Consensus Long

… and yet $RDDT trades at less than 20x NTM EPS which makes no sense… easily one of the most undervalued growth stocks in this market with multiple catalysts on the horizon… 1+ billion MAUs… the fastest growing ARPU… new licensing deals with the LLMs… expanding margins… only $10-12M of annual capex

Over the last 12 years, I've worked with 4 Private Equity funds at ZoomInfo. Here’s my 12-step playbook for working with PE Owners. In 2014, I took on my first PE investors (TA Associates and 22C Capital). In 2018, we brought on Carlyle and CPPIB. Private Equity is in the headlines everywhere now - buying businesses like Smartsheet, Zuora, SolarWinds, Avalara… Here are lessons I learned on how to make working with them a LOT easier. 1. Get aligned from Day 1 Ask them what they underwrote the deal to. That’s a fancy way of asking: “What did you tell your investment committee this business would be worth in 4–5 years in the base case?” Then ask about the upside case. If you want real alignment, ask for the memo. If they get squirrely, just say: “I assume there might be some misgivings about me in there - can we talk about those so I’m aware?” There is no faster way to get aligned than seeing exactly how they described the investment. 2. Understand the clock If you want to invest in growth and bring down margins to do it, do it early. As you approach exit, EBITDA becomes a sacred cow. Want to launch a new product? Great. Show what sales is committing to it and when. If you can’t do that, don’t even bother asking. 3. You don’t have to do everything they tell you After my second board meeting I went to D. Randall Winn (my PE board member and CEO of S&P Capital IQ) and said, “Randy, just tell me what you want me to do and I’ll go do it.” He laughed and said: “Whoa whoa, that's not how it works - no one here knows your business as well as you do. We’re going to give you advice and pattern match. Your job is to listen and decide.” That said, you MUST listen to their advice and explain your choice. This doesn't have to happen immediately. Try phrases like this: “I hadn’t thought about that - it’s a good point, I want to take some time to think it through and get back to you.” Then actually follow-up. 4. You NEED a strong CFO and FP&A team Most of your private equity investors’ interactions are with your CFO. A strong CFO and FP&A team build trust. They help you craft strategy around data AND they're endlessly valuable to your PE partners because they can build models and get them the data they need to understand what’s happening in the biz. This makes life easier for you and them. 5. Response time matters PE employees work all hours. One of the associates on our deal told me that she was sleeping in her car outside their office for ~2 hours and then starting to work again cause she didn’t want to waste 30 mins driving home. When they email asking for clarification or making a suggestion, respond fast - even if it’s just to say you’ll follow up. 6. Send them swag This one might sound dumb, but you want them to FEEL like they are on your team. When you get new swag, put it in an envelope and send it with a nice note - you want them to feel the same level of pride you feel in your company. 7. Expect pressure to do M&A I remember being at a PE conference where they flashed a slide showing that portfolio companies that did M&A far outperformed the ones that didn’t. Every firm had the same slide, they all believe it and you should expect pressure here. 8. Be prepared to offshore They believe deeply in offshoring because labor offshore can be equally talented at 1/2 to 1/3 the cost. There is an organizational tax that comes with this, you can’t negotiate it away. You just have to prepare the company to manage it. 9. When a metric goes sideways, don’t show up like a macho man If you show up with a confident solution, you’re begging for a fight. Instead: present the metric, share POTENTIAL hypotheses, explain what you’re testing and ask what they think you might be missing Make them partners in solving, otherwise you’ll quickly turn them into adversaries poking holes. 10. Cutting costs is easier than driving growth This is just objectively true. If your strategy increases costs in the hope of faster growth, you need to answer two questions: - What metrics and checkpoints will tell us this is working - and when do we kill it if it’s not? - Does the additional growth actually change the multiple and valuation of your business? If you go from 15% to 20% growth in an EBITDA-dilutive way, you may have made the business worth less, not more. Your PE partners will care a lot about this. 11. They LOVE pedigree. Hiring someone from Stanford or Salesforce is almost never questioned. But take a risk on a state school or a non A-plus company hire and you’ll be defending that person even in good times - your job is to build the best team you can so the price of doing that is owning those hiring decisions at the board level. 12. Relationships matter There were a handful of times where I knew that I got on the wrong side of one of my PE board members. So I would tell my wife, “hey listen, I’m flying to San Francisco or New York on Sunday and I’m going to have breakfast with them and then fly home.” Then I’d call them and just say “Hey, do you have time for breakfast on Sunday? Maybe a workout before.” They always said yes and it gave me 4 hours of time, some relationship building and then we got right into the reasons we were misaligned and what I could do better. These were super valuable - don’t EVER underestimate the power of getting in person with your partners - same rule applies to your team. The thing I loved about working with Private Equity is that there is no singing kumbaya pretending we are some happy family. It’s a 4-5 year relationship and the expectations are very clear. I really appreciated that.

$NRG $CEG $TLN $VST Why I am no longer long IPPs and even leaning slightly short (especially $TLN) ahead of what could be a very negative headline catalyst next year

You are about to see hundreds of Nick Shirley imitators flood social media and YouTube. They will go all over the country trying to expose the insane fraud and wasteful spending. The incentive to capture millions of views is too great to be ignored by a generation of young people who treat views like oxygen. Nick’s single video will spawn thousands more. But what is fascinating about that development will be the realization that a decentralized DOGE effort can’t be defeated by bureaucrats and politicians. These establishment people could stop DOGE because it was a centralized organization that had a clear leader. Take down Elon and resist DOGE for the first few months…that was the winning strategy. You can’t resist or defeat a decentralized onslaught of hundreds of young people running around with cameras though. And Nick just showed a generation how many views they can get if they can uncover fraud and wasteful spending. Sunlight is the best disinfectant and the sun is about to get VERY bright.

This one is for all the AI Capex bears 1% of GDP today versus 2-5% of GDP (peak) for other major technology investment cycles. *If* we are in a bubble still have a hell of a long way to go to the top $CLS $AMD $NVDA $VRT $AVGO $HUT $APLD

Why AI is Underhyped and Isn't a Bubble Yet Here's why AI isn't a bubble today. I've distilled the data points and ideas from my previous columns and coverage. If you prefer facts and evidence-based reality over vibes and conflated narratives, enjoy! -Big Tech valuations are reasonable and leverage is low. We're at the beginning of multiple AI super product cycles in the year ahead -We are in the early innings of a technology computing shift to AI, the largest in decades. Think 1994 versus 1999. -Every credible source reports overwhelming demand for AI computing capacity. Where is the overcapacity glut? Nowhere. Valuations -During the dotcom bubble, top technology stocks like Microsoft and Cisco traded at 70 to 100 times forward P/E in December 1999 (remember these stocks went significantly higher in Q1 2000 too) versus today's top stocks (Nvidia etc.) trading at 30x with materially better underlying fundamental growth prospects. -The positive cycle sentiment remains in early stages. The Netscape IPO occurred in 1995, five years before the cycle peak. Is there any doubt the eventual OpenAI IPO will be a Netscape-type success? AI is only two to three years in. Think 1994 versus 1999. -The major buyers of AI infrastructure are the most profitable businesses in history, each generating roughly $100 billion in annual net profit. This is nothing like the debt-driven fiber optic network buildout of the dotcom era. Generational Secular Computing Shift -The global TAM for IT spending is $5-6 trillion annually. The entire technology stack needs restructuring and rearchitecting for AI because this new technology produces better results for corporations and consumers. You either use it or get disrupted by rivals who do. -Think electrification. Think the advent of the microprocessor and personal computer in the early 1980s. It's that significant. -The first growth wave was driven by natural language processing with LLMs and the application of parallel GPU computing. For the first time, computers could understand context from user language input. Previously, if you typed one character wrong in a query request, the computer would fail. GPUs allowed companies to apply incredible computing power to distill and compress knowledge from vast pools of unstructured data. -The current second wave of growth is driven by reasoning models that are significantly more accurate and useful by spending more time working on requests and searching dozens of websites. Reasoning models use 100 to 1,000 times more compute resources than prior models. The next wave will feature increased use of multi-modal models (audio/video) and agents (workflow automation, multi-step tasks). The following wave will be driven by physical AI, drug discovery, factory simulation, and robotics. AI Bubble Skeptic Arguments -Skeptics focus on simplistic narratives without nuance. It's up a lot, so it must be a bubble. OpenAI is losing a lot money! -This mirrors narratives from earlier this year when skeptics claimed the DeepSeek moment meant expensive training runs were no longer needed because DeepSeek was trained with only $6 million in spending (a false statement especially as literally in the same week China announced $140 billion in new AI investment). They also claimed DeepSeek's efficiency meant a computing glut was ahead. Both views proved categorically false and misleading as reasoning models (including DeepSeek!) and better AI models sparked an exponential wave of AI computing demand over the last nine months. -OpenAI's business model divides into two parts. Training new models requires enormous fixed investment, with each model driving roughly 10x more spending. Inference, serving already developed and built models, is extremely profitable. -Do you believe leading AI edge models will be a foundational technology transforming every business worldwide? The answer is yes. Companies view the risk as existential. -100% of Nvidia's engineers use AI coding assistants like Cursor. These AI assistants make engineers more productive by autocompleting code and automatically fixing bugs. All developers will use AI assistants in the future. Customer service? Same. AI will improve chatbots for customer service while giving live agents all the information they need from prior conversations and the latest product updates to improve service quality. Sales agents? Same. Product research and development? Same. AI will test product ideas and iterations while simulating every permutation. -This is happening and will continue happening. It’s inevitable. Every company will use AI in every part of their business. I spoke with executives from Nvidia, Dell, and Microsoft this month. It's occurring everywhere and accelerating. Circularity -Thus far, the vast majority of spending has come from profitable large technology companies. Now concerns about circular vendor spend is rising. -Despite what you hear, much of this hasn't occurred yet, and each gigawatt of spending depends on specific performance technical milestones on both sides (AMD-OpenAI deal). -Yes, the Oracle-OpenAI deal is real with hundreds of billions in RPO. Let's assume it's $300 billion over five years, requiring roughly $60 billion annually. -Alphabet/Google generates about $400 billion in sales with $120 billion profit. Meta generates $200 billion in sales with $73 billion profit. -Markets and investors look at the potential future not the present or past. The question becomes can OpenAI eventually become a technology giant using their AI model advantage and product execution abilities? ChatGPT's user base has grown from 0 to 800 million in three years. Can it reach 2 or 3 billion in another three years? It seems achievable. Like Google in its early years, ChatGPT currently has a scale advantage where the large user base has started a flywheel, enabling ChatGPT to iterate, improve, get more data, and A/B test better answers for users. Nvidia NVL72 Super Cycle – Pre-iPhone Moment -Dan Benton noted that technology investing revolves around product cycles. In just over two years, Nvidia has increased its quarterly data center revenue tenfold. As impressive as this is, the company will likely experience its best product cycle ever over the next few quarters, comparable to the iPhone launch. -Nvidia has recently begun shipping GB200/GB300 NVL72 servers in volume for the first time. Foxconn, a major AI server manufacturer for Nvidia, reports that current quarter AI server revenue will increase 170% year-over-year. -What is the NVL72? The first AI server with 72 GPUs in one server rack versus 8 GPUs in prior models. It offers 25 to 30 times better performance than the previous model and will enable more AI capabilities and use cases. Each server weighs 1.5 tons, contains 5,000 copper cables (2 miles), and offers unprecedented computing density. AI Demand Signs -EVERY credible industry source reports off-the-charts demand and overwhelming compute shortages everywhere. EVERY SINGLE ONE. -Microsoft's Scott Guthrie, head of the Cloud + AI group at Microsoft and member of the senior executive team, told me this month he sees an "explosion" of AI infrastructure usage ahead, driven by reasoning/agents and workflow automation. -TD Cowen: "Based on our checks, 3Q25 would represent the largest inflection in demand we have seen since the inception of the data center industry... a staggering ~7.4GW of U.S. data center capacity was leased by hyperscalers in 3Q25, which would exceed all capacity leased in 2024." Largest inflection in demand in history. Right now. More capacity in one quarter than all of last year. -TSMC's CEO says AI demand is "stronger than" they thought three months ago. Given the strength three months ago, that's remarkable. He then literally describes today's growth as "insane," strongly hinting at guidance and capex raises in January. -Four-year-old A100 GPUs remain profitable today on inference tasks. -Microsoft AI startup employee states: "Many days it feels my whole job is begging for GPUs. It's been that way since 2020 and hasn't become easier." -Anthropic's ARR grew from $1 billion to $7 billion in 10 months. -Crusoe CEO: "Every single customer we talk to is compute-constrained right now." -AI token consumption data points from Microsoft, OpenAI, and Google show exponential growth YTD. Conclusion -Hold on to your hats. We're just getting started. The next several quarters are going to be off the charts.