I build developer platforms, SDKs, APIs, and practical AI harnesses for real engineering and business workflows.

My current focus is AI transformation on top of developer-platform fundamentals: using agents, retrieval, tools, evaluation, and guardrails to make workflows faster, safer, and more trustworthy.

At Cisco Webex, I work across developer platform, SDK/API integration, and AI transformation. I have spent years helping partners and engineering teams build on Webex capabilities across meetings, messaging, calling, contact center, WebRTC, widgets, and extensible UI frameworks.

• AI agents for SDLC workflows: PR review, test triage, docs, onboarding, and developer support
• AI workflow improvement for business teams beyond engineering
• Agent harness architecture with clear context, tool boundaries, and human approval points
• RAG and context engineering for code, docs, tickets, and team knowledge
• Evaluation patterns that make AI outputs trustworthy enough for real workflows
• Developer-platform patterns for SDKs, APIs, widgets, and partner integrations

I'm a Software Engineering Technical Leader at Cisco Webex, working on AI transformation, developer platforms, SDKs, APIs, and partner-facing integration experiences. I have contributed to open-source and platform work around Webex, with a focus on making complex collaboration capabilities easier for developers and customers to adopt.

I like the intersection of developer experience, platform engineering, and applied AI: not demos for their own sake, but systems that skeptical engineering teams can actually adopt.

I'm starting to write about practical AI-for-work patterns:

• agent harnesses vs. prompts
• context and retrieval design
• tool boundaries and approvals
• evals and guardrails
• where AI actually helps teams move faster

I'm always happy to compare notes with builders, engineering leaders, and teams exploring how AI can improve real workflows.