Accelerating Our Mission to Bring AI to Everything After Code

Since launching Harness in 2017, we’ve been on a mission to unlock faster innovation by removing the bottlenecks that slow software engineering teams down. From day one, we believed that the biggest obstacles in engineering weren’t in writing code — they were in everything that followed.

Where the engineering bottleneck really lives

Long before Harness existed, I felt this personally in my work as an engineer and later as a founder. The real friction wasn’t in creativity or innovation; it was in the countless hours spent testing, verifying, securing, deploying, and governing software before it ever reached a customer. The constant context switching between tools and tasks disrupted my flow state and reduced productivity. 

Those downstream steps were slow, fragmented, and full of risk. And they held teams back far more than most leaders realized.

That experience shaped the foundation of Harness. Because even then, it was clear: the bottleneck in software engineering hits teams after the code is written.

And today, as AI accelerates how quickly code gets created, the gap between development and delivery is widening even faster. Engineering leaders everywhere are recognizing that the real impact of AI won’t just come from writing more code — it will also come from removing the friction in everything that follows.

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AI-generated code is making the problem worse

AI is producing more code than teams can reasonably ship using manual workflows. Developers may write code several times faster with the help of AI, but that acceleration creates a new problem: a surge of changes flowing into delivery pipelines, tests, security checks, and feature experimentation systems.

Most organizations simply can’t keep up with this shift using fragmented tools or manual processes. Every change — whether written by a developer or generated by AI — still needs to be tested, secured, deployed, and governed. The volume of that work is growing faster than the systems built to manage it. 

The bottleneck has moved, and the only way to match AI-accelerated development is with a software delivery platform built to understand an organization's complexity and manage the downstream work that follows. Our mission has never been more important, and it’s exactly why I’m so excited about today’s news.

A milestone that validates our mission

We’re announcing a $240 million Series E financing round, comprised of a $200 million investment led by Goldman Sachs and a planned $40 million tender offer with participation from IVP, Menlo Ventures, and Unusual Ventures. This investment values Harness at $5.5 billion.

I’m grateful for this milestone because it reflects the clear shift happening across the industry: organizations finally have the tools – and the urgency – to transform everything after code. 

Harness was built for this moment

Long before AI became mainstream, we believed intelligent automation needed to be built into the foundation of software delivery. It’s why, when we first came out of stealth, AI was already central to how we thought about building the platform.

We’ve invested in three core capabilities that now power Harness AI:

• A knowledge graph and deep context model that understands each organization’s architecture, pipelines, policies, services, and history.
• A set of focused AI agents that evaluate, prioritize, and automate the steps after code — testing, verification, security, governance, and delivery.
• A reliable orchestration engine that makes every AI-driven decision consistent and safe.

And over the last year, we’ve expanded this foundation into a full set of agentic AI workflows. What makes these agents different is that they’re grounded in the platform — they act with organizational context and predictable execution. Instead of simply surfacing recommendations, they close the loop by taking action and removing much of the manual work that has traditionally slowed teams down.

Individually, these capabilities matter. Together, they form a unified platform that helps teams ship faster by absorbing the complexity that has held engineering back for decades. 

This is what we mean when we say Harness is the AI platform for everything after code.

Harness AI diagnoses DevOps pipeline failures and makes pipelines more resilient at your command.

Strong momentum — and real impact for customers

We’re on track to exceed $250M ARR this year with 50%+ growth. But what matters most to me is seeing how customers are using Harness to change the way they deliver software. Here are a few examples of how teams are transforming their delivery workflows with Harness:

• United Airlines accelerated deployment times by 75% and migrated 80% of workloads to the cloud.
• Morningstar modernized its CI/CD ecosystem, achieving 5x faster builds, consolidating 36,000 pipelines to 50 templates, and transitioning from weeks-long releases to daily deployments.
• Keller Williams increased deployment frequency by 6x and saved 3 weeks in every release cycle.
• National Australia Bank (NAB) reduced build times by 67% and improved troubleshooting efficiency by 85%.
• Citibank reduced toil across 20,000 engineers and cut deployment times to 7 minutes.

A turning point for engineering

AI has rewritten the first half of software engineering. The second half — everything after code — is where the next chapter will be defined. Delivering software safely, reliably, and with confidence is bound to be the biggest differentiator for modern engineering teams.

This new investment accelerates our ability to build the systems that make that possible: unified intelligence, deep context, and automation that brings clarity to complexity.

We’re still early in the journey, but our mission remains constant: to automate everything after code and help teams move with the speed and confidence the AI era demands.

I couldn’t be more excited for what’s ahead, and I’m grateful to everyone building this future with us -– our customers, our partners, and our employees. Thank you for your partnership, your feedback, and the work you do with us every day. 

— Jyoti