The a16z Show

Erik Torenberg × Marc Andreessen

AI is already lifting leading-edge programmer productivity by an estimated 20x year over year, with higher compensation and exhausted “AI vampires” signaling demand rather than labor withdrawal.Andreessen argues AI-attributed layoffs may reset 2x–4x organizational bloat while funding more software, but adoption speed, role convergence, and institutional resistance remain key variables.

David Haber × David Solomon × Ben Horowitz

David Solomon sees one of the strongest macro setups in his “40-odd years” in markets, combining fiscal expansion, rate cuts, deregulation and an unprecedented capital-investment supercycle.Confidence has shifted M&A from “no” to “maybe,” potentially producing the biggest M&A year in history, while Goldman’s $1.9 trillion balance sheet and $500 billion deposit base frame the scale-and-funding challenge; FTC uncertainty and geopolitical risk remain key variables.

Yafah Edelman × David Owen × Marco Mascorro × Erik Torenberg

Inference demand, subscription revenue, and continued capability gains suggest AI has not become an obvious bubble, although ever-larger development costs could still overwhelm current profits if progress stalls.Coding and computer-use agents are already useful but imperfect, while a 20%-30% chance of a five-percentage-point unemployment shock within the next decade makes labor-market discontinuity, policy response, and the uncertain 2045 superintelligence timeline key variables.

Erik Torenberg × Dwarkesh Patel × Noah Smith

AGI’s investable threshold is whole-job substitution, requiring continual learning, preference accumulation, and reliable workflow execution beyond current reasoning models.AI-built data centers and robot factories could drive rapid growth, but falling labor income, demand, ownership concentration, and compute scaling remain unresolved constraints.