Why Ramp built its own in-house coding agent, Inspect
👋 Hi, this is Gergely with a subscriber-only issue of the Pragmatic Engineer Newsletter. In every issue, I cover challenges at Big Tech and startups through the lens of engineering managers and senior engineers. If you’ve been forwarded this email, you can subscribe here. Why Ramp built its own in-house coding agent, InspectA fintech company rejected the easy route and homebrewed its own coding agent – and is now a step ahead of coding agents from frontier AI labs. An in-depth look
At a select few tech companies, they write most of their code with their own, custom-built, internal AI coding agents. This is different from most of the industry which uses AI coding agents and harnesses like Codex, Claude Code, Cursor, OpenCode, GitHub Copilot, etc. At Ramp, their own version is called Inspect, while at Block it’s Goose (open source), at Stripe it’s Minions, and River at Shopify. But why not just use what frontier labs and coding harness AI startups already offer; why take the time and effort? We reached out to Ramp, a fintech company big on building its internal AI infrastructure, and sat down with the founding team of Inspect and engineering leadership. We talked with CTO Rahul Sengottuvelu, head of engineering Hamid Dadkhah, and Zach Bruggeman, principal engineer and founding engineer of Inspect. Today, we cover:
If you’re like us, you might wonder what the point would be of building your own harness and investing the time and resources in it, given all the choices already out there. This article sets out to answer that question, to understand why other places chose a similar path, and how a non-AI frontier lab can build more efficient tooling than what the frontier AI labs offer. It looks like the “buy, don’t build” tooling convention might not apply to AI tools! Let’s get into it. The bottom of this article could be cut off in some email clients. Read the full article uninterrupted, online. 1. What is Inspect?Inspect is Ramp’s internal background coding agent, shipped and opened internally last November. Engineers at Ramp can use any tool they want, but 75% of merged PRs are now raised by Inspect; a clear indication that many engineers prefer the tool over others:
A couple of things make Inspect different from coding agents like Claude Code and Cursor:
Inspect verifies all its changes. As a remote development environment with full tooling access, it can “close the loop” and confirm the changes it makes work:
At present, most third-party AI harnesses cannot do these kinds of verifications ‘out of the box’ because they lack internal integrations with things like telemetry and feature flag systems. Also, almost a year ago, Ramp built screenshot verification before it was supported by third-party vendors. Things like this placed Ramp months ahead of nearly all AI coding harnesses, and they could also build a far better feedback loop in their own harness. Rapid adoption when background agent releasedThe v1 of Inspect was a Chrome extension for designers to prompt AI to make minor website changes. A few months later, the v2 version with background agents followed.
By January of this year, just two months after the v2 launch, around 60% of PRs at Ramp were authored by Inspect, which increased to 75% by May. At Anthropic, Claude Code won rapid adoption after an internal release, as covered in the deepdive How Claude Code is built. Then Inspect hit a neat milestone in July, crossing the one million total sessions mark:
2. Why build your own background coding agent?There are a few reasons why Ramp decided to turn down tried-and-tested products and create their own:
Inspect started as a designer’s frontend tool, and a good part of its team were frontend engineers with interests in UX and speedy performance. The v1 was a Chrome extension for visual edits, where a user could highlight an area and tell the AI what minor website changes to make, like copy edits and button placements. The task of building a tool for making UI edits with AI was given to two frontend engineers, Zach Bruggeman and Jason Quense, who aside from their frontend domain knowledge, brought a welcome adversarial perspective, as they were less than fully convinced by AI at that time. People liked v1 but it wasn’t adopted because engineers already knew how to go to a file and edit a single line of code, so didn’t have a reason to use it, and it also required setting up a local development environment, making it too complicated for non-devs. For the current iteration of Inspect (released November 2025) the team pivoted. They built Inspect v2 as a remote development environment with a coding agent on top. Setting it up as a remote environment that they could configure centrally removed the need for local setup on each machine. They were also encouraged by seeing that OpenCode, the open-source coding agent which serves as Inspect’s harness, exposed an HTTP API which made it straightforward to set up, and was open-source, good enough, and importantly, offered model agnosticism. Check out the episode of The Pragmatic Engineer podcast with OpenCode creator, Dax Raad. After pivoting, adoption skyrocketed to where it is today:
Adoption numbers today:
3. How Ramp uses InspectHaving built it, Ramp uses Inspect for a few things:
Here’s an example of how debugging works. Devs can ask the agent to investigate an issue, and Inspect goes off and pulls data from the correct sources:
The tool goes and makes database or Snowflake queries when helpful:
The debug agent can be long-running while it gathers data from various sources. Finally, it presents its findings:
This debugging example illustrates how much more capable agents can be with the correct access to tools, data, and context. Some internal agents built on top of Inspect:
Visualized:
It’s clever that the Ramp team extended Inspect into a platform, and made it easy to build additional agentic tools, without engineers having to worry about the cloud backend for those tools. Not bad for a tool that started as a simple Chrome extension almost exactly a year ago! 4. Architecture and tech stackInspect’s core principle is that agents should have access to the same context and tools as software engineers. Hooking up Inspect to the data sources that engineers would browse with the same tools seems to be a key difference between Inspect and third-party AI harnesses... Subscribe to The Pragmatic Engineer to unlock the rest.Become a paying subscriber of The Pragmatic Engineer to get access to this post and other subscriber-only content. A subscription gets you:
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