Software 3.0

Software 3.0

Software 3.0 is Andrej Karpathy’s frame for programming with LLMs as interpreters: context, prompts, examples, files, images, and instructions become the lever over a model that performs computation in digital information space.

Key points

  • Software 1.0 is explicit hand-written code; Software 2.0 is learned neural-network weights trained by arranging datasets, objectives, and architectures; Software 3.0 is programming through context and prompting [src-055].
  • The LLM behaves like a programmable computer once it has been trained across a sufficiently broad multitask distribution from internet-scale data [src-055].
  • OpenClaw’s installation instructions illustrate the shift: instead of a cross-platform bash script, users paste instructions into an agent that inspects the environment, adapts, debugs, and acts [src-055].
  • MenuGen illustrates a more radical shift: a conventional web app that OCRs a menu and generates dish images can collapse into a direct prompt to Gemini/Nano Banana that transforms an input image into an output image [src-055].
  • The implication is not only faster programming; some new information-processing products become possible because natural-language and multimodal source material can be recompiled into new artifacts [src-055].
  • Rory Richardson gives a complementary enterprise frame: agentic AI compresses abstraction layers between human intent and working systems, so teams can move from ideation toward ones and zeros through fewer manual translation steps [src-057].

Related entities

Related concepts

Source references

  • [src-055] Sequoia Capital — “Andrej Karpathy: From Vibe Coding to Agentic Engineering” (2026-04-29)
  • [src-057] Amazon Web Services — “The Future of Agentic AI with Rory Richardson | AWS Humans In The Loop Podcast” (2026-05-01)

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

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