There's a moment when a technology stops being a tool and starts being a collaborator. I experienced that moment last week when I watched an AI agent plan, research, code, test, and deploy a feature across our codebase — while I reviewed its work like a senior engineer reviewing a junior's PR.

That tool is Google Antigravity, and it represents a fundamental shift in how software gets built.

What Is Agentic Coding?

Traditional AI coding assistants autocomplete your code. They're fast typists with good memory. Agentic coding is different — it's autonomous problem-solving. You describe what you want, and the agent:

  • Researches the existing codebase to understand patterns
  • Creates an implementation plan and asks for your approval
  • Writes the code across multiple files
  • Runs tests and fixes issues
  • Documents what it did and why

The shift isn't from "typing code" to "generating code." It's from writing software to directing software.

Antigravity in Practice

At Namma Yatri, I've been using Antigravity for everything from debugging Haskell build issues to building analytics dashboards. Here's what surprised me:

The 10x isn't in speed — it's in scope

Before Antigravity, I'd context-switch between understanding code, writing code, and verifying code. Now I operate at the architecture level. I describe the system I want, review the plan, and validate the output. The mechanical translation from intent to code is handled by the agent.

A concrete example: our executive metrics dashboard needed a complete overhaul — new data pipeline, ClickHouse queries, React components, and live comparison charts. With Antigravity, this went from a multi-sprint project to a multi-day collaboration. The agent handled the ETL refactoring, I handled the product decisions.

The CEO Perspective

As a CEO, I shouldn't be writing code. But I do, because understanding the system deeply is how I make better product decisions. Antigravity changes the equation — I can engage with our codebase at the architectural level without getting lost in implementation details.

The best leaders don't need to write every line of code. They need to understand every line of intent.

When I'm debugging a build issue at 2 AM, I don't want to read Stack Overflow. I want an agent that already knows our toolchain, our constraints (Apple Silicon + Haskell + dynamic linking, anyone?), and can figure it out while I think about what to ship next.

What's Next

We're at the beginning of something massive. The tools will get better. The agents will get smarter. But the hardest part isn't the technology — it's the mental model shift. Moving from "I write code" to "I direct code" requires trust, and trust requires transparency.

Antigravity gets this right with its artifact system — implementation plans, walkthroughs, task tracking. You always know what the agent is doing and why. That's the foundation of trust.

The future of coding isn't autocomplete. It's autopilot with a really good flight deck.

Magizhan is the CEO of Namma Yatri, India's open mobility platform. He writes about technology, leadership, and maximising value.