I am a Product Manager with an IIT and IIM background, currently working at a Silicon Valley agentic frontier startup lab. My work sits at the intersection of product strategy, data systems, applied AI, and business outcomes. I specialize in building intelligence-first products where data, reasoning, and automation are embedded directly into workflows. This includes agentic systems that orchestrate data ingestion, analytics, decision intelligence, and execution across real business functions such as finance, operations, and supply chain. My focus is on durable systems that compound value over time, not surface-level AI features or demos. My product experience is deeply rooted in data. I have worked extensively on data-heavy products involving complex ingestion pipelines, transformations, analytics layers, workflow builders, and stateful execution systems. I am comfortable operating across raw data, master data, metrics design, and downstream decision layers, and I approach product problems with a strong systems and modeling mindset rather than a purely UI or feature-driven lens. Alongside this, I bring a strong business analysis and strategic foundation. I spend significant time on problem framing, defining success metrics, evaluating tradeoffs, and aligning product direction with business outcomes such as adoption, ARR impact, expansion, and operational leverage. I think explicitly about pricing, packaging, GTM readiness, and narrative clarity, especially in the context of AI-native and enterprise products. I do not view product management as limited to agile rituals or backlog execution. I operate across strategy, discovery, execution, and learning loops, with a clear bias toward outcome-driven decision-making. I am equally comfortable working with engineering on system design, with data teams on models and pipelines, and with business stakeholders on priorities, ROI, and go-to-market implications. A key area of my work is agentic product operations. I design product ops systems where planning, discovery, execution tracking, feedback, and decision-making are partially automated and intelligence-driven. This includes building workflows that connect customer signals, data telemetry, and execution systems to reduce manual overhead, improve signal quality, and increase decision velocity for product teams. Overall, my strength lies in operating in complexity. I enjoy working on ambiguous, data-intensive, and system-heavy problems where product decisions require balancing technical constraints, business realities, and long-term leverage. I am particularly interested in how product management evolves in an AI-first world, where intelligence, orchestration, and automation fundamentally change how products are built and operated.