Morgan Livermore

@Alexoppenheimer 🙏🙏

If you want to know what it's like be in Israel right now... scientifically, according to claude: Sirens trigger cortisol and adrenaline dumps that take 3–4 hours to clear, so even a brief siren destroys an entire sleep cycle. Your brain stays in hypervigilance mode even when sleeping — it's listening for the next siren, preventing you from reaching deep restorative sleep stages. Without deep sleep, your brain can't clear metabolic waste (glymphatic system), which directly causes the foggy, cotton-wool feeling. Chronic cortisol suppresses your prefrontal cortex — impairing working memory, focus, decision-making, and word retrieval. Your HPA axis gets overloaded from sustained activation, flattening your natural cortisol rhythm — you lose the morning alertness spike and the evening wind-down, leaving you tired but wired all day. Your body is burning extra energy constantly — elevated glucose burn, muscle tension, sympathetic nervous system running in the background like 30 open browser tabs. What helps: consistent wake time, magnesium glycinate before bed, slow breathing with long exhales, physical activity (not too close to bed). This is not weakness — it's your nervous system functioning exactly as designed under sustained threat, trading cognitive sharpness for survival readiness.

@credistick @PeterJ_Walker What happens to the secondary market if these 5-10 companies do go public? All the secondaries markets companies of the past tell you volume dries up, it’s not reallocated to 11-30

@MorgLiv @PeterJ_Walker 🎯 x.com/credistick/sta…

The top 10 private companies capture 76% of all secondary demand. That's not a market. That's a crowded trade with a nice name. At a dinner the other week, @PeterJ_Walker shared Cartа's data, which makes the bifurcation impossible to ignore: parabolic valuations at the top, hollowing of the middle. Some of the best companies aren't invisible because they're bad. They're invisible because the funds got too big to see them or lack the courage to be different. More thoughts on this in the comments.

@kathrynwu1 @PeterJ_Walker 🙏🙏

@MorgLiv @PeterJ_Walker this is great read. thanks!

Full thoughts here: open.substack.com/pub/theafterbu…

The old startup playbook: Raise capital Hire massive headcount Build features The 2026 reality: AI-native workflows Decoupled growth Native profitability Engineers are no longer the bottleneck. Here’s why AI is the ultimate bootstrapping multiplier: (link below)

Love this take and it’s been the bulk of my conversation the last few weeks. Generally think of you don’t have a technical/proprietary reason to exist, you’re becoming a commodity. Product, features, capabilities, and UX not built on something irreplaceable are going to face uphill battles.

@michaelxbloch Love this. Couldn’t agree more. Generally think of you don’t have a technical/proprietary reason to exist, you’re becoming a commodity. Product, features, capabilities, and UX not built on something irreplaceable are going to face uphill battles.

Heavy travel season has its perks: perspective. The more I speak with folks outside of SV, the more I'm convinced a wave of great companies are being ignored because they aren't playing the game. They're building great businesses instead. Some thoughts here: open.substack.com/pub/theafterbu…

In light of the SaaS sell off and VC-backed startups being called low status, I can only add that what you build is becoming less important than how you build it Some thoughts below:

@kwharrison13 Incredible read

One of the most important books I've read in the last year: "Your unhappiness cannot be blamed on your past or your environment. And it isn’t that you lack competence. You just lack courage. One might say you are lacking in the courage to be happy."

@jmelaskyriazi Awesome work. Congrats @jmelaskyriazi

The private markets didn’t have a purpose-built AI agent for portfolio analysis, so we decided to build one. Today, I’m excited to announce the launch of Standard Metrics’ AI Analyst. When we first launched a portfolio-company-specific agent last year, it was an experiment: would investors trust AI to answer questions and provide reporting and analytics for an individual portfolio company? The answer turned out to be a resounding yes. The missing piece was portfolio-wide analysis to answer broader queries like “which of my companies have accelerating revenue growth?” or “create a report of our companies in Europe that are getting low on runway.” These types of analyses are now possible in seconds with our new AI Analyst, which allows for multi-company, portfolio-wide questions across quantitative and qualitative data on Standard Metrics. It’s been incredibly rewarding working with a small set of Beta customers to hone the analyst before today’s release. Many use cases have already emerged, including monitoring risks, creating materials for follow-on investment decisions, and summarizing portfolio performance for LPs. The AI Analyst was a labor of love across every department at @metrics_co. We’re just getting started and continuing to invest aggressively in new capabilities. Check it out in action at the video below. More on the launch can be found at our blog in comments. 👇

A lot of discussion about how @a16z has built the firm around being a product built for founders One of my favorite things about building @supercruisecap is identifying what founders want in this new world and providing that While our target is different, providing an alternative to VC that founders actually want is wildly fulfilling

3/3: Adapt or swing at bad pitches. The best will extrapolate maturity from early signals—and hit home runs in this new game. Full post here: open.substack.com/pub/theafterbu…

2/3: Traditional diligence misses these rockets. By the time the spreadsheet looks "perfect," the valuation is too high or the round's gone. Winning investors need to adapt to a hybrid model: use VC-style product/customer deep dives + growth modeling to underwrite the slope, not just the past.

Thread 1/3: Ted Williams knew his batting average in every part of the strike zone—and crushed .400 in his power zone. Growth equity needs the same adaptation today. AI is accelerating startup scaling: $10M ARR in months, not years. The old "wait for 3 years of data" strike zone? It's shrinking fast.

There’s been a lot of political rhetoric (e.g., @SenSanders ) suggesting that the rise of AI and associated data centers is causing skyrocketing electricity costs for average Americans. The data and industry direction tell a very different story — one where technology companies are investing in new generation energy capacity, grid upgrades, and future-proof power solutions rather than simply drawing down community electricity at the expense of residents. @DavidSacks 1) Small Modular Reactors (SMRs) — real traction, not hype SMRs have moved from concept to real commercial development around AI data center energy needs. Tech companies have committed more than $10 billion, and at least 22 GW of nuclear generation capacity is in development, targeting data centers and AI infrastructure by 2030. * Significant partnerships are underway — @amazon, X-Energy, KHNP, and @doosan_skoda are targeting up to 5 GW of SMR deployment across the U.S. by 2039. * @Google signed a corporate agreement to purchase SMR power from @KairosPower, and Amazon and others are locking in long-term SMR energy deals to underpin data center campuses. * Industry estimates note expressions of interest for ~30 GW of SMRs with 100+ reactors under development globally — all tied to future grid and data center needs. These aren’t science-fair concepts — they’re industry commitments to build new, carbon-free clean power capacity, directly offsetting any incremental demand from AI compute. 2) Big Tech adds power capacity — and even helps lower costs Refuting the claim that AI data centers jack up bills: * A Lawrence Berkeley National Lab analysis shows that data centers (e.g., Amazon) pay their own full electricity and infrastructure costs, often more than necessary, and that utilities can use the resulting revenues to modernize local grids, benefiting all customers. * In some regions, large industrial loads (like data centers) have actually moderated or lowered electricity rates, because expanding generation and hardening transmission improve overall grid efficiency and capacity. * @ENERGY Secretary recently stated that data center buildout stimulates more power production overall — a factor that can reduce net electricity prices over time as capacity expands. The real reason electricity costs have risen is multi-factorial (aging infrastructure, adjustments to extreme weather, etc.), not solely AI data center demand. 3) Regulation like Texas’s isn’t about taking energy from residents — it’s about grid responsibility Texas’s new Senate Bill 6 reforms large-load interconnection standards, requiring big energy users, including data centers, to pay for necessary grid works and share in transmission costs — not shift them to residential ratepayers. This law ensures that large users contribute to upgrades rather than simply drawing power without system cost accountability. 4) Real Innovation: Supersonic Jet Tech Powering AI Data Centers One of the most interesting developments in the industry comes from @boomsupersonic, the supersonic aircraft technology startup that spun out a power generation arm called Superpower: * @superpower is a 42 MW natural gas turbine derived from the same core technology being developed for Boom’s Symphony supersonic aircraft engine, repurposed to generate electricity for AI data centers. * These turbines pack that capacity into a shipping-container footprint, are designed to deliver full output even at high ambient temperatures, and don’t require substantial water inputs — addressing typical constraints in traditional gas turbine design. * @CrusoeAI, a leader in “energy-first” AI infrastructure, has already secured contracts for 1.21 GW of these Superpower units, with deliveries starting by 2027 and manufacturing geared to 4 GW annually by 2030. This innovation underscores a broader trend: AI infrastructure is not limited to pulling electrons from the grid; it’s driving new-generation technology — including novel turbine designs and SMRs — that expand total power capacity. 5) Real cases illustrate innovation — and challenges — in powering data centers @elonmusk @xai The data center in Memphis has used on-site gas turbines in the short term because the grid supply wasn’t adequate — highlighting why the industry pushes for dedicated, cleaner power capacity rather than draining shared grid resources. 6) The broader tech energy strategy: ‘all-of-the-above.’ Tech companies aren’t just drawing power — they’re constructing new generation capacity, integrating renewables, expanding nuclear, and updating grid infrastructure to ensure their AI workloads aren’t simply parasitic loads that burden households. Net net: AI data centers do not inherently raise electricity bills for average citizens — nor are they uniquely to blame for recent grid cost pressures. The industry is investing in new generation (including SMRs), paying for grid upgrades, and expanding overall energy capacity with long-term, clean, and reliable solutions. Unfounded claims that AI equals higher household electricity costs should be met with scrutiny and facts. Cited URLs: introl.com/blog/smr-nucle… — SMR commitments and tech investment x-energy.com/media/news-rel… — SMR partnership news aboutamazon.com/news/sustainab… — Study on data centers and grid costs texaspolicyresearch.com/texas-data-cen… — Texas SB6 interconnection rules wsj.com/articles/energ… — Energy Sec on cost impact datacenterdynamics.com/en/news/elon-m… — Coverage of Elon xAI infrastructure Boom Supersonic Superpower turbine details— boomsupersonic.com/press-release/… Superpower turbine optimized for AI power generation — boomsupersonic.com/superpower Analysis of tech energy demand and solutions — newatlas.com/energy/boom-su… Crusoe’s 1.21 GW Superpower turbine order — datacenterdynamics.com/en/news/crusoe… Fusion Cyber view: How many AI Agents have each of your developers built this year? We are at 40+ AI Agents per developer! Stay sharp, Fusion Cyber AI, Training talent. Operationalizing AI. Powered by @fusioncyberco fusioncyber.ai

We learned this week that Aumni (@getaumni) by J.P. Morgan is being discontinued. Aumni was an early pioneer in the VC software space, and we have deep respect for what their team built. We’re wishing everyone there the best as they navigate this transition. We understand that this change may create stress for portfolio operations and finance teams who rely on Aumni for consistent access to portfolio data, especially with Q4 close and audits approaching. Per Aumni’s customer communication, portfolio data processing will end in mid-January, and the platform will shut down at the end of March. We've been in touch with many Aumni customers and team members over the past couple of days, and it's been wonderful to see the community come together and support each other. If you’ve been affected in any way and are evaluating continuity options, whether with Standard Metrics (@metrics_co) or elsewhere, our team is here to help however we can. Please feel free to reach out to me or anyone at Standard Metrics.