Marc Andreessen and Amjad Masad: English As the New Programming Language

• In any domain of human effort in which there is a verifiable answer, AI will drive extremely rapid progress; it is about the concreteness of the problem, not the difficulty
  • In fields with concrete true/false answers (math, coding, physics, genomics), AI will drive extremely rapid advancement
  • The difficulty matters less than the concreteness of the problem
• AI agents can now code autonomously for hours
  • Using platforms like Replit, anyone can describe an app in plain English, and AI will build it
  • Agents maintain coherence through verification loops that allow them to check their work and course-correct in real-time
• The definition of AI is always the next thing that the machine can’t do; AI scientists are always being judged against the next thing, as opposed to all the things they have already accomplished 
• We may be hitting diminishing returns with frontier models
  • GPT-5 showed improvements in verifiable domains, but didn’t advance much elsewhere
  • Top models excel at synthesizing information but struggle with nuanced, abstract problems and original discovery
• “Functional AGI” may block true AGI: AI that’s “good enough” to automate most economically useful tasks could reduce incentives to pursue actual general intelligence
• The real AGI benchmark should be efficient continual learning and generalized reasoning acquisition

Amjad Masad, founder and CEO of Replit, joins a16z’s Marc Andreessen and Erik Torenberg to discuss the new world of AI agents, the future of programming, and how software itself is beginning to build software.

They trace the history of computing to the rise of AI agents that can now plan, reason, and code for hours without breaking, and explore how Replit is making it possible for anyone to create complex applications in natural language. Amjad explains how RL unlocked reasoning for modern models, why verification loops changed everything, whether LLMs are hitting diminishing returns — and if “good enough” AI might actually block progress toward true general intelligence.

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