The brief
SonarQube CLI is a flagship product in my domain — but the team had limited understanding of how developers were actually using it, what was falling short, and what they'd expect from a CLI that integrated with an LLM of their choice. As AI-native workflows took hold, the stakes got higher: if Sonar's CLI didn't fit how developers worked, it risked being bypassed entirely in favour of tools that did. I initiated and led the research to find out where the gaps were.
What I did
- Designed and led the CLI research programme: Created a research plan spanning an internal survey, qualitative interviews with developers, and a competitive analysis across CLI tools in the developer ecosystem. The goal was to understand current CLI use cases, what made developers stay loyal to their existing tools, and what they'd expect from a Sonar CLI that integrated with an LLM of their choice.
- Competitive analysis: Mapped the CLI landscape to identify what competing tools were doing well and where Sonar had gaps — giving the team a clear picture of what developers were comparing Sonar against.
- Identified experience gaps: Synthesised findings into a clear view of where the current CLI experience was falling short — in terms of command language, discoverability, LLM integration expectations, and workflow fit.
- Built the sales enablement layer: Created a CLI-focused sales asset using Claude so customer-facing teams could answer product questions about the CLI clearly and consistently during customer conversations — reducing the gap between product reality and what sales could confidently explain.
- Advocated for prioritisation: Brought findings to PM and engineering leadership with a clear case for why CLI investment was strategically important — grounding the argument in workflow research, competitive positioning, and developer expectations around AI-native tooling.
What I found
- Developers weren't just using the CLI as a convenience — for many, it was the primary interface for integrating Sonar into their pipelines. A poor CLI experience had outsized impact on adoption and trust.
- The current CLI experience had meaningful gaps around discoverability, command clarity, and integration with the kinds of AI-assisted workflows developers were increasingly using.
- Developers expected CLI tools to work seamlessly alongside LLMs — not as a separate, disconnected step. Sonar's CLI wasn't meeting that expectation.
- Competing tools were moving faster on LLM integration, which meant the window to establish Sonar's CLI as the quality layer in AI-native workflows was narrowing.
The decisions this enabled
- The research gave PM and engineering leadership the evidence base to prioritize CLI investment — moving it from a backlog item to active roadmap work. The work is now in progress.
- Grounded the CLI roadmap in real developer workflow questions: command language, discoverability, LLM integration, and what a repeatable user feedback loop would need to look like.
- Gave sales a concrete, always-current resource for CLI customer conversations — reducing reliance on ad-hoc answers in demos.
- Positioned the CLI not as a standalone tool but as a critical surface for Sonar's presence in AI-native developer workflows.