Quick answer: Start with data, not tools. Agents only work when you give them two things — context and actions. The context is the data you already have: your product's metadata, your workflows, your knowledge graph. Build that shared foundation first. The agents come after.
That's the core of what Bala Venkatrao — SVP & GM of Platform at Harness, the AI-native software delivery platform valued at $5.5B — told me on the Intentional Product Manager podcast. Most teams trying to "go AI-first" start by picking a tool. Bala starts somewhere else entirely.
"Agents at the end of the day, it's two things — context and actions," Bala said. "Data and actions, when they come together, that's what agents is. If you just give a AI agent whatever to an LLM and say go and make it happen, it'll stumble and fumble and hallucinate. You never know what you're going to get. You need to give AI the right context, and that context is the data that you have."
At Harness, that means building what Bala calls a knowledge graph — a data model that pulls together every aspect of the software delivery lifecycle so an AI agent has something real to query before it acts. Skip that step, and the agent has no grounding for its decisions. It's not that the agent is bad. It's that it was never given anything to reason over.
Harness's own product thesis makes the point concrete. Tools like Cursor, Gemini, and Claude now generate a lot of code — but Bala estimates code and design account for only about 30% of software delivery. The other 70% is what he calls "the toil": integration, testing, build, deployment, feature flags, cost management. Harness built its AI-native platform specifically for that 70%, positioning itself as "everything for AI after code."
The organizational lesson underneath it: if you're trying to make your own org AI-first, the question isn't which AI feature to ship first. It's whether you have a shared data foundation any future AI agent can actually use — and whether you're building for the 30% everyone's excited about, or the 70% where the actual toil lives.
Bala's team builds shared building blocks — security, compliance, cloud infrastructure — once, so every new AI capability doesn't have to rebuild the same foundation from scratch. "Come for the products, stay for the platform," is how he puts it. Each new module gets cheaper to build because the substrate underneath it already exists. That's the same leverage logic that makes AI-first orgs compound instead of just accumulating point solutions.
Bala Venkatraman is SVP & GM of Platform at Harness. Before that, he led Atlassian's enterprise cloud business — scaling it from zero to several hundred million in ARR — and then ran Atlassian's marketplace and ecosystem business, growing its GMV from roughly $300M to nearly $1B. He's also been a founder himself, which shapes how he talks about decision-making: "We get paid only to take decisions," he told me. "The more decisions you take, the more confident you get."
He joined the Intentional Product Manager podcast to talk about what building an AI-native org actually requires — not the hype, the mechanics.
Ready to move to the next level in your product career? I'm Shobhit from Intentional Product Manager. Join me as we discuss ways to help you stand out in your job search and your career so you can have more impact and make more money. Hey everyone, welcome back to the Intentional Product Manager podcast, where we explore product management careers, choices, and mindsets, and I'm often joined by world-class product leaders. I'm your host Shobhit Chugh, and today with me is Bala Venkatraman, who's SVP and GM at Harness.io. He's an advisor, angel investor, previously ran his own company, and I've known him for a long, long time. So Bala, welcome to the show. Great to have you here.
Bala: Great — like I've been following you on LinkedIn. Congratulations on all the success. You've been doing these podcasts which are very informational and helpful. I listen to them once in a while too. So it's great to be here. I know we connected a while back, trying to find a time slot, but hey, this is a good time. Let's make it happen.
Shobhit: Absolutely. Just so you know, we're recording right before the holidays and making the most out of the time we have. So let's dig in. Bala, you've had quite the journey — Atlassian, Unravel before this, Cloudera, and then now at Harness. Tell us more about Harness — what's your role, what's your charter over there?
Bala: Yeah, though I've been at Harness for a little more than four months, and it's been an amazing journey. It's fast-paced — it's a company that's moving fast, we're seeing a lot of pull in the market. At the end of the day, we're building an AI-native SDLC platform — software developer life cycle management — and the thesis is pretty straightforward: there's a lot of code being generated by AI tools, whether it's Cursor or Gemini or Claude, but Harness is being positioned as everything for AI after code. Because the reality is maybe only 30% of any software development is related to code and design and thinking through it. 70% is what we call the toil — all the work it takes to get the product really in the hands of the customer. You've checked in the code, but then you need to do everything around integration and testing and build and deployment and feature flags and cost management. That's a lot of workflows developers have to account for. It takes a lot of time and effort, and that's what Harness is doing. Prior to Harness, a lot of times companies end up with point products, or they write a bunch of scripts to do a lot of the work — it's fragile. Harness has built a cloud-first, AI-native platform to really orchestrate and streamline all of these workflows, and we're seeing a lot of pull in the market. It seems like the right product at the right time, built for the right market, and our job is to make that 37 to 40 million software developers — and growing, with all of this vibe coding and other tools — able to bring their innovations to life.
Shobhit: Congrats on all the momentum — and recently you guys also raised funds. So congrats on that.
Bala: Yeah, it was a big round. We raised a Series E with Goldman Sachs participating, valued the company at $5.5 billion. We have a lot of momentum, large marquee customers, we're well over $250 million in ARR, growing at 50%, and clearly we want to double down on that momentum and make Harness the platform of choice for every company and every developer out there.
Shobhit: Tell me more about your role over there.
Bala: I joined as the SVP and GM to lead the platform business, the platform product. Harness has got around 14 products or modules covering every aspect of your software developer life cycle, but all of these products are built on a substrate — the platform substrate — and that's what my team is responsible for. Think about this platform as providing the building blocks that many teams can leverage — security and compliance and scale and cloud portability and cloud infrastructure. A lot of these are common building blocks, and we don't want every team to repeat the same building block over and over again — that's the leverage as a platform vendor: we can keep adding new modules, but the effort required to bring up a new module is significantly lower. I think Jyoti, who's the founder of Harness, talks about the "startup within startup" model — but the startups are possible because of the foundation we've built. So we have that foundation, but also a lot of things around commerce and billing constructs, all built by the team. And the thing I'm pushing forward is what a platform can do uniquely. Some of the initiatives we've kicked off are around data and AI and analytics and a knowledge graph — that's the key thing. If you think about AI, what are agents? At the end of the day, it's two things: it's context and actions. Data and actions — when they come together, that's what agents is. If you just give an AI agent whatever to an LLM and say "go and make it happen," it'll stumble and fumble and hallucinate — you never know what you're going to get. You need to give AI the right context, and that context is the data that you have — the data that you harness, no pun intended. At the end of the day, we have all the different aspects of SDLC, and we have so much of the data and metadata that we collect. We create a data model, or a knowledge graph, that our AI agents can query — and that becomes a very powerful differentiator, because based on that, our AI agents can do all the workflows they're supposed to do in a way that meets the customer requirements, the compliance requirements, and has the right guardrails. A lot of those efforts are driven by my team at Harness.
Shobhit: I've had quite a few platform product leaders on this podcast, and it's been such a fascinating conversation because you really have to think very deeply about what's unique that the platform can provide, what goes in the products — I love that mental framing.
Bala: Yeah, the ethos of the mindset I bring to my teams and to all of Harness is: I keep telling customers, come for the products and stay for the platform. The platform is the leverage that we provide — leverage both to internal teams and to customers. When they bet on the Harness platform, they get so many more products working seamlessly because they're part of the platform — that's the advantage we bring to the market.
Shobhit: I'm sure a lot of your mindset has been shaped by some previous experiences. Tell me more about your time at Atlassian and how you helped scale that business.
Bala: Prior to Harness, I spent five-plus years at Atlassian. Of course I took some time off between Atlassian and starting — evaluating a bunch of ideas myself, kicking the tires, as you know, once an entrepreneur always an entrepreneur. Atlassian was a really good experience — I joined right as the pandemic was taking off, transitioning out of my own startup. Atlassian was a great opportunity because they were looking for an enterprise and platform leader like me to help them figure out how to build their cloud more for large enterprise customers. Atlassian has always been known for product-led growth, a lot of momentum in the mid-market and SMB, but they were trying to go up-market to enterprise customers. So they wanted a product leader who could really work with those large enterprise customers, work backwards, and build out those foundations in the cloud platform. That's what I did. Launched under my leadership, we launched something called Atlassian Cloud Enterprise, and that's been a really successful product — it scaled from zero to several hundred million in ARR over four or five years, because the market was there. We'd pitch to JP Morgan and Goldman Sachs — everybody wanted to come to the Atlassian cloud, but they had requirements around scale and compliance and security, so we bundled that as part of the edition. Based on the success of that, I led a fairly unique opportunity called Atlassian Economy, where the thinking was: given this platform we're building, how do we create economies around it? We looked at inspirations from companies like Salesforce with the Force.com platform, or Amazon Retail — they started by providing their own products, but now Amazon Retail offers everything as a service: warehouse as a service, payment as a service. We took a lot of those inspirations and asked, can we create an economy around the platform? Some of the key products I was responsible for as part of Atlassian Economy included the marketplace, the ecosystem, the developer teams, and the commerce team. Under my leadership we scaled the GMV — that's one of the output metrics you measure for any ecosystem or economy — fairly significantly. Before I left, it was close to a billion in annual run rate; when I joined it was around $300 million. So it roughly tripled over three or four years. We had tailwinds — a lot of Atlassian customers migrating to the cloud — but we also made sure those enterprise customers came to the cloud and leveraged a lot of the cloud apps offered through the marketplace.
Shobhit: You mentioned entrepreneurship, and I know you were at Cloudera before. So you've run product teams, transitioned into entrepreneurship, and back into running product teams. How did that transition look, and how did you talk about your experience as an entrepreneur when you were interviewing at Atlassian?
Bala: To a great extent it's just a mindset. As an entrepreneur, what are you doing? You're hustling — you want to push the agenda, you have an idea and you're trying to bring that idea to life. The same mindset is applicable everywhere, whether it's a small startup you're trying to bring to life, or even in a large company where you're trying to bring an idea to life. I'm sometimes puzzled when people ask, "Are you a big company person or a small company person?" I find that question quite puzzling — at the end of the day you really need to drive outcomes, and you want to bring new ideas. That's what personally excites me — working on new things, breaking new ground, going from zero to one. And once you get to one, it doesn't stop — you need to keep scaling. There are a lot of entrepreneurial hacks where you're trying out a bunch of new things, experimenting. For me it's been that mindset, and I brought it to Atlassian — created a bunch of zero-to-one products, and now I'm bringing that same energy to Harness — thinking about new things I can bring to market and help scale the company.
Shobhit: One thing I caught onto as you were talking is you just didn't see a difference — either way you have to deliver outcomes, deliver results. I really admire that, and it's a lesson I keep telling my students: if you believe strongly that your past experience has value without the title of product manager, it has value. I know you're a big believer in having a founder mindset even within large companies — in practice, how does that look, and does anything change when you go from a startup to a large company?
Bala: Founder mindset is having the conviction and the belief to do something. A lot of times people are afraid to take decisions, but we get paid only to take decisions — as you get into more of a leadership role, you take decisions based on data and facts. I make sure I'm out there talking to customers, really understanding where the market is headed, because that's how you build your product intuition. Whenever I talk to my PMs in one-on-ones, the first thing I ask is how many customers did you talk to this week, were you on any escalation calls — because product craft is all about building that intuition, and the only way to build it is to go and talk to customers. When you do that enough, you have a certain conviction about where the market is headed, what solution you ought to build. Of course you want to listen to everyone, but you need a strong point of view, whether it's your manager or the CEO of the company — you go in with that level of confidence, and you spar and debate. As a founder you have an intuition because you started the company; but even as a newbie product manager, the more grounded you are in what your customers are asking for, the better off you are, because now you bring data and facts to the conversation, and that helps everybody make the right calls. Founder mindset is about going back to first principles: is this the right thing for the customer first, then is this the right thing for the company, then is this the right thing for my team and myself. If you have that priority order, chances are you're making a lot of right calls. And you're thinking ahead — not just a week or a month, but 12, 18, 24 months out — placing bets that are the right ones for the customer and the company.
Shobhit: Let's switch topics — a very popular topic right now, the role of AI in product management. You've mentioned to me before that PMs need to engage deeply with AI, not just generally talk about it, not just put "AI Product Manager" on their LinkedIn. What's your philosophy on this?
Bala: With AI, I feel like I'm a kid in a candy store. There's so much going on — every day I want to try something, download an app, try vibe coding, deploy something. As a product manager I can get started very quickly, because now the language is natural language — I don't need to do much coding, I can just use natural language to create an app or a mockup and have that conversation with my engineering team. AI is giving you superpowers as a PM to do a lot of things that earlier you were constrained or hesitant to do — you were good at talking to customers and writing a PRD, but couldn't do the wireframe. Now you can do that very easily. In my view, AI is about really understanding the tools out there and, going back to first principles, thinking about how to build agents the right way — what context do you provide, what guardrails do you have. Nothing substitutes going back and really thinking it through. Carve time out, put it on your calendar, go back to first principles: is this the right thing, how will these AI interactions work, how will agents work, what will they do — because at the end of the day agents are trying to mimic what humans would do, but at scale. If you had humans do that, you'd probably need ten people to do the job a single AI agent will do. This is also an opportunity for PMs to step up their learning — some people are still fixed in the old ways, doing everything by Jira or a PRD, but there are new and modern ways product management is evolving. I wouldn't be surprised if we see product managers evolve to do things end-to-end — write a spec, talk to the customer, use vibe coding to build the mockups, maybe write the code, do the PR, check everything in. We'll see this concept of "product owners" evolve, where they own outcomes end to end, from idea to actually delivering the feature. Some features are more complex, distributed backends and so on, but for some of the smaller features we'll start to see that paradigm shift.
Shobhit: It's a very exciting time because those strict boundaries are starting to blur — when does a designer come in, when does an engineer come in. I think people should be fine with a new world where they can do part of the job of an engineer without needing infrastructure expertise. I'm sure you talk to less experienced PMs — what's been your experience with those who are waiting for someone to teach them instead of diving in?
Bala: This is true with any change — whenever change happens, people get uncomfortable. One lesson I've learned, and you've probably seen this too, is that whenever change happens, that's when you learn the most. If you're settled in a job doing the same routine, you don't learn — but when you put yourself in an uncomfortable situation, where you don't know much about an area, that's where most of the learning happens. Similarly with AI, a lot of people say "I can't do this" — why can't you? Just download the app, try it out, kick the tires, you'll learn something. It's the concept of "learn it all" instead of "know it all" — constantly learning, pushing the envelope. You have to carve time for yourself, otherwise your calendar is busy and you don't have time. I carve time on Fridays to read papers on the latest research — a couple weeks back there was an amazing paper on agents in production, why it's working, what's not working, put out by a bunch of university folks — great learning, and I shared it with my team. Or I'll download a new piece of software and kick the tires. It gives me a sense of where things are headed, and many times I point my team to it — "have we considered this, we're trying to build this internally, is this the best use of our time and resources, or should we buy a product or capability out there." Constantly learning, and then trying to apply it in your current job — because if you just keep learning and don't implement it, you're not building that muscle. For example, last week I was interviewing someone who gave a nice presentation of where we should build. At the end I asked, "where are the mockups?" And he said, "I didn't know we had to do mockups." I said, "yeah, you could use Lovable or Vercel to create the mockups." He said that's a good point, and the next day he created an amazing set of mockups. That's the expectation — I do it too, I create mockups and share them with the team. Have that attitude of constantly asking what it is you want to learn, and be open to the possibilities, because the beliefs you held in the past may not necessarily be true anymore — things are changing really fast, there's a new model every day, a new company building something agentic, new protocols coming up. You can use ChatGPT to quickly learn and synthesize and start to formulate your point of view. That's probably a good mantra to stay ahead and at least keep pace with what's going on.
Shobhit: We talked about your career, founder mindset, AI and product management. Let's talk about leadership. You've led multiple teams across startups and public companies — how has your leadership style and philosophy evolved over time?
Bala: A lot of my leadership thinking was grounded during my early formative years as an engineer, working at Sun Microsystems and other places, where it was more of a peer mentality — leadership isn't someone up there telling others what to do, that's such an old-school way of thinking. A leader is someone who's inspiring others, saying "this is where we need to go," but at the end of the day it's a collective effort — you're bringing everybody along, they're your peers, and in many cases your peers may know more about a certain area than you do. As a leader you're inspiring people, saying "this is possible" — otherwise people are okay with the status quo. You're pushing the envelope, and then as a leader you help people address the roadblocks — you roll up your sleeves and collectively solve the problem. I've done that consistently: if a team comes back and says it's not possible, I ask why not, let's go figure it out — there should be a way for us to address this, because at the end of the day we're doing this to solve a customer problem, help them be successful. If you do that well, revenue will flow, you'll grow your career. That's the first unlock for me as a leader — bringing positivity, optimism, working with your team, inspiring others, saying "yes, it's possible, it's doable, let's do that." Over the years, across large teams and small teams — and I don't measure leadership by the number of people you manage, that's a very old-school way of looking at it, you can be an IC and still be a fantastic leader — I've built a simple framework for myself that I've used pretty successfully. I call it the CATS framework. I have a cat at home too. The first thing as a leader is you bring Clarity — why does your org exist, what are you supposed to do, what's your north star, your mission, and how do you set up the right OKRs or KPIs so there's transparency because people have clarity on roles and responsibilities. The next is Accountability — once you have clarity on what needs to be done, you give the right people and teams the responsibility, but also the accountability to deliver, and you empower them: this is what we collectively agreed, go make it happen, and if you hit a stumbling block, come back and we'll collectively solve it, or maybe you have a creative way to solve it yourself. Then Trust and transparency — you need to be transparent in your actions and communication, you can't tell your team one thing and your management something else behind the scenes. I've never believed in upward management, downward management — just be transparent, call a spade a spade. If there's a problem, it's a problem, and you address it and show how the team is acting toward it — that creates a lot of trust, because people see a leader who isn't sugarcoating things or saying different things to different audiences. And the last thing is Servant leadership — I'm very much a servant leader, I'm here to serve my customers, serve my team, make other people successful, and if I do that well, indirectly I'll be successful too. If I can make each of my team members amazingly successful in their career, help them grow — I had some amazing mentors who helped me get to where I am — if I do that well for my team, set them up for success, indirectly I'll do well too. It all comes back together, and that's the framework and approach I've been practicing for many years now.
Shobhit: I love how you've thought through it and codified it for yourself. Let's talk about transferring some of this to others — a lot of product folks want to figure out how to become better leaders, how to move into exec roles. What advice would you give them?
Bala: The key thing is to take on hard problems — problems other people don't want to do. Many times you're in a comfortable role and keep doing that, and then wonder why you're not getting promoted. There's a day job and then there's a night-and-weekend job. If you keep doing your day job day in and day out, great, I'll give you credibility for what you've done — but you need to figure out what you're doing above and beyond, what's wowing people about things they haven't thought through. Those are the things that get you to the next level, more visibility, more recognition, more responsibility — and sometimes you need to raise your hand. It might be the messiest problem, but if you have the courage and conviction that you can go solve it, raise your hand, take the bull by the horns. That's something I've repeated to myself many times — take on the challenge head-on and go make it happen. Once you do that, it gives you confidence — as I said, you get paid to make decisions, and the more decisions you take, the more confident you get, because you're building that muscle, building intuition. People start seeing that in a leader and give you more responsibility, more scope, more opportunities.
Shobhit: I want to add something to this — two people I follow who aren't product leaders. Alex Hormozi does a podcast for business leaders and entrepreneurs, and he talks about taking on hard problems, but the reason people don't is because they don't know how to solve them — and that's the very definition of a hard problem: right now you don't know how to solve it, but if you take it on, you'll figure it out. And Brendon Burchard talks about the ultimate confidence being the confidence that you can figure something out.
Bala: There's a fear of failure — "what if I take it on and it fails" — but again, nobody else knows how to solve it either. You take on the problem with first-principles thinking: is this the right way to do it, what's a better way, break the problem down into smaller pieces, get the right team, put a structure in place — these are the monthly goals, this is where we need to go, start showing progress. Those are very basic, fundamental things, but when people get into that gray, nebulous problem, they get overwhelmed and say it's not possible, it's too crazy. But if you take a deep breath, step back, and break it down, it is possible — because if it's not going to be you, it's going to be somebody else, and they're going to take a similar approach. There's no magic wand somebody can wave to solve the problem — it's more about having a collective approach, being thoughtful, making forward progress, having clarity on your goals, and if you don't meet them, go iterate, go solve for that, and eventually you'll get to the right place.
Shobhit: Bala, this has been a very thoughtful, energizing conversation — I always love speaking with you, this was phenomenal. Before we wrap up, any final advice for PMs looking to grow their careers, especially in today's job market?
Bala: Be curious — that's the one thing. Keep that learning mindset, and take on hard problems. If you have these things built in, and you're always checking yourself on it, it'll go a long way, because a lot of things are in flux right now — but that's true for everybody, not just you. Being curious, being able to learn — and you can learn from anybody, from someone who just graduated yesterday, or someone who's been in the industry for 30 years — having the humility to learn from anybody and everybody, soaking it in, and being hands-on, pushing the envelope. It'll keep you excited about what you're doing, and it'll also come across as someone willing to be flexible, adjust, and try new ways to solve current or emerging problems. Those are the fundamental things to keep in mind, and if you take on bigger and bigger problems, you build the muscle to create more impact — and impact is what helps you get more confident, more recognized, and scale up in your leadership journey. You can't wake up one day and say "I want to be an SVP and GM" — that's a great ambition, but it's not the goal. It's the impact you're creating, and if you do that well, you'll get there — why stop at SVP and GM, you can be a CEO of a company too. At the end of the day, it's problem solving — if you build that mindset, you can get to wherever you want to go.
Shobhit: And last but not least, if people want to learn more from you, follow you — what's the best place?
Bala: They should connect with me on LinkedIn — I occasionally write posts there. These are the kinds of things I'd love to do as I'm starting to mentor other folks, both within Harness and outside. Nothing like sharing my knowledge and also learning from others — I think it's a good forum, and thanks Shobhit for creating forums like this. It's two ways — you share something, people read it, people reach out to you, there's a lot of serendipity here, and some of those relationships and connections you build now will serve you forever. I've known Shobhit for so many years now — in fact, we were part of a program called the Startup Leadership Program back in the day.
Shobhit: Bala, thank you so much for being on the podcast. Really appreciate your time, and I can't wait to see all the amazing things you do at Harness.
Bala: Likewise, Shobhit — it was great to be on this podcast, and congratulations on your continued success creating a platform like this. Happy to help any way I can.
And to our listeners — just so you know, in the show notes, whether you're watching on YouTube or listening on podcast platforms, we'll have Bala's LinkedIn profile so you can connect with him. If you enjoyed this episode, make sure to subscribe, rate it, share it with a fellow product leader. Until next time, stay intentional — and as Bala mentioned, stay curious. Be sure to check out our website at intentionalproductmanager.com to see how you can level up in your career.