moonbatant.

Mamoon Mondal

I build AI-native products end to end — running a PLG self-serve product and an enterprise B2B agentic product in parallel, owning 0-to-1 discovery, agent design, and eval-driven reliability.

KHUMBU HIMAL · 27.99°N 86.93°E

Products & agents I've shipped.

I'm an AI product manager who builds AI-native products from zero to one. As founding PM at Supanote.ai, I run a PLG self-serve clinical-scribe product and an enterprise B2B benefits-verification agent in parallel — owning discovery, agent design, and the eval harnesses that keep them reliable in production.

Before that, at Innovaccer, I shipped AI agents that automated healthcare operations at scale, lifting per-user efficiency 4x and unifying post-acquisition product integrations.

I use AI heavily inside my own workflow too — building internal agents on Claude Code + MCP that automate program and design ops and multiply my throughput as a PM. I write about those experiments below.

Product
Discovery Strategy Roadmapping Prioritization GTM Eval frameworks A/B testing KPI trees Telemetry
AI & Agents
LLMs (Claude, OpenAI, Gemini) Agent design Harnesses Tool calling Skill hierarchies Context/memory HITL & guardrails RAG Evals MCP
AI Foundations
Post-training (SFT, RLHF, DPO) Reasoning models Transformer internals
Data & Tools
Claude Code Codex SQL Python Mixpanel PostHog Linear Figma n8n Cursor Braintrust Langfuse

Where I've shipped.

Founding Product Manager · Supanote.ai

Bengaluru, India

Jan 2026 — Present
  • Lifted PLG paid conversion 5% in 2 months on the AI clinical scribe through funnel analysis, onboarding iteration, and reliability improvements — running PLG and enterprise B2B in parallel.
  • Scaled the B2B benefits-verification agent to 2.2x ARR in 3 months post 0-to-1 launch by re-architecting rule-based workflows into an agentic, harness-based orchestration with parallel agents, skill hierarchies, tool calling, and context/memory loops.
  • Drove production incident rate from 3.5% to <1% in 2 weeks via architectural audits and a custom eval harness.
  • Built the founding product operating layer — analytics, agile cadence, and internal AI agents automating program and design ops — driving a 5x lift in product velocity.

Product Manager · Innovaccer

Noida, India

Jul 2022 — Dec 2025
  • Automated fax-based referral intake for specialty clinics with an AI agent, improving per-user operational efficiency 4x (40% faster TAT).
  • Scaled adoption of an automation platform 75% in 3 quarters by segmenting users, uncovering key pain points, and shipping bi-weekly experiments guided by KPIs.
  • Improved complex UI flows via user-journey analytics and A/B testing, lifting active engagement 35%.
  • Scaled automation execution capacity 2x through demand forecasting and rapid cross-functional delivery, maintaining <1% error rate under higher load.
  • Unified post-acquisition product integrations into a single UX, achieving 100% SLA adherence and <2% incident rate post-launch.
  • Built a contract-driven integration layer replacing one-off API/Kafka hooks, cutting rollout time by 67%.

Indian Institute of Technology (IIT) Dhanbad

B.Tech, Mechanical Engineering · CGPA 8.28

2018 — 2022