Milestone and the Growing Need to Measure AI’s Real Impact on Engineering

At AI Dubliners, we don’t just share a company once. We also follow how they evolve over time. Milestone is exactly that kind of company.

We first featured Milestone in November 2025. At the time, the company was drawing attention with a $10M seed round. But what caught our attention wasn’t the funding itself, it was the question they had taken ownership of: AI has started writing code. But does it actually work?

Today, that question matters more than ever. Most developers now use AI tools every day. A significant share of the code being produced is AI-assisted. Companies are integrating AI into their workflows at speed. Yet many organisations still don’t have a clear answer to: Are these tools really improving productivity? Are they improving code quality? And where, exactly, does the return on investment show up?

This is precisely where Milestone positions itself. By bringing together code repositories, project management systems, team structure, and AI coding tools, the company aims to make AI’s impact on engineering teams visible. In other words, it tries to ground AI’s impact in data rather than guesswork.

You can see this shift in the company’s recent activity, too. AI Workflow Automation. Multi-Agent Systems. Engineering Intelligence. And, more recently, its “Vibe Metrics” approach. All of these feel like different pieces of the same shift. The focus is no longer simply using AI. It’s understanding how AI works, how it creates value, and how it affects teams. Because in the AI era, claiming productivity is easy. Showing that value was actually created is harder.

Another detail that makes Milestone interesting to us is its Dublin roots. The academic collaboration between founders Liad Elidan and Prof. Stephen Barrett, which began at Trinity College Dublin, has grown into a technology company now serving global customers such as Kayak, Monday. com, and Sapiens. Their collaborations with names like GitHub, Atlassian, and NVIDIA show the scale of that journey.

Just as we did in November 2025, we continue to follow Milestone with great interest today. Because the real value of AI often isn’t found in new models. It’s found in more measurable engineering, in more informed AI investments, and in teams where humans and AI work better together.