There is a version of the Legal team that exists in most companies: thorough, careful, and quietly overwhelmed. Good lawyers are spending their days on tasks that really should not require a lawyer at all.
We decided early on that this was not the team we wanted to be.
At Harness, the AI-first approach is not just saved for the engineering team. It is how every team operates, including Legal. That means we stopped asking “should we use AI?” a long time ago and started asking “how do we build with AI?” The result is a Legal team that does not just use AI tools. It develops them. We close faster, advise smarter, and frankly, have more fun doing it!
Our AI legal stack
Every tool in our stack has a job. Here is what that looks like in practice:
- Contract review and redlining: This is where we are headed this year. The vision: we work from our own templates, so AI already knows what good looks like. It runs the first review, benchmarks the contract against our standards, and surfaces only the deviations worth our attention. Not every deviation is a problem. We focus on the relevant ones.
- Legal research: Finding the relevant law (the correct statute, regulation, or court decision) for a specific situation is the real challenge, not just finding the general law itself. Our AI tools are trained on comprehensive legal datasets to quickly filter out irrelevancies, ensuring we arrive at the precise answer faster and are supported by verifiable sources.
- Knowledge management: We are building a system where years of institutional know-how live in searchable, AI-powered playbooks, giving teams across Harness answers to common legal questions instantly, without filing a request or waiting for a callback.
- Data discovery and privacy compliance: Before you can be compliant, you need to know what you are actually dealing with. We use AI to discover and map all data currently being processed across the business: what it is, where it lives, and how it flows. That visibility makes it possible to track, manage, and meet our legal obligations, including privacy requirements for personal data.
- M&A project management: An AI-assisted platform provides a secure, structured home for our M&A work. When the pace picks up and the details multiply, nothing falls through the cracks.
- Regulatory compliance intake: Every new product goes through a single AI-assisted form before launch. Privacy, AI regulation, cybersecurity, accessibility: one entry point, no gaps.
- Building AI agents: This is the part most people do not expect. Our lawyers are not just using AI. They are learning to build with it, developing agents that handle specific legal tasks end-to-end. We are not waiting for the legal tech market to catch up with what we need. We are building it ourselves.
What it actually changes
The honest answer: the relationship between Legal and the rest of the business.
Turnarounds that used to take days take hours. Quality has gone up, not down. And because teams can self-serve answers to routine questions through our Legal Playbooks, the requests that do reach us are the ones that genuinely need us. We spend less time being a checkpoint and more time being a partner. That is a different job, and a more meaningful one.
We take the guardrails seriously
Moving fast with AI does not mean being reckless about it:
- Every output gets reviewed by a qualified attorney before it goes anywhere.
- We only use approved, enterprise-grade tools.
- Sensitive data never touches a public AI model.
- And we treat every AI-generated output as a starting point, not an answer, checking it against real sources before we rely on it.
What makes this more than a policy is the culture around it. We run regular sessions where the team shares what they are learning: tools worth trying, prompting approaches that actually work for legal drafting, and ways to get more out of what we already use. When one person figures something out, everyone benefits. That collective curiosity is what stops this from becoming shelfware and keeps it genuinely evolving.
If this is what Legal looks like at Harness, imagine the rest.
Every team here operates this way. Not because they are told to, but because it is genuinely a better way to work. If you are looking for a company where AI is woven into how things actually get done, not just what gets announced, we are hiring!
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Chinmay Gaikwad is an expert on making complex technologies - such as cloud-native solutions, Kubernetes, application security, and CI/CD pipelines - accessible and engaging for both developers and business decision-makers.
