Posts

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.

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.

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. We saw a notable uptick in close rates. We saw an improvement in sales cycles. The majority of large customers I mentioned last quarter, those deals had slipped from Q3, reengaged and signed significant contracts in Q4. We crossed 3 million active developers on our platform, including Cloudflare Workers and Workers AI.”

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. But it can be just as meaningful.

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. That’s not chump change. It underscores the return potential of this space.

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.

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.

Darwin’s finches sprinted to evolve when food sources changed. For decades, nothing—then sudden transformation. AI follows the same pattern & it’s accelerating.

Every morning, I wake up wondering what breakthrough will propel the ecosystem forward.

Last week, it was DeepSeek v2. This morning, a Hugging Face researcher announced that he could induce reasoning on the major advance of the last three months in one of the smallest models, a 3B parameter model.

A microwave that writes its own recipes. A smart watch that crafts personalized workout plans. A ticket kiosk that negotiates refunds in natural language. This isn’t science fiction - it’s 2025, & DeepSeek just made it far more affordable.

The Chinese AI company released two breakthroughs: V3, which slashes training costs by 90+%, & R1, which delivers top-tier performance at 1/40th the cost. But the real innovation? They proved that sometimes simpler is better.