Company
Oracle NetSuite
Time & Role
2025.08-2025.12 Lead UX Designer
From Code-First Deployment to Agentic Orchestration
Overview
Overview
For years, NetSuite’s developer-centric deployment flow left non-technical administrators without a safe, intelligible way to move customizations across environments—pushing them toward risky workarounds and driving significant operational strain.
As UX Lead, I led the transition from code-heavy execution to a guided, point-and-click orchestration, and later evolved it into an AI-native, agentic workflow that proactively surfaces dependencies, explains risk, and guides resolution—transforming deployment from manual troubleshooting into a state of system-supported confidence.
For years, NetSuite’s developer-centric deployment flow left non-technical administrators without a safe, intelligible way to move customizations across environments—pushing them toward risky workarounds and driving significant operational strain.
As UX Lead, I led the transition from code-heavy execution to a guided, point-and-click orchestration, and later evolved it into an AI-native, agentic workflow that proactively surfaces dependencies, explains risk, and guides resolution—transforming deployment from manual troubleshooting into a state of system-supported confidence.
Role
Role
End-to-end UX design lead
End-to-end UX design lead
Stakeholders
Stakeholders
Product manager, UX researcher, Developer, Tech writer, Content designer, Data scientist, Consultants
Product manager, UX researcher, Developer, Tech writer, Content designer, Data scientist, Consultants
Domain
Platform & Admin experience, DevOps, AI pattern interaction
Platform & Admin experience, DevOps, AI pattern interaction
Impact & Outcome
Impact & Outcome
Bridging the gap by delivering a new feature that empowers non-technical users to confidently manage deployments, aligning NetSuite’s functionality with user needs.
Bridging the gap by delivering a new feature that empowers non-technical users to confidently manage deployments, aligning NetSuite’s functionality with user needs.
400K+
Legacy bundles prevented from further misuse as deployment workarounds.
60%
Deployment-related support tickets volume addressed at the root cause level.
90%
Increased adoption rate of the deployment tool from 25% to 90%.
Agentic workflow
Established a concrete, in-production agentic workflow pattern for NetSuite’s complex enterprise operations.
Context
Context
NetSuite is widely known for its extensibility. Customers tailor the platform by creating large volumes of custom objects—such as custom records, fields, workflows, and scripts—to fit their unique business processes.
To reduce risk, administrators and developers typically build and test these customizations in a sandbox environment, then deploy them to production once they’re ready. This sandbox → production movement—known as deployment—is a critical but high-risk operation: missing dependencies or configuration mismatches can block releases or cause production issues.
As NetSuite customers grow, deployment increasingly becomes the responsibility of non-technical administrators, not just developers—making clarity, predictability, and system guidance essential.
NetSuite is widely known for its extensibility. Customers tailor the platform by creating large volumes of custom objects—such as custom records, fields, workflows, and scripts—to fit their unique business processes.
To reduce risk, administrators and developers typically build and test these customizations in a sandbox environment, then deploy them to production once they’re ready. This sandbox → production movement—known as deployment—is a critical but high-risk operation: missing dependencies or configuration mismatches can block releases or cause production issues.
As NetSuite customers grow, deployment increasingly becomes the responsibility of non-technical administrators, not just developers—making clarity, predictability, and system guidance essential.
Problem
Problem
Through research, we discovered that most non-tech users weren’t using NetSuite’s intended deployment flow at all. Instead, they hijacked an old packaging tool—Bundler—to push customizations between accounts. This workaround spawned 400 K+ “misused” bundles and drove 60 % of deployment-related support tickets, flooding both data and support queues.
The real problem is the misaligned experience that pushed users to the wrong tool.
Through research, we discovered that most non-tech users weren’t using NetSuite’s intended deployment flow at all. Instead, they hijacked an old packaging tool—Bundler—to push customizations between accounts. This workaround spawned 400 K+ “misused” bundles and drove 60 % of deployment-related support tickets, flooding both data and support queues.
The real problem is the misaligned experience that pushed users to the wrong tool.
Whydidasafer,intendeddeploymentflowseelowadoption—whilealegacytoolbecamethedefaultforreal-worlddeployments?
Whydidasafer,intendeddeploymentflowseelowadoption—whilealegacytoolbecamethedefaultforreal-worlddeployments?
User Research
User Research
To understand why users bypassed the intended Copy to Account flow and relied on Bundler instead, we conducted research with 30+ customers and internal NetSuite consultants who regularly help customers resolve deployment issues.
To understand why users bypassed the intended Copy to Account flow and relied on Bundler instead, we conducted research with 30+ customers and internal NetSuite consultants who regularly help customers resolve deployment issues.
Although Bundler provided more clarity than Copy to Account by exposing object dependencies, it was never designed for safe deployment. Hidden dependencies, late failures, and poor visibility into outcomes remained systemic problems—making deployments risky despite the apparent transparency.
Although Bundler provided more clarity than Copy to Account by exposing object dependencies, it was never designed for safe deployment. Hidden dependencies, late failures, and poor visibility into outcomes remained systemic problems—making deployments risky despite the apparent transparency.
Objects often have nested, hidden, or locked dependencies
Objects often have nested, hidden, or locked dependencies
Errors are discovered late, often after deployment
Errors are discovered late, often after deployment
Users lack a clear way to know of what has been deployed, what might break, and why
Users lack a clear way to know of what has been deployed, what might break, and why
User Flow
User Flow
With these insights, I studied users’ common deployment workflows and began designing several deployment flows that better aligned with how admins plan, validate, and ship changes in practice.
With these insights, I studied users’ common deployment workflows and began designing several deployment flows that better aligned with how admins plan, validate, and ship changes in practice.
Solution Phase 1
Point-and-Click
Solution Phase 1
Point-and-Click
I redesigned deployment as a clear, guided workflow that allows users to deploy multiple custom objects at once, while making dependencies and validation explicit before execution.
The system automatically surfaces nested and locked dependencies, enabling users to understand scope and risk without guesswork. By shifting error detection and validation upstream—before production deployment—the experience replaces late-stage failures with predictable, resolvable feedback.
This realignment of visibility, control, and timing redirects users away from fragile workaround tools and back to the system’s intended deployment path.
I redesigned deployment as a clear, guided workflow that allows users to deploy multiple custom objects at once, while making dependencies and validation explicit before execution.
The system automatically surfaces nested and locked dependencies, enabling users to understand scope and risk without guesswork. By shifting error detection and validation upstream—before production deployment—the experience replaces late-stage failures with predictable, resolvable feedback.
This realignment of visibility, control, and timing redirects users away from fragile workaround tools and back to the system’s intended deployment path.
The AI-first shift:
Rethinking Deployment as an AI-Native Workflow
The AI-first shift:
Rethinking Deployment as an AI-Native Workflow
In 2025, as the next generation of NetSuite embeds conversational AI and agentic workflows across the suite, I began rethinking how deployment could evolve from a guided UI into an AI-native, system-assisted experience.
we conducted research to understand administrators’ mental models of AI—how they perceive AI as an assistant versus an autonomous agent, where they expect control, and where they welcome system initiative. These insights shaped not only how AI shows up in the workflow, but when it should act and when humans should remain in the loop in our ERP.
In 2025, as the next generation of NetSuite embeds conversational AI and agentic workflows across the suite, I began rethinking how deployment could evolve from a guided UI into an AI-native, system-assisted experience.
we conducted research to understand administrators’ mental models of AI—how they perceive AI as an assistant versus an autonomous agent, where they expect control, and where they welcome system initiative. These insights shaped not only how AI shows up in the workflow, but when it should act and when humans should remain in the loop in our ERP.
I actively contributed to defining NetSuite’s emerging AI patterns—shaping how conversational interfaces and agent behaviors should work across complex enterprise workflows.
I actively contributed to defining NetSuite’s emerging AI patterns—shaping how conversational interfaces and agent behaviors should work across complex enterprise workflows.
Solution Phase 2
Agentic workflow
Solution Phase 2
Agentic workflow
To make deployment truly AI-first, I didn’t start by adding agents—I started by evaluating where agentic behavior actually made sense. Deployment is a high-risk workflow, so the goal wasn’t full automation by default, but intelligent collaboration between humans and the system.
By defining when agents should act, when they should assist, and when they should step back, the deployment flow shifts from manual execution to system-guided orchestration—reducing effort and uncertainty without sacrificing trust or accountability.
This pattern became a reference for NetSuite’s AI evolution and was presented at SuiteWorld 2025, with strong positive feedback from enterprise customers.
To make deployment truly AI-first, I didn’t start by adding agents—I started by evaluating where agentic behavior actually made sense. Deployment is a high-risk workflow, so the goal wasn’t full automation by default, but intelligent collaboration between humans and the system.
By defining when agents should act, when they should assist, and when they should step back, the deployment flow shifts from manual execution to system-guided orchestration—reducing effort and uncertainty without sacrificing trust or accountability.
This pattern became a reference for NetSuite’s AI evolution and was presented at SuiteWorld 2025, with strong positive feedback from enterprise customers.
Intent-based deployment via conversational entry point
After creating a custom object, users can initiate deployment through Ask Oracle. A deployment agent interprets user intent to identify the relevant objects and target account—eliminating manual setup.
After creating a custom object, users can initiate deployment through Ask Oracle. A deployment agent interprets user intent to identify the relevant objects and target account—eliminating manual setup.
Post-deployment summary and customizable reporting
After deployment, the AI generates a summary report. Users can tailor the report by selecting specific objects or details, adapting it for different stakeholders.
After deployment, the AI generates a summary report. Users can tailor the report by selecting specific objects or details, adapting it for different stakeholders.
Human-in-the-loop error handling and guided resolution
When errors or warnings occur, users stay in control while the AI provides contextual explanations and guided resolution paths—reducing trial-and-error without automating high-risk decisions.
When errors or warnings occur, users stay in control while the AI provides contextual explanations and guided resolution paths—reducing trial-and-error without automating high-risk decisions.
Additional agentic workflow patterns are confidential—feel free to reach out to learn more.
Additional agentic workflow patterns are confidential—feel free to reach out to learn more.
Proactive Extension: Reimagining the IDE Experience
While my primary focus was the web-based deployment engine, I recognized a critical friction point for "power users" who spent their time in VS Code. I proactively proposed and led the UX optimization for the SuiteCloud IDE extension to ensure a unified deployment experience across the NetSuite ecosystem.
While my primary focus was the web-based deployment engine, I recognized a critical friction point for "power users" who spent their time in VS Code. I proactively proposed and led the UX optimization for the SuiteCloud IDE extension to ensure a unified deployment experience across the NetSuite ecosystem.
More Details Available Upon Request
Due to confidentiality, I’m unable to share further details publicly. I’d be happy to share more about the design approach, scope, and impact in a conversation.
More Details Available Upon Request
This page represents key highlights from my four years at Oracle.
Due to confidentiality, I’m unable to share further details publicly. I’d be happy to share more about the design approach, scope, and impact in a conversation.
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