Hi, I'm Nishtha.

I lead design and research at Workato, where I'm building the platform that gives a flock of unpredictable AI agents their rules and shape.

Design leadership

What does it take to build an agent platform in an evolving market?

Leading design through a product split, a strategic reversal, and a compressed launch; then using research findings to reshape how enterprise agents are built, tested, and governed.

Design direction

How do you supervise an AI fleet while neck-deep in your own work?

Designing a peek-a-boo bar that keeps a fleet of agents within reach across Workato, so people can supervise, steer, and queue parallel work without leaving their current task.

Co-inventor

Can streamed AI responses have conversational etiquette?

Replacing a jittery, ambiguous response stream with a patented conversational cue that shows when AI is still responding and when it is the user's turn.

Product incubation

Where is the product hiding inside a newly emerging protocol?

I used working prototypes and early practitioners to understand MCP, recruit a small team, and ship before the opportunity reached the roadmap.

Organization design

When designers can build software, what changes about the team?

Giving a 22-person design team the tools, skills, and career incentives to turn ideas into working prototypes with Claude Code changed both what designers could build and how they worked with engineering.

Hands-on design

Why has a workflow editor from 2019 thrived for seven years?

Reflecting on the recipe editor I designed in 2019, I explore how a durable interaction model has evolved gracefully from integrations to copilots and agent skills.

Some tinkering. A few musings.

The mirror

The murmuration

Recipe editor

Capability to product

AI Maturity Levels

Agents, not features

Voice, trust, machines

The disposable prototype

Nishtha presenting on stage at a Workato conference

I've been leading Product Design and Research at Workato for the last 10 years. In that time, design has scaled from one person to a 22-person global team. I'm quietly proud that it's a team almost nobody leaves.

Along the way, I've designed the same platform through three eras: integration workflows, copilots, and now agents that act on their own.

I'm formally trained in physical product design, visual communication, psychology and human factors. I've been researching how people learn to trust machines since before that question had an industry attached to it.

I'm looking to build with companies, in software or hardware, where the hard part is making powerful systems people can trust.

LinkedIn comment from Vijay Tella, Co-founder and CEO of Workato: “Nishtha Mehrotra - I'm incredibly grateful—we're so lucky to have you leading the intuitive product experience we're known for. I've spent 30 years in integration middleware, and this tech is complex and whack under the hood. Refactoring six complex platform categories into one while making it seamless for both pro-code integration experts and business teams? No joke. What you and your team have built is one of the great feats of enterprise software design. So much so - you have created a marketing challenge as Workato confounds people. How can something that looks so easy be so powerful? What blows me away is your first-principles thinking and relentless drive to keep attacking the complexity. We don't have real competition for our product experience, productivity, and speed—our biggest challenger is ourselves. You and your team are awesome role models of our core value to keep raising our game. Thank you.”

From Vijay Tella, Workato’s CEO

Where is the product hiding inside a newly emerging protocol?

Contribution
Founder/sponsor of the effort
Team
Small cross-functional crew
Timeframe
2025–2026
Outcome
Capabilities shipped outside formal roadmap; fed back into platform strategy

The bottleneck

Enterprise roadmaps move at enterprise speed. The Model Context Protocol didn't. When MCP made it possible to put Workato's capabilities directly inside AI assistants, waiting for the formal process meant arriving after the moment. So I built a different kind of team: small, scrappy, empowered to iterate and ship without a PRD in sight.

How it ran

Team size, cadence, what shipped — list 2–3 concrete MCP apps. The rule was disposability: everything shipped was allowed to be wrong, cheap to replace, and instructive either way. The team's output fed the platform strategy — MCP evolved from an API-platform component to a first-class project asset with verified user access — but the deeper output was proof that a design-led team could ship production capability outside the machine.

The formal roadmap is how an enterprise ships what it already believes. The skunkworks is how it learns what to believe next.

Outcome

Apps shipped
Weeks, not quarters
MCP → first-class platform asset
MCP app in an assistant surface