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Hey y’all!
After publishing Inside “ChatGTM”: Cursor’s Internal Sales AI Used by their 400+ Sales Org, I got a message on LinkedIn from a guy named Bruno, at a company I didn’t recognize: XBOW. My quick research showed me that XBOW is legit. XBOW’s AI hacker reached #1 on HackerOne’s leaderboard, the first time a machine outranked human bug hunters. Their founder is Oege de Moor, who created GitHub Copilot and GitHub Advanced Security. They were founded in January 2024 and have already raised $272M to date, most recently at a $1B+ valuation. Anyway, Bruno’s message to me said: “We have an internal tool that goes across the funnel (we use a bowtie model) and has a UI that is similar to Cursor’s and then there are all the backend jobs and a Slack Bot that complements it. It has been a game changer for our GTM teams.” I immediately set up a call to learn more.
Bruno Leardine (Director of GTM Engineering) also brought his CRO (Niroshan Rajadurai) and Head of RevOps (Justin Miller) to the call. One of the first things they told me is that they had decided to build a truly AI-native revenue org, based on their prior experience at GitHub. And they were going to build their revenue org the same way a modern product org runs: planning in sprints, building their tools in-house, and staying on the leading edge of agentic tools.
The tool they’ve built is one of the most sophisticated internal GTM systems I’ve seen. The first version was built by just Bruno, Niroshan, and Justin. And they were kind enough to give The Signal readers a behind-the-scenes look at:
Their unique approach to building
The most interesting capabilities of their in-house tool
How they built the whole system with just 3 people
How this compares to what I’m seeing in the industry
Plus, I’ll share how their approach ties into a big theme I’m seeing across the best GTM teams.
Let’s get into it.
The XBOW team’s unique approach to building
Most GTM teams don’t operate like a Product team. But this team has an atypical perspective based on their background at GitHub. Plus, they had specific constraints: as a cybersecurity company, XBOW can’t use the same off-the-shelf LLM products that others can, because they can’t just hand a third-party tool company-wide access to their Drive and Slack. So they built everything a bit differently.
1. Foundation before agents.
Justin (Head of RevOps) spent the first 6 months getting a standard tech stack in place: ZoomInfo, Salesforce, Gong, and others. But, eventually, they cut their sales stack from twelve tools down to just five (tools like Rox, Clay, and Sumble) and got the data model right. They also put in a lot of work with the field on where all the data should live. That was all before they even started building any agents. If you bolt an agent onto a messy stack, you’re going to get poor results.
2. Develop everything through rapid experimentation.
Justin told me they started experimenting, not only with what they were building internally, but also in their choice of partners. Working with nimble startups helped them experiment faster as co-builders / design partners. Bruno said: “It was clear to me that Rox was thinking about prospecting six to twelve months ahead, and that’s a burden I don’t need to have. So I can come and learn and be advised on the topic, and then go figure out other parts of the business that I don’t have a partner looking into.” These tools have become more popular recently (back then, they weren’t as well established), but the XBOW team knew they wanted to move away from the incumbent sales tech providers to try out some tools that could really help them level up. So they tested to see what worked and found some real winners.
3. Centralize the org’s knowledge.
They decided to centralize knowledge and context so the tool “knows the business cold” and sits on the source of the data. As Director of GTM Engineering, Bruno’s rule for every integration is to go to the raw source (the Slack API directly, for instance), with no middle layer.
Pro tip from Bruno:
The principle behind this is that the goal is to build agents that know what to verify and when reality has changed. Correctness of information is not a function of documenting everything, all the time. It comes from validation systems that help agents reconcile what is written, what is said, and what is actually practiced. I spent a lot of time trying to get this right at the beginning.
4. Cover the whole bow tie.
Both Justin and Niroshan (CRO) called out that they didn’t want to just stop at top-of-funnel. Their system runs “the full bow tie.” This is Jacco van der Kooij’s model that doesn’t just cover awareness through acquisition (like traditional marketing funnels), but also includes renewal and expansion. This matches something I believe more every week: the lines between sales, CS, and support are blurring, and a unifying layer across the whole customer lifecycle is becoming the obvious architecture when building a modern revenue engine.