for anyone not working on the models themselves.

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!

Interesting trend: CTO/ Head of Eng / VPE folks at startups and mid-sized companies are... leaving / burning out. Hiring for these roles is HARD, but even after filling the role, they will often leave a few months later and take a career break And they have v good reasons

Tech giants like @nvidia don't always have the specificity to build the next wave of innovative tech, but they have the resources to back the startups that are. NVIDIA's global head of VC partnerships @Syd_Lykes is on this week's Build Mode to talk about working with corporate VC's and the unique power a single-minded founder has:

AI Startups Are Pivoting From Flashy Demos To Tech That Pays The Bills Founders who were working on neural-signal headphones and viral presentation builders are starting over in a high-stakes race for survival and revenue. Read more:

AI Startups Are Pivoting From Flashy Demos To Tech That Pays The Bills Founders who were working on neural-signal headphones and viral presentation builders are starting over in a high-stakes race for survival and revenue. Read more:

Why Do 90% of Startups and Businesses Fail—and What Mistakes Are They Making? #AxioraPulse# #StartupIndia# #Entrepreneurship# #IdeaValidation# #Startup# #Founder# #Entrepreneur# #Innovation# #BusinessGrowth# #Mentorship# #AI# #MarketValidation#

Consistency matters most when it makes the founder smarter, not merely busier. You can publish every week, send outreach, build features, or attend events consistently. But repetition alone does not mean the business is learning or improving 🤯 💡 Choose one repeated activity and ask yourself: “What should this teach me?” Outreach may reveal which customers respond. Sales calls may show which problem matters most. Product trials may expose where customers lose interest or become confused. The useful loop is simple: act, observe, compare, adjust. Consistency creates momentum when every repetition makes your next founder move more informed, before time, money, and attention run out 💨 👉 Follow @bMightie for more founder intelligence for the solo and bootstrapped business journey from day zero to takeoff. #startupshowup# #entrepreneurship# #founderlife# #productivity#