The landscape of AI-assisted development has changed dramatically. Here's what we've learned watching this space evolve.

The Three Waves

We've seen three distinct waves of AI coding tools:

Wave 1: Autocomplete (2021-2023)

GitHub Copilot kicked off the revolution. Suddenly, your IDE could suggest entire functions. It felt like magic—until you realized it was really just very good pattern matching.

Wave 2: Chat Interfaces (2023-2024)

ChatGPT and Claude brought conversational AI to coding. Copy code in, get code out. Better context, better explanations, but still fundamentally a back-and-forth workflow.

Wave 3: Autonomous Agents (2024-2026)

Now we're in the agent era. Tools like Cursor, Claude Code, and Devin don't just suggest code—they execute multi-step tasks, run tests, and iterate based on feedback.

Where Infrastructure Breaks Down

The agent era has exposed a fundamental gap: where does the code run?

When an AI agent writes a database migration, it needs a database. When it creates an API endpoint, it needs a server. When it builds a frontend, it needs to see the result.

Most solutions today either:

Run everything locally (limited by your machine)
Use ephemeral sandboxes (nothing persists)
Require manual deployment steps (defeats automation)

This is the problem Runtime solves.

What Comes Next

We believe the next wave will be full-stack autonomous development—AI agents that can take a product spec and ship working software, end-to-end.

But that requires infrastructure that's designed for agents, not humans. That's what we're building.