The AI Coding Gold Rush Ends Where Harness Begins

On a bright afternoon in Bengaluru’s HSR Layout, where AI startups bloom faster than cafés and ambition hums louder than traffic, Harness, the AI-native software delivery platform, was turning demos into products overnight. 

Today, platforms like Replit, Lovable, and the new generation of AI developer tools can spin up features in minutes, including Indian alternatives like Emergent, Rocket, and others. These so-called vibe-coding tools or code-automation platforms have radically transformed the first 30-40% of software development.

At Harness’s Bengaluru office, where meeting rooms are named after cult films, series, and games, the company hosted its inaugural developer community event, AI Connect, focusing on solving complex software challenges. This phase—the often messy, unseen, and unglamorous 60-70% of the software lifecycle—is where Harness operates. It involves testing, securing, governing, verifying, deploying, rolling back, auditing, and building trust in code. This is the part that AI demos rarely address, yet enterprises cannot afford to overlook it.

“Only 30% of software engineering happens on the laptop. The real 70% starts after you code,” says Jyoti Bansal with disarming clarity. 

Harness recently raised a $240 million Series E round, valuing the company at $5.5 billion. Bansal has already built and exited a unicorn before, the likes of AppDynamics, which got acquired by Cisco in 2017. 

Bansal shrugs off the label, perhaps a reflex born from growing up in a small town in Rajasthan’s Jaisalmer.  He quips the “billionaire founder” mould and rejects the performative glamour around it. “That’s not what drives me,” he said. “Labels don’t build companies. Obsession with solving real problems does.”

In 2025, the company reportedly reached $250 million in Annual Recurring Revenue (ARR), showing 50% year-over-year growth, and has expanded its workforce to 1,200 employees operating out of 14 offices globally.

Check out the full conversation exclusively on Front Page by AIM Network.

By combining specialised AI agents, deep organisational context, and reliable orchestration, the platform turns software delivery workflows into an intelligent system that learns, adapts, and acts on behalf of engineering teams.

“Agents are easy to demo. The hard part is making agents that actually work for a real bank or airline,” Bansal said. 

When asked if AI agents are killing SaaS faster than ever, Bansal added that he doesn’t believe the narrative. 

A few kilometres from where dozens of early-stage AI startups are prototyping the future in Bengaluru, Harness is expanding, anchoring its work in generative AI for software delivery, intelligent testing, secure DevOps automation, platform intelligence, cloud optimisation and modern resilience systems. 

“India is taking on an increasingly strategic role as a major hub for the innovations that shape Harness’s long-term platform vision,” said Bansal. 

Head of R&D India, Prashant Verma, puts it even more plainly: “We’re building one of the world’s most advanced AI engineering ecosystems right here in India.”

But the infrastructure ambition is matched by culture. Harness behaves like a federation of founders. “We run Harness like 15 startups inside one company,” said Bansal. 

The company states it has powered 128 million deployments, executed 81 million builds, safeguarded 1.2 trillion API calls, and assisted organisations in optimising over $1.9 billion in cloud expenses. 

Harness said, its enterprise customer, United Airlines, sped up deployment by 75% and migrated 80% of workloads to the cloud; Morningstar reduced 36,000 pipelines to 50 templates; Citibank cut release cycles from weeks to minutes; Keller Williams increased deployment six-fold; National Australia Bank cut build times by 67% and improved troubleshooting by 85%.

Harness told AIM that it will eventually go public. His previous company was minutes away from ringing the bell before Cisco acquired it.

Bansal insists that the IPO is an outcome, not an obsession. The real mission, however, he said, is to build a world where everything after code, testing, governance, reliability, deployment, security, cost and resilience, becomes as automated, intelligent and dependable as the AI that now writes the code itself. 

“If you’re a software engineer and you’re not great at using AI and agents, your job is at risk,” Bansal said, reflecting the urgency of that shift. However, he clarified that Harness is not replacing engineers, but is future-proofing them.

Platforms like Replit and Lovable keep pushing the pace at which code can be created. AI will continue to compress the creativity cycle, and Harness is building for that checkpoint. 

The post The AI Coding Gold Rush Ends Where Harness Begins appeared first on Analytics India Magazine.

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