Posts

Measuring engineering productivity is a Gordian knot.

How does a manager measure the performance of an engineer? Lines of code, like lines of a blog post aren’t a good metric. Most of the time, short, direct prose is better than verbose or lengthy sentences that carry on forever because they haven’t been edited & really ought to be, but someone was rushing or forgetful, & they lose the reader along the way.

Companies aren’t bought. They’re sold.

Hang around startups & venture capital long enough, & you’ll hear this aphorism. It means it’s much easier to sell a company when there’s plenty of demand.

In any given year, there’s an 82% chance the value of startup liquidity will change by more than 77% - both up & down.

Aside from certain crypto tokens, it’s hard to find a less reliable market than the VC exit market.

Every year I make a list of predictions & score last year’s predictions.

Here are my predictions for 2024.

1. The IPO market remains closed through the first 6 months of the year. But a few mega issuances, especially Stripe & Databricks in the summer or fall, re-open it for others. The Fed cuts rates, which helps.
2. M&A accelerates throughout the year. The anticipation of a rate change drives fear of target acquisition valuations. In the last two years, M&A has totaled about $49b & it surges to above $60b driven by AI acquisitions. PE becomes an important buyer of companies growing 10-25%, as it did in 2018, driven by lower debt costs.
3. AI & data continue to dominate the funding landscape as founders & investors seek novel applications of the technology. A handful of companies achieve record-setting growth rates.
4. The share of AI-enabled web searches approaches 50% of all consumer search as consumer behavior patterns evolve, especially on mobile.
5. The BTC ETF drives a resurgence in interest in web3 financing. The winter forced many companies to evolve from open-source projects to revenue-generating businesses. We see the first broadly successful tokens with dividends (likely outside the US). This innovation reinvigorates very early-stage IPOs. We also see more ARR-based web3 businesses achieving scale. Record inflows into tokens fuel all-time highs in Bitcoin, Solana, & higher performance L1s who offer better price/performance to market.
6. US VC investment falls from $275b in 2022 to $200b in 2023 & sustains at about $200-220b in 2024 as LP interest in venture attenuates after the euphoria in 2020 & 2021. Valuations remain relatively steady except for AI businesses, which command a premium to market of about 10-25%.
7. The discussion around AI regulation becomes a critical topic in the US during the election because machine-generated content exacerbates international meddling in US politics. But the overwhelming desire for the US to continue to lead the innovation wave it started creates safe harbors, the same provisions which enabled the web to flourish, are applied to AI.
8. Companies & startups in particular begin to report meaningful improvements in productivity from AI, reducing their headcount growth, but growing revenue just as much as projected. ARR per employee increases 10%, twice the decade long average.
9. Data lakes become the dominant data architecture across business intelligence & observability workloads as more startups leverage Amazon S3 free replication. Cloudflare R2’s architecture for very large data sets drives a meaningful growth in its usage, predominantly for AI.

Grading last year’s predictions :

Earlier this week, Alteryx announced its intention to go private for $4.4b. It’s the 10th in 2023.

In December of last year, I wrote :

Private equity acquires 10% of the 70+ publicly traded software companies by the end of the year. With hundreds of billions of dry powder, plenty of healthy cash flows generated by SaaS publics, & the leverage of the inevitable shareholder lawsuit if a board rebuffs the 30% premium of a tender offer, private equity becomes the dominant M&A option in dollar terms for 2023.

Data teams are becoming software engineering teams.

On December 14th we welcomed Philip Zelitchenko, VP of Data from ZoomInfo, to talk about how he has built this discipline within his team & it was fascinating. The video is here.

Like the Devops movement, the Dataops movement aims to scale the use of data within companies without increasing the headcount of the data team.

I had pre-ordered Poor Charlie’s Almanack before Charlie Munger died & read it when it arrived.

In the ten speeches that constitute the book, Mr. Munger reveals his frameworks for life.

Mr. Munger was known for his worldly wisdom, a collection of mental models that helped him think about the world. Compound interest, confirmation bias, & something he calls the Lollapalooza effect - human psychology that shapes human behavior. Tulips, cryptocurrency, & cola all fit into this effect.

The typical software startup raised their Series A 15 months after raising their seed at 2x their seed valuation.

A year ago, that Series A would have been raised three months earlier at 3.5x the valuation.

Here’s another way of visualizing the data. The red dot is 2023 - the other years are in grey. Across rounds for the 50th & 75th percentile of companies, step-up valuations are the lowest multiples in about ten years.

The future of LLM evaluations resembles software testing more than benchmarks. Real-world testing looks like this, asking LLMs to produce Dad jokes like this zinger : I’m reading a book about gravity & it’s impossible to put down.

Machine learning benchmarks like those published by Google for Gemini2 last week, or precision and recall for classifying dog & cat photos, or the BLEU score for measuring machine translation provide a high-level comparison of relative model performance.

Mongo announcing earnings yesterday concludes this quarter’s index of software buyers.

As the chart above shows, the software market is plateauing & some companies are rebounding.

Why is a flat growth rate something to cheer?

First, 30% growth is now top quartile.

Second, each of these businesses has scaled, doubling or more in the last three years. A 30% growth on twice as large a revenue base signifies many buyers are ready to spend.

These are the top 10 posts by engagement for 2023 at tomtunguz.com.

Reflecting on them, they cover the doldrums of the first half of the year, the euphoria of AI reinvigorating the second half, & the valuation environment. The next five posts all mentioned major exits : Klaviyo, Loom, & the many take-privates in 2023.

I’m grateful to everyone who read, commented, debated, & shared these posts & others.

0. Launching Theory! We launched the firm this year & announced our first fund. I’m grateful to the many people who helped us achieve this milestone.
1. The Typical Startup Saw a 24% Increase in Sales Cycle in 2023. The first two quarters of this year were rough for startups. Lengthening sales cycles created pipeline shocks & instability in sales forecasting.
2. How Markets Value SaaS in 2023. The public market shifted from valuing absolute growth, to valuing profitability, to valuing efficient growth - all in less than 12 months.
3. Why Every Startup Needs an AI Strategy. ChatGPT & AI upended the ecosystem. Much like mobile technology became a de facto part of every startup, AI is now no longer a category but the core or a component of every product.
4. Every Customer is a Design Partner - Leading Your Sales Motion with Sales Engineering. I argued that the best sales processes are sales engineering sales. Founder sales start the company this way & great sales teams continue this practice.
5. The 4 Questions Startups Should Ask Themselves about Building with Generative AI. In this presentation at Saastr, we broke down the major questions for startups building with AI : the layer, the moat, the market, & the depth of AI to use.
6. The Paradox of AI and Data Roles: How Automation Will Increase Demand for Data Professionals. As data becomes critical to developing products, the need for data professionals only grows, even if AI automates rote data analysis & retrieval.
7. The Implications of Increased Regulatory Scrutiny for Startup Acquisitions. The anti-trust pressure from the US & European governments eliminates about 70-75% of the purchasing power for M&A in Startupland.
8. Which Increases Productivity More : The Advent of Personal Computer or a Large-Language Model?. The PC increased GDP in the US by an immeasurably small amount. On the other hand, AI has the potential to boost US productivity enormously, boosting GDP growth by 50% or more.
9. Which AI Model Should You Pick for Your Startup?. The early days of the constellation of models thesis which is starting to appear in buyers’ architectures. Most AI products will be built with a series of models: one large general purpose, several smaller models, & a router in front to optimize cost & performance.
10. Operating in the Dark. A rallying cry during the dark days of 2023, throughout all the layoffs, unpredictability, & dysfunctional fundraising market.