Launch Your Legal Tech Career: Junior Product Manager

Using the STAR method: **Situation:** I was working on a project to automate contract review, and I needed to explain the concept of Natural Language Processing (NLP) to a team of paralegals with no technical expertise. **Task:** My task was to ensure they understood the capabilities and limitations of NLP so they could provide accurate feedback on the system's performance. **Action:** I avoided technical jargon and instead used analogies. I compared NLP to how a human reads and understands text, emphasizing the system's ability to identify key clauses and potential risks. I also provided examples of how NLP worked in practice, such as highlighting key terms in a contract. **Result:** The paralegals were able to understand the core concepts of NLP and provide valuable feedback on the system's accuracy and efficiency. They felt empowered to contribute to the project and were more receptive to the new technology.

Using the STAR method: **Situation:** I was working on two product features simultaneously: one was a high-priority feature requested by a key client, and the other was a critical bug fix that affected all users. **Task:** My task was to ensure both features were delivered on time without compromising quality. **Action:** I assessed the impact of each feature. The bug fix affected all users and could potentially lead to customer dissatisfaction, while the client feature was important but not immediately critical. I prioritized the bug fix and allocated the necessary resources to resolve it quickly. I then communicated the situation to the client, explaining the importance of the bug fix and assuring them that their feature would be delivered shortly after. **Result:** The bug was fixed promptly, minimizing the impact on users. The client understood the situation and appreciated the transparency. Both features were ultimately delivered on time and met expectations.

Some of the biggest challenges include data security and privacy concerns, the slow adoption of technology by some legal professionals, the complexity of integrating new technologies with existing systems, and the need to ensure that legal tech solutions are accessible and affordable for all.

I would start by conducting thorough market research to identify unmet needs and opportunities within the legal sector. This would involve analyzing industry reports, conducting surveys and interviews with legal professionals, and evaluating competitor products. I would also focus on understanding the pain points of legal professionals and identifying areas where technology could provide a significant benefit.

I have experience working in agile environments, particularly with Scrum. I understand the principles of sprints, daily stand-ups, sprint reviews, and retrospectives. I've used tools like Jira to manage tasks, track progress, and collaborate with team members. I understand the importance of iterative development and continuous improvement.

I regularly read industry publications, attend conferences and webinars, follow thought leaders on social media, and participate in online communities. I also make an effort to network with legal professionals and other product managers to learn about their experiences and insights.

Using the STAR method: **Situation:** During the development of a legal research tool, a developer and I disagreed on the best way to implement a search algorithm. The developer wanted to use a more complex algorithm for better accuracy, while I favored a simpler, faster algorithm to improve user experience. **Task:** My task was to resolve the disagreement and ensure we chose the best algorithm for the product. **Action:** I facilitated a discussion where we both presented our arguments, supported by data and research. We weighed the pros and cons of each approach, considering factors such as accuracy, speed, scalability, and development time. We also conducted A/B testing to compare the performance of both algorithms. **Result:** Based on the A/B testing results, we found that the simpler algorithm provided a better balance of accuracy and speed. The developer agreed to implement the simpler algorithm, and the product was launched successfully with positive user feedback.