Inside Lob's AI upskilling sprint: 2 days to a smarter, faster dev team with DevClarity

Lob, the all-in-one platform for automating direct mail at scale, wanted to help its engineering team embrace modern AI coding practices. As an industry leader handling massive mail volumes every day, Lob believed that streamlining developer workflows would accelerate new features, cut debugging time, and free engineers to focus on deeper innovation.

They considered letting developers experiment with AI tools on their own, hoping that organic interest would bubble up. But with mission-critical deadlines looming, the risk of AI slop entering their codebase felt too high. Leaders realized a structured, hands-on approach would help their team avoid messy AI code and have a faster impact. That's when Lob partnered with DevClarity to run an on-site AI training and hackathon, ensuring every engineer—from junior to senior—got equipped with best practices, advanced workflows, and the "why" behind AI-driven coding.

In just two days of hands-on, in-person sessions, DevClarity equipped Lob's team with powerful techniques:

• • Project Rules: to provide clear context & establish consistent code patterns.
• • Inline prompting: for small, targeted changes.
• • Step-by-step task planning: transforming big JIRA tickets into clear coding sequences well-suited for AI.

Developers applied each method to live Lob code—refactoring legacy files, building new features, and learning to guide AI with precision. Working in their teams, they created standards and formed organizational-wide opinions, systematizing their AI coding approach.

One engineer noted how simply adding "anti-pattern" guidelines in Project Rules prevented repeated bad code suggestions. Another used AI to isolate commits by author and auto-generate PR summaries, shaving off hours of repetitive manual work.

By the end of the workshop, Lob's team saw tangible wins. People were less fearful of AI "breaking" their code and more confident about controlling the model with good prompts and better organizational patterns. In the words of one participant, "We realized it's more like having a really smart intern you can shape with rules and feedback—if you guide it well, you get clean, functional code fast."

Implementing DevClarity's approach took just a couple of focused sessions, yet it gave Lob's engineers a repeatable framework for staying on top of new AI tools as they evolve. The workshop cost was a fraction of a single missed sprint, and the return—speedier feature cycles, fewer debugging headaches, and sharper developer collaboration—made it a clear win. Today, Lob continues iterating on its AI workflows and exploring advanced integrations like model context protocols (MCP) that tie directly into internal systems.

For Lob, the real payoff isn't just time saved, though that helps. It's the freedom to focus on big ideas that make their direct mail platform even more indispensable. For engineering leaders wondering how to turn AI from a distraction into a force multiplier, Lob's story shows how fast that shift can happen with the right partner.