Scoring 2025's Predictions

Every year I make a list of predictions & score the previous year’s. You can find my 10 Predictions for 2026 here. 2025 was a good year : I scored 7.85 out of 10.

1. The IPO market rips.

Company Sector Market Cap, $b vs Last Private Round
CoreWeave AI Infrastructure 40.5 2.1x
Circle Stablecoin/Fintech 20.3 2.2x
Figma Design Software 18.85 0.9x
Chime Digital Banking 11.6 0.5x
Hinge Health Health Tech 3.8 0.6x

Score : 0.6.

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12 Predictions for 2026

Every year I make a list of predictions & score last year’s predictions. 2025 was a good year : I scored 7.85 out of 10. I will release the scoring tomorrow. For today, here are my predictions for 2026 :

1. Businesses pay more for AI agents than people for the first time.

This has already happened with consumers. Waymo rides cost 31% more than Uber on average, yet demand keeps growing. 1 Riders prefer the safety & reliability of autonomous vehicles. For rote business tasks, agents will command a similar premium as companies factor in onboarding, recruiting, training, & management costs.

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Thursday is Podcast Day

Thursday is the new Monday for podcast producers. Analyzing hundreds of tech & VC podcasts over six weeks this fall through MotherDuck’s MCP server, I found 42% of episodes drop mid-week, between Thursday & Friday. Sunday? A publishing desert at just 3%.

Here’s what else the data reveals.

When Episodes Drop

Prompt: Count the number of podcasts published on each day of the week with %

motherduck_podcast_dow_v2

The pattern makes sense : listeners consume podcasts during commutes & workouts early in the week, so publishing mid-week ensures fresh content when people are ready to listen.

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A Flash of Deflation

Gemini 3 Flash represents a step function increase in model deflation : a gauntlet thrown.

Google’s latest model underprices the state of the art by 70% to 79%, with very similar levels of performance. At $0.50 per million input tokens & $3.00 per million output tokens, Gemini 3 Flash hovers within 9% of the best scores across 20 benchmarks.1

How much better is the price-performance? How much cheaper can teams run inference?

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The Bifurcation in the AI Market

Despite open-source AI models being 10-100x cheaper, proprietary providers haven’t lost pricing power. OpenRouter’s data reveals a market splitting in two.

Over the last year, open-source models’ market share has remained stable around 22-25%, briefly spiking to 35% during the explosive growth of Chinese models in mid-2025 before settling back down.

Open Source Market Share Steady Despite Massive Growth

The weak price elasticity indicates that even drastic cost differences do not fully shift demand; proprietary providers retain pricing power for mission-critical applications, while open ecosystems absorb volume from cost-sensitive users.

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Is Your AI Funded by Junk Bonds?

It’s not often that venture capital thinks about the credit markets. I remember becoming a venture capitalist three months before Lehman fell, when mortgage securities topped the news of the global financial crisis.

Recently Oracle’s bonds have been weighing on my mind.

AI’s capital expenditure in 2025 represents about 1.6% of US GDP. In 2026, that number should top 3% of US GDP according to Goldman Sachs estimates1.

Hyperscaler Capital Expenditures for Data Centers

Google, Microsoft & Amazon do not have the capital necessary on their balance sheets to fund this buildout without debt.

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The Average Founder Ages 6 Months Each Year

No, founders are not adopting Bryan Johnson’s regimen to reverse aging. Quite the opposite : the average founder raising capital ages six months every year.1

Median founder age trend over time

I suspect founder age has been increasing steadily for three reasons. First, venture capital has shifted toward AI, which grew from roughly 10% to 60% of investment in just three years.2 AI founders skew older. Many AI labs are started by PhDs who spent extended periods in school & often come from industry, commercializing initiatives from major labs or hyperscalers.

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The Two Context Databases Powering Enterprise AI

Enterprises learned a lesson from cloud data warehouses. They handed over both data & compute, then watched as the most strategic asset in their business, how they operate, became someone else’s leverage, which created an opportunity for Iceberg.

Fool me once…

Leaders have recognized their companies need a new system of record for AI agents in the form of a context database. There are two different kinds of these context databases :

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The AI Value Gap : Where Does the $7,000 Per Seat Go?

A new study from OpenAI shows AI saves the average white-collar worker 54 minutes per day. Where does all that value go?

BLS data shows median weekly earnings for full-time workers hit $1,165 in Q3 2024, or $60,580 annually. Across 2,080 working hours, hourly compensation equals $29.13. One hour saved per day equals 250 hours per year, or $7,282 in recovered productivity per seat.

Current AI pricing captures between 3% & 5% of this value :

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Streaming Comes into the Fold

Streaming is the next category to consolidate within the modern data stack. IBM announced its intent to acquire Confluent.

The deal values Confluent at $11.1 billion, or 10.0x LTM revenue. Confluent commands more than 40% of the Fortune 500 as customers & has grown into a $1.1 billion revenue business.

The founders of Confluent, including CEO Jay Kreps, created Apache Kafka, a streaming technology built inside LinkedIn. Founded in 2014, Apache Kafka now runs at more than 80% of the Fortune 100. Kafka powers real-time data pipelines & stream processing, updating data systems whenever a new event happens. When a taxi ride is booked, a credit card is swiped, or a user likes a comment, Kafka handles the data flow.

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