greeshmagopal08
👋 About Me
I’m a Senior Product Manager with 10+ years of experience across product management, software development, business analysis, and analytics.
I currently build SaaS products in the HCM and employee benefits space, working across product, engineering, design, data, and business teams to take products from problem discovery through launch and measurement.
🚀 What I Do
Product Strategy
- Product strategy and roadmap ownership
- Product discovery and problem definition
- Prioritization and experimentation
- User research and journey mapping
- Product analytics and outcome measurement
Product Delivery
- PRDs, specifications, user stories, and acceptance criteria
- Web and mobile product development
- Cross-functional leadership
- API and system integrations
- Technical requirements and system workflows
- UX and accessibility
AI Products
- LLM-powered experiences
- AI assistants and conversational products
- AI agents and agentic workflows
- RAG and knowledge-grounded experiences
- AI evaluation and quality
- Human-in-the-loop experiences
- Responsible AI, privacy, and safety
- AI product metrics and experimentation
🧩 Product Projects
TA Tracker
A product prototype exploring how teams can identify TA workload signals and support TAs before workload becomes a bigger problem.
Product focus
- Defined the problem and target user
- Designed the core workload and check-in workflow
- Used workload signals and contextual data to support product decisions
- Considered privacy and how sensitive information should be surfaced
- Designed the experience around support rather than performance monitoring
How I built it
Built using Claude Code** with a spec-driven, agentic development workflow.
- Started with the product problem, users, requirements, and expected outcomes
- Used specifications to define workflows and expected behavior
- Used Claude Code to translate the specifications into a working prototype
- Iterated through build → review → refine cycles
- Reviewed the generated implementation and made product and UX decisions throughout
- Explored how AI-assisted development can shorten the path from product idea → specification → working software
More Projects Coming Soon
I’m building additional product case studies around:
AI Products • Product Analytics • Experimentation • Specification-Driven Development • Agentic Workflows
🤖 How I Think About AI Products
I don’t start with “Where can we add AI?”
I start with:
What problem are we solving, and does AI make the experience meaningfully better?
My approach:
01 — Problem Understand the customer, workflow, pain point, and desired outcome.
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02 — AI Opportunity Determine whether AI actually improves the experience.
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03 — Product Design Define what the AI should do, what it shouldn’t do, and when a human should be involved.
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04 — Build Use the right combination of models, data, context, tools, and product experiences.
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05 — Evaluate Test accuracy, relevance, grounding, safety, and overall experience.
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06 — Measure Measure user and business outcomes — not just AI usage.
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07 — Learn & Improve Use real-world feedback and evaluation data to continuously improve the product.
🌱 Currently Exploring
AI Product Management Building and evaluating AI-powered product experiences.
Agentic Workflows Exploring how AI agents can reason, use tools, and complete multi-step tasks.
Specification-Driven Development Using structured specifications to improve the way product ideas become working software.
AI-Assisted Development Experimenting with tools such as Claude Code to shorten the product → prototype → feedback loop.
AI Evaluation Thinking about how to measure quality, reliability, grounding, and user value.