Glean
Glean Analytics is a AI-powered spend intelligence solution from New York that saves companies money by analyzing expense drivers and finding line-item level insights often overlooked by finance teams and budget owners.
When I joined the team was in their pre-revenue stage with seed funding round, and my role was to:
- improve development team feature delivery speed
- increase estimation accuracy
- help with key features for growth of the company and product
Steps I took or strongly pushed the team in order to achieve these expectations
1. Added key features towards our product stability and valuePayment processing
- enabled our revenue stream and Plaid integration
- added International payments functionality
- it gave our users more actionable invoice and vendor analysis
- increased our development velocity and cross-team understanding of the code that reduced "knowledge silos"2. Changed team communication
By having weekly team sync we managed to establish certain engineering standards that helped out our code review process significantly.
We started documeting our best practices and created a technical roadmap that would guide our decision making process and ensure code quality.
By assigning specific feature owner we enabled engineers to ask the right questions and discover potential risks to development ahead of time. This role also provided a "hub" person who had the most context relevant for that specific feature.
We started giving relevant feedback to our product managers in order to reduce the scope of potential "rabbit holes" or split the feature into MVP and Nice To Have items.
This effort eventually brough us to:
- Series A funding - TechCrunch article
- first revenue stream through introduction of Payment processing feature and extended International payments
- client base growth
- consistent track record of feature delivery and product quality