MongoDB AMP Application Analysis
Timeline
Jan '25 - May '25
Team
2 Product Managers, 2 Designers, 10 Engineers
TLDR;
The App Modernization Platform (AMP) is an early-stage B2B consulting and developer tooling initiative helping enterprises convert from relational databases to MongoDB while modernizing their legacy apps.
I led multi-phase 0→1 research, identifying app analysis as a critical blocker and intentionally driving focused discovery in this area to shape product strategy pre-launch. The resulting analysis tools are now adopted by 90%+ of consultants and have helped accelerate projects by up to 3x.
Context: Modernizing legacy apps is a slow and complex process, thus the AMP team sprouted to help enterprises do it faster and safely with AI developer tools and expert consultancy services
As a UX researcher on AMP, I supported 5+ globally distributed product teams that cover every step of modernization from app analysis and data modeling to data migration, testing, and code generation.
AMP is a massive product space, so we mapped the service end-to-end to find where research could make the biggest impact
I teamed up with another UX researcher to dig through everything we could find on AMP (decks, docs, customer notes, Slack channels), plus anything external about modernization. We then each led our own co-design sessions with stakeholders, like PMs and engineering leads, to figure out how all the pieces and people fit together, spot friction points, and align on how we think the process currently works.
We wrapped it all up in a service blueprint that became a go-to for onboarding. I continued to add more details as I learned more over time.
I prioritized discovery research in app analysis because I realized modernization can't START without this step, and it was a major time-sink for our consultants
I scoped discovery into a few phases to understand the different analyses consultants perform and clarify their core tasks and goals. This was to give my team a more granular understanding of the process and help them build specifically for each type of analysis.
Like everything else in software development, and especially modernization, app analysis is complicated and technical. I didn't want to give me team only high-level view of the process. I wanted to dive deep into how our consultants approach large, legacy "spaghetti" apps. This means things like source code inspection, stored procedure dependency mapping, complexity analysis, project planning, and might as well also pressure-test our early product ideas.
I partnered closely with product, design, and engineering, to make sure insights shaped action in real time
Kept regular contact with stakeholders to consult on research plans, project pivots, and product strategy via 1:1s, team meetings, Slack threads, and document comments
Invited PMs, designers, and interested engineers to sessions
Left takeaways and notes after each session in a central document
Shared preliminary insights after the last session with the whole team before I complete a more detailed synthesis and recommendations
Wrapped up projects with a presentation (key insights, session clips, recommendations) and discussion so the team can be up-to-date on what's already happening and next steps
Impact: Research shaped the roadmap for AMP’s app analysis tools, now adopted by 90%+ of consultants to accelerate modernization projects by up to 3x
I ensured research insights translated directly into product requirements, helping app analysis become one of AMP’s most mature toolsets. Consultants can now focus more on executing modernization — the code changes and implementation work — rather than spending time figuring out how to approach the project in the first place.
After the initial discovery, I also did deep dives across other AMP product areas like data modeling, data migration, and testing to build a more holistic perspective and understand cross-product relationships. The goal is to move the team toward a clearer north star: connecting tools into an integrated workflow that could potentially support a more self-serve (rather than consultant-led) platform.
