moonbatant

4+ years building AI‑native products

Mamoon Mondal

AI Product Manager

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.

See selected work Résumé
  1. 01 Supanote.ai 5x Product velocity lift
  2. 02 Innovaccer 4x Per-user operational efficiency
  3. 03 Supanote.ai +5% Trial-to-paid conversion (2 mo)
  4. 04 Supanote.ai 2.2x ARR in 3 months

02 Selected work

Products & agents I've shipped.

  1. 01
    Supanote.ai 2026

    Building a 5x PM agent on Claude Code

    An always-on autonomous PM agent: one Slack message in, a PRD, a mockup, and a Linear ticket out — built on Claude Code + MCP with parallel research sub-agents and full observability.
    5x Product velocity lift 1 Slack msg → PRD, mockup & Linear ticket Minutes Insight → reviewable artifact (was hours)
  2. 02
    Innovaccer 2022–2025

    Automating fax-based referral intake with an AI agent

    Specialty clinics still run referrals over fax. An AI intake agent cut turnaround 40% and 4x'd per-user operational efficiency.
    4x Per-user operational efficiency 40% Faster turnaround time
  3. 03
    Supanote.ai 2026 · ~2 months

    Rebuilding Supanote's PLG activation path

    Signup→subscription sat flat at ~12% for months. I reframed the quarter around conversion, found the real leak — setup, not the demo note — and lifted trial-to-paid +5% in two months.
    +5% Trial-to-paid conversion (2 mo) 5 in 7 Activation metric (notes / days) 3.5% → <1% Incident rate, cut in parallel
  4. 04
    Supanote.ai 2026 · 3 months post-launch

    Re-architecting benefits verification into an agentic system

    Took a brittle rule-based enterprise workflow to a harness-based agent orchestration — 2.2x ARR in 3 months, with eval-gated reliability for an enterprise bar.
    2.2x ARR in 3 months 0 → 1 Launched the product line Eval-gated Regressions caught pre-production

04 of 10 All work

03 About

About

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.

Skills

Product
DiscoveryStrategyRoadmappingPrioritizationGTMEval frameworksA/B testingKPI treesTelemetry
AI & Agents
LLMs (Claude, OpenAI, Gemini)Agent designHarnessesTool callingSkill hierarchiesContext/memoryHITL & guardrailsRAGEvalsMCP
AI Foundations
Post-training (SFT, RLHF, DPO)Reasoning modelsTransformer internals
Data & Tools
Claude CodeCodexSQLPythonMixpanelPostHogLinearFigman8nCursorBraintrustLangfuse

04 Experience

Where I've shipped.

Supanote.ai

Founding Product Manager

Jan 2026 — Present Bengaluru, India
  • 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.

Innovaccer

Product Manager

Jul 2022 — Dec 2025 Noida, India
  • 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%.

05 Education

Indian Institute of Technology (IIT) Dhanbad

B.Tech, Mechanical Engineering · CGPA 8.28

2018 — 2022

06 Writing

Essays & write-ups

07 · Contact

Let's build something reliable.

Bengaluru, India · +91 7022382627

sheikh.mamoon.mondal@gmail.com
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