AI as a CEO's Multiplier

Most CEOs I know use AI to draft emails and summarise meeting notes. I use it to build data pipelines, debug Haskell backends, and ship analytics dashboards.

This isn't a humble brag — it's a strategic necessity. When you're leading a company like Namma Yatri, speed is survival. And AI has become my biggest multiplier.

The CEO Code Paradox

There's an unwritten rule in tech: CEOs shouldn't code. Delegate. Hire. Focus on strategy.

I disagree. Not because every CEO should write code, but because understanding your system deeply changes the quality of every decision you make. The question was never "should the CEO code?" — it was "can the CEO engage with the codebase at the right level of abstraction?"

AI makes the answer yes.

My AI Stack

Each tool has its sweet spot. Claude is my thinking partner for hard problems. Gemini is my fast pair programmer. Antigravity is the agent that does the work while I review. OpenClaw is the always-on assistant that answers team questions at 3 AM.

Real Examples

Executive Metrics Dashboard: Our analytics team needed a complete overhaul of the executive dashboard. Instead of a 3-sprint project, I worked with Antigravity over 4 days. It refactored the ETL pipeline, built new ClickHouse aggregation tables, created React components with dual Y-axis charts, and fixed edge cases in cumulative comparison logic. I made product decisions; the agent made code decisions.

Backend Debugging: Our Haskell services were segfaulting during compilation on Apple Silicon. A human would spend days researching GHC linker issues. The AI identified the root cause in minutes: GHC's built-in linker can't handle the large symbol tables in our binaries. Solution: dynamic linking with --enable-shared --ghc-options="-dynamic". Fixed.

Data Pipeline Migration: Moving our ETL from a standalone repo into the control center monorepo. The agent mapped dependencies, refactored imports, created new test fixtures, and opened a PR with a comprehensive changelog. What would have been a risky, error-prone migration became a reviewed, validated operation.

The Multiplier Effect

Here's what changes when a CEO has AI teammates:

• Decision speed increases — I can validate technical feasibility myself, right now, instead of scheduling a meeting
• Quality of direction improves — When I tell the team "let's build X," I've already verified the approach works
• Bottlenecks dissolve — Things that used to wait for "someone to get to it" get done by the AI immediately
• Learning accelerates — Every interaction with AI teaches me something about our own system

The CEO's job isn't to do everything. It's to make sure nothing important waits. AI makes "waiting" nearly obsolete.

The Human Part

Let me be clear: AI doesn't replace judgment. It amplifies it. Every plan the agent creates, I review. Every PR it opens, I read. The AI handles the mechanical translation from intent to implementation. I handle the intent.

The real skill isn't prompting or coding — it's taste. Knowing what to build, when to ship, and when to say no. AI can't do that. But it can make sure that once you decide, execution is instant.

Advice for Other Leaders

If you're a CEO or technical leader considering AI tools:

1. Start with your actual work. Don't experiment in a sandbox. Use it on real problems.
2. Trust but verify. Let the AI work autonomously, but review everything before it ships.
3. Invest in setup. The first hour of configuring tools saves a hundred hours later.
4. Think in systems. AI is most powerful when it understands your entire context, not just a snippet.

The leaders who will thrive aren't those who resist AI or blindly adopt it. They're the ones who learn to collaborate with it — treating it as a capable teammate with specific strengths and known limitations.

The future belongs to the augmented.

Magizhan is the CEO of Namma Yatri, India's open mobility platform. He believes the best way to lead a technology company is to stay deeply connected to the technology.