Tomasz Tunguz

Practitioners building AI agent systems should prototype with state-of-the-art models, fine-tune specialized smaller models for well-defined tasks, use statically-typed languages to reduce hallucinations, and implement closed-loop prompt optimization systems for incremental performance improvements.

“Author of "9 Observations from Building with AI Agents" in Tom Tunguz”

Google achieved a 52x year-over-year increase in AI token processing to 10 billion tokens per minute while reducing serving costs by 78%, demonstrating unprecedented efficiency gains in its Gemini platform.

“Author of "Google's 52x AI Growth"”

Microsoft has built a $281B revenue contract with OpenAI, representing 45% of its commercial backlog, demonstrating massive AI demand but creating significant customer concentration risk for even the largest technology companies.

“Author of "$281B From One Customer" in Tom Tunguz”

Gemini 3's breakthrough performance improvements with identical parameter count to Gemini 2.5, combined with Nvidia's Blackwell infrastructure dominance, proves scaling laws remain viable and the 2025 'scaling wall' narrative was unfounded.

“Author of "The Scaling Wall Was A Mirage" in Tom Tunguz”

OpenAI's $1.15 trillion infrastructure commitment between 2025-2035 implies the company must grow revenue from $10B in 2024 to $577B by 2029 to maintain target profit margins, requiring a scaling trajectory comparable to Google's historical growth.

“Author of "OpenAI's $1 Trillion Infrastructure Spend"”

AI tool design must prioritize complex, parameter-rich tools over simple ones to improve LLM accuracy and token efficiency by up to 70%, fundamentally shifting from human-intuitive to AI-cognition-optimized architecture.

“Author of "How AI Tools Differ From Human Tools"”

AI vendor growth is creating second-order effects throughout the software stack, with MongoDB's Atlas experiencing renewed growth acceleration as AI-native companies adopt it for vector search and data management at scale.

“Author of "The Second-Order Effects of AI"”

Perplexity AI made a surprise unsolicited $34.5 billion bid to acquire Google Chrome, which industry investors dismissed as a stunt worth far less than the browser's true value.

“Venture capitalist who valued Chrome at ten times the Perplexity bid or more.”