Mike Long

Leadership intro

Snowflake Design Leadership Case Study

From platform complexity to trusted AI workflows.

Updated Feb 25, 2026

Context
Platform product work spanning enterprise data, AI workflows, and multi-surface systems where mistakes carry real cost.
Role & scope
Design leader and hands-on operator shaping product direction, design systems, and execution rhythms across product teams.
Outcome
A repeatable way to make complex workflows legible, governable, and easier for teams to ship without losing trust.

Artifacts

The visual proof behind the outcome.

Selected frames and diagrams that show the structural decisions, not just the final polish.

Nexla workflow after redesign
Workflow after redesignA workflow surface designed to make state, decisions, and next actions easier to read.
Nexla workflow before redesign
Workflow before redesignThe baseline experience that created hidden state and inconsistent decision paths.
Execution pattern diagram
AI execution patternThe control loop I use for AI-assisted workflows: propose, preview, explain, and apply.

Leadership Narrative

  • Improve product clarity and team operating systems together
  • Lead in domains where workflow trust, governance, and delivery speed all matter
  • Stay hands-on enough to shape structure, not just direction

Across Pivotal Cloud Foundry, GitLab, Shortcut, and Nexla, the throughline has been consistent: clarify how a complex system works, make the next decision easier, and create an operating rhythm that helps teams ship without avoidable confusion.

  • First full-time designer
  • Partnered directly with CEO and product leadership
  • Owned end-to-end UX across 50+ product surfaces
  • Shipped a new 0 -> 1 product while tightening the core platform

Nexla is the closest proof point for the type of work I want to keep doing: enterprise data workflows, AI assistance inside the product, and design leadership in a system where users need confidence before speed matters.

  • AI proposes mappings and transforms, but the user reviews the diff
  • Preview and validation happen before irreversible action
  • The system explains why it is making a suggestion and where data will go
  • Safe defaults come first, with expert control when it matters

I am most interested in AI when it improves workflow clarity instead of competing with it. The right interaction model is not a separate chatbot. It is an embedded control loop that helps users move faster without giving up orientation or accountability.

  • Unified Nexla core and Express.dev so they felt built by the same company
  • Established shared tokens, components, and workflow patterns
  • Socialized standards by shipping design -> code -> PR review loops
  • Built feedback rituals that helped design, product, and engineering stay aligned

This is where leadership compounds. The work is not only the screen. It is the pattern library, the decision language, and the review cadence that makes good work repeatable.

Why This Role

  • Snowflake is increasingly the system of record for data and AI workflows, where the cost of confusion is high
  • Users need consistent patterns across build, govern, observe, and share surfaces
  • My focus is making advanced workflow actions feel safe, obvious, and auditable, then scaling that through shared systems

What trusted workflow means in practice:

  • Legible: states, inputs, and outcomes are obvious
  • Governable: permissions, policy, and review points are visible
  • Observable: users can see logs, lineage, and system reasoning
  • Shippable: teams have patterns and systems that scale

Case Map

The two flagship cases in this portfolio show the combination I care about most:

  1. BYO Code Flows demonstrates power-user workflow design without chaos.
  2. Schema Template Designer demonstrates how to turn a complex data model into a repeatable contract workflow.

Together they show how I approach trust, structure, and implementation pressure in enterprise product design.