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The ServiceNow team is raising the bar by innovating on our own platform, taking an end-to-end agentic AI-first approach to running our business. We see this in a 16x improvement from lead-to-sale conversion & an over 86% deflection of the soul-crushing work people used to do themselves. ServiceNow reported earnings yesterday alongside Google & many other companies. All the insights out of those reports were interesting, but this was the one that stood out the most to me.
When you buy a stock or a bond, do you know which database that transaction is running on? I’m sure the answer is no, but the database will change & that has far-reaching implications. data via Allium Blackrock’s tokenized Treasury fund, BUIDL, has amassed $2b of treasuries so far, with a recent significant surge. This fund is still a bit smaller than BlackRock’s classic Treasury Fund BYTXX at $21b. Tokenized assets, stocks and bonds on blockchains, are at just the beginning.
Two years ago I published an image of a rabbit on a fire truck to demonstrate how effective image generation was for blog posts. The conclusion at the time : the images were unusable. In 2025, the opposite is true - with one caveat. Prompt: Coupa & Thoma Bravo logos each in front of a cloud with a plus sign between them. 2023 2025 Two years has brought tremendous professionalism to new image.
Software systems work best when they’re connected to each other. For years, incumbents use deep integrations as a competitive moat. But AI upends this dynamic. A few of our portfolio companies are starting to develop integrations with AI in a matter of hours, completely upending the two or three quarter timeframes of classic enterprise integration development. This enables two important impacts to the sales cycle. First, the integration a customer desires can be built during the sales cycle, demonstrating the startup’s technical agility.
I want to see how you use AI. The biggest challenge to AI adoption is reimagining workflows, AI is best discovered socially. Midjourney’s launch on Discord was brilliant. As a new user, I knew enough to ask for an image of a rabbit on a firetruck. But by watching others, I discovered I could create vector images, recast photos into Ghibli-style art, change aspect ratios, or convert photos to pencil-shaded drawings.
We don’t often hear the words speed & ERP in the same sentence. But when researching Doss, we heard it again & again. We’ve always believed fast sales cycles create competitive advantage - nowhere is this more true than enterprise software. Imagine purchasing software knowing there’s a 75% chance it won’t deliver value after a 12-month deployment. If selling software is the business of selling promotions, traditional ERP offers a ponderous path to career advancement.
I’ve been watching my behavior evolve as I use AI more. Coding new projects, I started first by describing a big idea : generate a new website that ingests podcasts and transcribes them. But I quickly discovered this approach was like asking someone to build a skyscraper without blueprints—the AI choked on requests too broad & lacking structure. So I broke the project down into smaller blocks. Write a function to download the list of podcasts in the last week from these sites.
Pricing is one of the most complex topics in software. Changing pricing is never simple. It is a company-wide evolution that has the potential to completely reshape your entire business & your customer relationships. Few have executed this transition better than Barr Moses, Co-Founder & CEO of Monte Carlo. Join us for a candid conversation with Barr as she shares how Monte Carlo transitioned from ARR to daily revenue as the core operating metric for the business.
With another tariff induced red-tinged day hammering markets, I wondered: Do private markets follow public ones? The data suggests yes—but with a delay & at a fraction of the magnitude. A 1% increase in Nasdaq’s (QQQ) quarterly return translates to a 0.47% rise in median Series A valuations—but only after a two-quarter delay. The inverse holds true as well: when public markets contract, private valuations follow suit approximately six months later at roughly half the intensity.
The new tariffs have markets down broadly. What do they mean for startups?1 In terms of first order effects, tariffs can impact a startup in two ways : the input costs and consumers’ demand. Most software companies don’t import or source critical components of the software from abroad so the COGS / gross margin structure of the company shouldn’t change unless they rely on significant hardware purchases, for example GPUs or robotics components.
We’re excited to announce our Head of AI, Bryan Bischof, and our first entrepreneur in residence, Philip Zelitchenko. A practicing professor of data science at Rutgers and a Math PhD, Bryan has spent the past two decades building AI and data science practices across thought-leading startups, including Hex, Weights & Biases, Stitch Fix, Blue Bottle Coffee and many others. Recently, he published his learnings on a year’s worth of learnings building with AI here.
As startups scale, effective sales implementation becomes the difference between stagnation and sustainable growth. After analyzing hundreds of sales organizations across startups, I’ve distilled the key pieces of advice that founders and leaders should keep in mind. 1. Sales Strategy Fundamentals Start with the right price: Establish pricing that reflects value rather than just covering costs. Define your ICP: Clearly identify your ideal customer profile before building your sales process. Understand sales velocity: Recognize that sales success depends on both deal size and deal frequency—optimize for predictability.
As AI capabilities accelerate, effective implementation becomes the difference between wasted investment and transformational success. After analyzing hundreds of AI deployments across startups, I’ve distilled the key pieces of advice that founders and leaders should keep in mind. 1. AI Strategy Fundamentals Start with the problem: Define specific business challenges before exploring AI solutions—not the other way around. Build or buy decision: Evaluate whether to develop custom models or leverage existing AI platforms based on your competitive advantage.
71% of exit dollars in 2024 came from a new avenue : secondaries. Historically, IPOs and M&A have been the dominant exit paths for venture backed companies. Some years IPOs dominate, other M&A dominates, but in 2024 secondaries captured the super majority. When a company sells new shares to investors in exchange for dollars, they create new shares in the company - primary shares. When existing shareholders sell their shares to new investors, we call this a secondary sale.
You have to pay a price for your distinctiveness, and it’s worth it. The fairy tale version of “be yourself” is that all the pain stops as soon as you allow your distinctiveness to shine. That version is misleading. Being yourself is worth it, but don’t expect it to be easy or free. You’ll have to put energy into it continuously. The world wants you to be typical – in a thousand ways, it pulls at you.
What is a webinar in the age of AI? It’s a blog post. And a podcast. And a video. And a meme. Let me explain. For many webinars, I’ll send a notetaker in my place, a robot to record the conversation & summarize it in the way I ask. A personal journalist in a sense. Instead of watching & listening to a conversation, I’m transmogrifying the subset of the content that matters to me into the format I prefer : a summary in a template, in other words, a blog post.
I remember the day I received it : my first Blackberry. A few weeks later I lost it in the back of a taxi cab in Paris. But I haven’t forgotten the chiclet keyboard, its subtle click with each keypress. A year later, the iPhone presented the world with an all glass keyboard. Who would type on a flat surface, detractors asked? In the end, all of us. This week, I saw another user interface for a phone : dictation only.
Is tech M&A back? Google announced its intention to buy Wiz for $32b today. If approved by regulators, it would be the 6th largest technology M&A ever. This transaction would make Wiz the 5th most valuable pure-play security company. For Google, this would be its largest acquisition ever second to Motorola for about $12b. Notably two of the top three acquisitions are security. Mandiant sold for $5.4b. Why should Google be so interested in security?
Engineering teams within AI application startups are much smaller than a classic software company - maybe half the size or less. Let’s run an experiment : let’s assume every public software company benefits immediately to the same extent & cuts R&D spending by half.1 How would the value of these businesses change?2 72% of unprofitable SaaS companies would become profitable. The typical SaaS company would increase from 4.4% net income margin to 15.
Public SaaS companies’ growth rates have halved since 2023, as David Spitz pointed, from 36% to 17%. Why? There are few, fast growing, younger SaaS companies to sustain the growth rates. The top quartile companies are growing at slower rates today than the bottom quartile companies in 2016. The median has never been lower in the last ten years. It’s not to say software spending is slowing (it’s not), or that there aren’t fast-growing businesses (they thrive in the private markets).
Monday’s analysis cost about 27 cents to produce. This little screenshot is of Claude Code, the product I use now to write the analysis of datasets like estimating the value of a venture firm. I didn’t expect to find this feature initially as useful as I do now. But it makes me feel great because of how inexpensive it is to be productive. 27 cents for a statistical analysis of a small dataset is a bargain considering the battery of statistical tests the AI applied.
How do you position and scale an AI company in a rapidly evolving market? Join us for an in-person Office Hours session in San Francisco with Alan Hsia, VP of Marketing at Fireworks AI. Alan brings deep expertise in go-to-market strategy and will share insights on: Building a strong brand in AI from the early stages Creating a differentiated GTM strategy to create distance from competition Aligning marketing with sales for maximum growth This session is designed for early-stage AI founders looking for tactical advice from a seasoned Marketing & GTM leader.
A small spin-out from a publicly traded behemoth launched with the ambitious vision of transforming their entire industry. Within just a few years, as capital markets shifted in their favor, they emerged simultaneously as both innovators & titans in their field. We don’t often think of private equity this way, but that’s exactly what happened when KKR spun out of Bear Stearns and Michael Milken at Drexel Burnham Lambert catalyzed the junk bond boom of the 1980s.
Imagine if every time you edited a document, the word processor forced you to retype everything that had been written before that edit. How expensive would that be for a company? This is exactly how data transformation works today. Each time a data engineer modifies some part of the data stack, the Cloud Data Warehouse & its transformation layer recalculates everything. What if the system were designed so that it only recalculated the metrics needed?
As startups scale, effective management becomes the difference between chaotic growth and sustainable success. After analyzing hundreds of posts on startup management, I’ve distilled the key pieces of advice that founders and leaders should keep in mind. 1. Management Philosophy Management is a design pattern: Just like engineering has patterns, management has best practices that can be learned and applied systematically. Use Situational Judgement: tailor support for employees ranging from micromanagement for new hires to hands-off for high performers.
Which is the best business in AI at the moment? I analyzed Q4 revenue data from publicly traded companies across multiple sectors—software companies, consulting firms, and hardware manufacturers to determine which segment dominates the AI market. NVIDIA’s data center business dominated the field, generating $31b in Q4 revenue with impressive margins exceeding 70%. In second place, Microsoft’s AI business, including Azure, is at a $3.25b Q4 revenue. IBM reported $2b, which was a big surprise to me.
During a recent Theory Office Hours with Kady Srinivasan CMO at Lightspeed Commerce, Dropbox, and Klaviyo, we discussed several powerful insights emerged on how early-stage companies should approach marketing. Here are the highlights : Define Your ICP Before Anything Else The most fundamental decision for any startup is determining your Ideal Customer Profile (ICP). Without clarity on exactly who you’re targeting, GTM efforts become diluted and ineffective. The earlier the company, the narrower it should be.
Most startups play defense when discussing pricing with customers. They dance between asking for too little, leaving money on the table, and asking for too much, only to lose the customer’s interest. The very best companies lead their customers in that dance. They use pricing as an offensive tool to reinforce their product’s value and underscore the company’s core marketing message. For many founding teams, pricing is one of the most difficult and complex decisions for the business.
Chegg filed suit against Google for changes in their algorithm forcing the company to consider a sale. They allege the Google AI Overviews feature displays Chegg’s AI-enabled Q&A homework helper. This suit stands as the first of its kind challenging Google for changing search patterns, but it won’t be the last. The data tells a stark story. Looking at Chegg’s traffic using SEMRush analytics, their organic traffic has dropped from 5.
Algorithms needed for unpredictable journey. Significant compute costs, endless data processing, long periods of unexplained failures. Safe convergence doubtful. Honor & recognition in event of success. What Shackleton might have written in 2025. AI isn’t perfect but its productivity gains are undeniable. ServiceNow, Microsoft, and Amazon, plus nimble startups generating tens of millions in ARR with teams small enough to feed with a few pizzas all have benefitted. The new boast of 2025?
A decade ago, most startup pitches ended with a calculation justifying the amount they sought to raise. In other words, the raise was an output of the financial model. But for the most sought after companies, the raise amount is disjointed from the capital needs of the business - instead it’s driven by the fundraising auction. Great fundraisers are the teams that build the most auction pressure. This auction dynamic, combined with venture capital’s explosive growth over the last decade, has transformed fundraising strategy.
October 2024 marked a critical inflection point in AI development. Hidden in the performance data, a subtle elbow emerged - a mathematical harbinger that would prove prophetic. What began as a minor statistical anomaly has since exploded into exponential growth. Since then AI performance has surged attaining a new trajectory, a new slope - no longer linear but geometric. Segmenting out the models by size & type reveals a striking shift in innovation’s source.
For pre-seed to Series B founders, navigating GTM strategy, marketing, and positioning can be challenging. When should you hire your first marketing leader? How do you scale GTM efficiently? When is the right time to invest in branding? To help founders tackle these challenges, Theory Ventures is hosting exclusive 1:1 Office Hours with Kady Srinivasan, former CMO at Lightspeed Commerce and GTM leader at Dropbox and Klaviyo. Kady has led GTM teams that scaled revenue from $150M to $600M ARR, drove successful IPOs, and optimized marketing efficiency at scale.
Theory’s name isn’t just a name - it’s our ethos. We develop & test theories about the future of technology, business, & venture capital through constant experimentation. We’re seeking an architect of the future, someone who thrives at the intersection of AI & process design. Ideally, this person : enjoys architecting processes and implementing them with a team is relentlessly curious about new technologies & techniques has a good understanding or desire to learn about great sales teams thrives in a warm, collaborative, & urgent culture Apply here if you’re interested.
Cloudflare’s earnings last week revealed something more significant than just company optimism: a fundamental shift in software buyer confidence. “However, as the quarter progressed, we saw encouraging signs that confidence is beginning to return, particularly in the U.S. Security, AI, modernization and efficiency form the word cloud we hear most often in these conversations. These themes play directly to Cloudflare’s strength.” Sales cycles are accelerating. “Beyond the qualitative, we saw measurable improvements in Q4.
Web3 is putting up real revenue numbers. Over the last 30 days, the top 20 public Web3 projects generated $1.2B in revenue. This isn’t some theoretical valuation metric. This is hard revenue, derived from trading and other financial fees. And it tells a compelling story. A power law is clearly at play. While we might expect this in a nascent market, the sheer scale is impressive. Even the smallest project on this top 20 list is running at a $75M annual run rate.
What is the impact of AI across different levels of seniority? Over the weekend, I read Sergey Tselovalnikov’s post on AI Impact Curves. The software engineering curve reveals an intriguing pattern. Junior engineers experience both benefits and risks from AI. Staff+ engineers also gain tremendous leverage at the senior end of the curve. However, mid-level engineers see more modest impacts, primarily because they are proficient with their codebases and can write effective code adeptly.
Google’s earnings call identified some major changes and unexpected outcomes, including the performance of AI Ads, the importance of hardware compared to algorithmic efficiency gains, and the groundswell of developer adoption for Gemini models. AI algorithms have had a thousand times reduction in inference cost over the last three years. There is another cost reduction curve, which is the compute per watt of electricity. Google reveals that this is decreasing at half of the rate of algorithmic efficiency.
AI startups represent about 70% of B2B Series As, up from about 40% in early 2024. On average, AI Series As raise at 40% higher valuation than non-AI companies, a multiple that has been increasing over time. But this is less of a premium than in the public markets. As of January 31, an AI publicly traded software company trades at twice the multiple of a non-AI software company. Forward ARR Multiple
Microsoft announced earnings yesterday & the data painted a brilliant picture for the future of AI. Greater than 30% annual growth in back-to-back quarters is sensational for a $100b run rate business. Microsoft is projecting similar for next quarter. The AI subset is on a $13b run rate, more than double last year. Azure other cloud services revenue grew 31%. Azure growth included 13 points from AI services, which grew 157% year-over-year, and was ahead of expectations even as demand continued to be higher than our available capacity… In Azure, we expect Q3 revenue growth to be between 31% and 32% in constant currency driven by strong demand for our portfolio of services.