Fractional product and UX leadership
Clarify product direction, raise design quality, structure critique, and create practical operating mechanisms.
Agent-readable profile · Public
Praneet Koppula
Product design and UX leader who makes expert engineering tools, complex workflows, and AI product behavior easier to understand and trust.
Reading note: this page is a concise public profile for people and software agents. Project status labels distinguish shipped work, product concepts, leadership systems, and ongoing experiments.
Experience18+ years
LocationSan Francisco in person · U.S. remote
Current focusAI design experiments and complex workflows
Practice
Useful when a product is technically ambitious, behaviorally unclear, or needs senior design judgment without a full-time leadership hire.
AI interaction and trust
Define agent behavior, user control, confirmation, provenance, recovery, and appropriate human escalation.
Research and validation
Turn uncertain product questions into focused evidence plans, evaluative studies, and decision-ready synthesis.
Complex workflow design
Make system state, constraints, technical dependencies, and failure conditions easier to understand and act on.
Selected evidence
These summaries are deliberately bounded. Proprietary work is described through public context and redrawn abstractions.
AI partner for model-based engineering
Led the UX vision with an engineering lead for an assistant connecting requirements, architecture, implementation, simulation, and explanation. Tested the concepts with customers through user interviews and validation tests, then refined interaction patterns for visible context, traceability, confirmation, and human control.
Model Slicer workflows
Designed state-aware interactions and simulation-aware slicing prototypes involving starting points, exclusions, constraints, data provenance, time windows, and invalid states. Local primary artifacts support the contribution; redrawn visuals protect proprietary details.
Actionable Simulink diagnostics
Researched dense diagnostic states and helped shape message hierarchy, safe Fix-It behavior, and suppression workflows. The case separates direct design work, engineering collaboration, later product evolution, and exploratory strategy.
Task-based UI across engineering apps
Authored pattern guidance, contributed concepts during a Radar app workshop, documented the team's design decisions, and later served as a formal coach and reviewer. The shared strategy and workshop method remain team-owned.
Mask Editor as a technical authoring environment
Authored validation and constraint directions, facilitated team synthesis, mentored a broader discovery effort, and co-authored an unshipped studio vision. Later public capabilities are context, not a causal claim.
Customer workflows as a portfolio operating system
Authored and contributed structures that connected workflow evidence, product ownership, research questions, and investment decisions. The case presents the operating model without claiming quantified adoption.
Distributed UX leadership systems
Built planning, coaching, and decision mechanisms across a distributed UX leadership context. Personnel details and internal measures remain private; the public case focuses on the operating system and qualitative outcomes.
Writing
First-person essays connecting current AI design practice to a longer history of complex systems work.
Closed-Loop Experience Design
Praneet traces an idea from designing beside a developer in 2014 to direct collaboration with coding agents, then develops a research agenda for shaping physical system behavior through simulation and research with affected people.
Public AI design experiments
Ongoing repositories used to explore how agents understand workflows, validate interfaces, and support product and design practice.
Agent UX validation
A product and research exploration of agent-callable UX validation for AI-generated applications.
Design workflows for coding agents
Codex-native design and engineering workflows, including reusable design-review and implementation skills.
GitHub pull-request mapping
A compact experiment in making repository and pull-request relationships easier to inspect.
Start with the product question.
Available for fractional, advisory, and focused contract work. San Francisco in person and U.S. remote.