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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!

Watch the full recording of our Q2 2026 earnings call. Prepared Remarks 00:00:00 - Welcome 00:01:20 - 843,775 BTC, 203,683 sats per share, $17B raised year to date, and Strategy’s position as the largest institutional holder of Bitcoin 00:03:27 - Q2 balance sheet: $49.7B of digital assets, $3.75B current USD reserve, lower debt, higher preferred equity, and strong stress-case coverage 00:08:57 - Bitcoin KPIs: 4.5% BTC Yield, 29,997 BTC Gain, and ~3.6x growth in Bitcoin per share since 2020 00:12:47 - Q2 execution: higher Bitcoin holdings, lower debt, larger USD reserves, stronger Bitcoin per share, and active capital management 00:15:03 - Strategy as a net buyer of Bitcoin and net issuer of Digital Credit: 48x more BTC bought than sold and 300x more Digital Credit issued than repurchased 00:18:47 - Returning $STRC to $99–$100 through USD reserves, Bitcoin monetization, repurchases, dividend management, and disciplined issuance 00:24:50 - Bitcoin liquidity: why Strategy’s bitcoin purchases and sales are not material to overall Bitcoin trading volume 00:33:03 - Bitcoin as Digital Capital: website metrics, the 200-week moving average, current headwinds, Bitcoin Dominance, banking adoption, and security coordination 00:44:08 - $STRC as flagship Digital Credit: liquidity, lower volatility, market depth, yield, investor base, path to par, and updated credit metrics 01:05:04 - Equity framework: hurdle rate, breakeven rate, floor rate, market skepticism, $MSTR outperformance, franchise advantages, and Strategy’s long-term ambition Q&A 01:19:31 - Why Bitcoin-backed borrowing is not currently the preferred path to build USD reserves 01:23:11 - Why Strategy is consolidating around $STRC instead of creating more instruments or selling volatility 01:40:37 - Equitizing, repaying, or refinancing convertible debt 01:43:18 - Covered calls, cash-secured puts, Digital Credit, Bitcoin as money, and marketing products to the 99% outside Bitcoin 01:59:22 - USD reserve minimums and the path to $STRC trading at par 02:00:55 - Amplification, USD/BTC reserve mix, and countercyclical capital management 02:12:04 - Why Strategy does not intend to issue $STRC below par 02:20:34 - Lessons from 2022 and 2026, tokenized securities, Digital Money, and the June 26 dislocation 02:34:54 - Closing remarks

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