KDB.AI

Drove +19% activation by designing the Developer Interactions Framework and removing pre-activation blockers for KX's AI vector database.

Problem

KDB.AI had no design foundation and no user research baseline. Developers were dropping off before reaching product value, not because the product was weak, but because the path to value was invisible.

Solution

I defined two developer personas, built a Developer Interactions Framework adopted company-wide, and redesigned onboarding, guidance, and pricing clarity to eliminate activation blockers. Result: +19% activation rate, reduced support escalations, and a framework that scaled to other KX products.

My Role

Senior Product Designer on KDB.AI, KX’s AI vector database. Reported to Head of Design and CPTO; owned research, design strategy, and UI delivery end-to-end.

The Challenge

KDB.AI entered the developer market with no design language or research baseline. Developers hit activation blockers before reaching product value.

No visibility into where developers were dropping off
No pricing clarity to encourage trial
q language learning curve blocked new users before they could build anything

Two developer personas defined through interviews, surveys, and analytics: Data Builders and Analysts

Discovery

Four parallel research streams grounded the work before I designed anything:

Customer interviews with developers, data scientists, and front-office users
Surveys and desk research to validate the user landscape
In-product analytics to locate drop-off points between sign-up and activation
Cross-functional workshops with TAMs, Product, Engineering, and DevRel

The output: two distinct personas with overlapping and diverging needs. Data Builders (embedding, ingesting, building applications) and Analysts (querying and exploring). These became the lens for every design decision and drove PM roadmap prioritization in Aha.

What I Built

Developer Interactions Framework: codified design principles adopted company-wide
Onboarding & guidance system: tutorials, pricing transparency, and learning resources
Dynamic pricing calculator: AI-driven prototype using telemetry to recommend tiers
Q coding agent: prototype reducing debugging time and providing language guardrails
API parity redesign: consistent patterns across Python, q, and REST

Excerpt from Developer Interactions Framework with prototype of KX Agent. Pairs best-practice heuristics with AI-powered guidance including example projects and queries.

Dynamic pricing calculator wireframe. Telemetry-driven tier recommendation.

Impact

+19% activation rate by reducing time-to-value
Developer Interactions Framework adopted company-wide
Reduced support escalations through self-serve guidance
Two validated personas directly shaped product roadmap priorities

What’s Next

The framework keeps scaling. Current work that builds on this foundation:

Pre-built workflow learning paths reflecting validated personas, so users can trial KDB.AI in role-specific ways
The Developer Interactions Framework extended across the broader KX product suite and into KDB-X
IDE-native q-assistant that meets developers where they actually write code, with guardrails optimized for q
Continuous validation through in-product feedback loops and the Developer Center, so personas evolve with real input

year

2024–2025

timeline

10 months

type

B2B SaaS, Developer Tools, Onboarding, Retention

tools

Figma, GPT-4, Perplexity, Confluence, Jira, PowerBI, G-Analytics, Maze

team

3 Designers, PM, Engineering Lead, Dev Relations, Docs, VP Marketing, SVP CX

Key Takeaways

Adoption drives growthEvery flow I design is a lever for ARR and retention. Treating adoption as a strategic product layer lets companies capture the full return on their technical investments.

Content is productDocs, onboarding, and learning surfaces directly shape whether users unlock value — and whether decision-makers renew or churn.

AI optimizes returnsI use AI to unblock bottlenecks, accelerate discovery, and get more out of the team's effort so we solve problems sooner and with greater impact.

Alignment drives impactAdoption design only moves the needle with executive sponsorship. Translating design outcomes into business outcomes makes leadership treat the experience as a growth driver, not support overhead.