
Venture capital spending reached nearly $680 billion through the third quarter of 2026, driven largely by massive rounds for large-cap AI companies. Despite this record inflow, the number of deals has fallen sharply, with North American deal counts dropping 16% year-over-year in Q3. The contraction is most severe at the seed and Series B stages, where fewer startups are securing funding even as late-stage capital increases. This bifurcation highlights a market where capital is abundant but increasingly inaccessible to early-stage ventures.
Read originalTopicAI Startup Funding And M&A
Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
TechCrunch AI · July 17, 2026 · Background
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Series B funding hits $48B but deal volume drops
2 developments
© Crunchbase NewsPhysical AI is no longer a niche experiment—it’s attracting billion-dollar capital commitments. Re:Build secured $2.1 billion to scale manufacturing partnerships, signaling massive institutional confidence in industrial automation. Meanwhile, the AI sector saw significant moves: Serval raised $150 million for enterprise coding agents, and General Compute launched its AI infrastructure play with $100 million backed by Nvidia rivals like Cerebras and SambaNova. These deals highlight a clear pivot toward tangible, hardware-adjacent AI applications rather than pure software models.
© Crunchbase NewsInvestor appetite for travel tech has collapsed to levels unseen since before the pandemic, with only $2.2 billion raised in the first three quarters of 2026—a sharp drop from $3.7 billion in 2025. The narrative that AI will automatically rescue the sector is failing; despite startups pitching AI-driven automation and personalization, capital is fleeing rather than flowing. This trend underscores a disconnect between vendor promises and investor reality, as VCs prioritize fewer, larger bets over broad experimentation. Established players like Navan are seeing stock gains, but the startup ecosystem is contracting rapidly, signaling that AI alone isn't enough to justify valuations in this space.
© TechCrunch AIApple is quietly pivoting to monetize the AI wave through its App Store, signaling that third-party AI agents could become a new revenue stream. This shift addresses regulatory headwinds and an 18% drop in U.S. commission revenue by potentially taking a cut of AI agent transactions. While details remain vague, the move suggests Apple sees AI as a key driver for upgrades and subscription growth. It marks a strategic adaptation to maintain services dominance amid global legal pressures.
© TechCrunch AITrajectory’s $45 million Series A signals a pivot toward making post-training accessible to non-technical experts. By automating continual learning, the startup lets domain specialists like lawyers and doctors refine open-source models through feedback loops without hiring expensive research teams. This approach bridges the gap between foundational models and specialized industry needs, potentially lowering the barrier for enterprise AI adoption. With backing from Sequoia and Nvidia, Trajectory is positioning itself as a critical infrastructure layer for vertical-specific AI applications.
© TechCrunch AIAnthropic’s revised S-1 filing drops a sobering admission: the company believes it is imminently close to Recursive Self-Improvement (RSI). This isn't just theoretical speculation; they explicitly state that AI-driven R&D may have already caused capability leaps they didn't initially recognize. While no current model has crossed the threshold, the warning signals a critical inflection point where automated progress might outpace human safety validation. It forces the industry to confront whether human-in-the-loop oversight can survive the acceleration it helped create.