Product Manager · Applied AI · B2B SaaS
I ship LLM and agentic products into B2B SaaS — scoping what the model should own, where the human stays in the loop, and how we know it worked. An engineering foundation, and a bias for measurable outcomes.
Bangalore, India · Open to opportunities22 Anthropic Academy certificates · 2026
01 — Profile
Nearly two years owning AI-powered B2B SaaS end to end. I lead cross-functional squads across engineering, design, and go-to-market — and use a technical background to pressure-test feasibility and make informed trade-offs.
Data-informed prioritization. Customer research paired with product analytics. Clear PRDs as a single source of truth, and delivery that stays predictable.
Agentic workflows, tool integration over MCP, subagent orchestration, retrieval and context design, model evaluation & guardrails — the product layer that decides what the model owns and where the human stays in the loop.
02 — Impact
Activation lift from an onboarding redesign, validated by A/B test across 1,200 users.
Onboarding drop-off eliminated at the point of highest funnel friction.
Less auth friction — login time cut while session depth rose 25%.
New users onboarded in week one of a cross-functional GTM launch, beating target.
03 — Experience
An AI hiring platform automating resume screening, skill assessments, and AI-led interviews. I own AI-driven features end to end — discovery, PRDs, sprint & release planning — and shape roadmap direction.
Defined a 3-pillar roadmap tied to quarterly OKRs, giving engineering clear priorities and cutting scope-creep before sprint start.
Joined with an engineering focus and converted to full-time PM. Owned the full lifecycle of an AI writing SaaS from discovery to release.
04 — Featured Projects
05 — Case Studies
The bet, the job, the metric that matters, where it's fragile, and what I'd ship next. Sourced facts, argued conclusions.
The fastest-growing SaaS ever measured did not win on model quality — it won on where it chose to sit. A teardown of the wedge, the enterprise handoff, and the one dependency that should keep its PMs up at night.
56.5M daily actives and 10M people on a 365-day streak. The gamification is the famous part — the interesting part is that Duolingo optimizes a habit metric while selling a learning outcome, and has done it for a decade without the gap catching up.
Notion sold AI as a $10 add-on, then killed the add-on and folded it into a $20 plan. That reversal is the most useful packaging lesson available to anyone shipping AI into an existing product — and it wasn't really about pricing.
A Hack Week project became 20% of Spotify's streaming volume. The machine learning is the least interesting part — what made it work was a constraint most personalization products refuse to accept.
06 — Toolkit
Strategy · Roadmapping · Discovery · Lifecycle Ownership · PRDs & Specs · Backlog · Sprint & Release Planning · OKRs & KPIs · GTM
LLM Applications · Agentic Workflows · Tool Use & MCP · Subagent Orchestration · Retrieval & Context Design · Prompt Engineering · Model Evaluation & Guardrails · Human-in-the-Loop UX
User Research · Customer Interviews · Usability Testing · JTBD · Market & Competitive Analysis · Persona Development
Mixpanel · Amplitude · Google Analytics · Microsoft Clarity · Hotjar · A/B Testing · Funnel & Cohort Analysis · SQL
Agile / Scrum · Backlog Refinement · Release Management · RICE · MoSCoW · Kano
B.Tech, Computer Science (AI Specialization) · CGPA 9.4 / 10.0 · Hands-on with the Claude API, Claude Code & MCP — I prototype to pressure-test feasibility before I spec it
07 — Certifications & Credentials
AI Fluency for pK-12 EducatorsLearning path completed — 2 of 2 courses, Jul 2026
Anthropic's framework for working with AI deliberately — delegation, description, discernment, and diligence — applied across audiences.
The developer surface of the platform — API, tooling, and the agentic coding workflow — enough to prototype and pressure-test feasibility myself.
How agentic systems actually get built and shipped — tool integration via MCP, subagent orchestration, and enterprise cloud deployment.
Earlier credentials and the community work alongside them.
Anthropic Academy issues course-completion certificates, not proctored exams. Listed here because the coursework — agents, MCP, evaluation, deployment — is the substance behind the AI product work above.
08 — Writing
Scope-creep rarely starts in engineering. It starts in a vague line item nobody pushed back on. Here's the filter I run before anything enters a sprint.
Analytics told me where users left. It took session replays and interviews to understand why. A field note on pairing quantitative and qualitative signal.
A technical background is a superpower for a PM — until it quietly turns you into a bottleneck. How I use feasibility instincts without stealing decisions from engineers.
09 — Contact