STAFF PM · AI PRODUCT BUILDER

Hi, I'm Vik —
a product manager who builds.

For ~12 years I've shipped consumer products at scale — at Zillow, Wayfair, Ahold Delhaize, and Whirlpool. Today I build AI-native products end-to-end: the app, the AI pipeline, the data model, and the evals.

Selected work

How I Learn AI My open knowledge center: interactive maps and mental models for capturing, organizing and retaining what I learn. Open it ↗

Experience

Trustly
Lets people pay straight from their bank account, no card needed.
Staff PM, AI Product Builder2026 — PRESENT · NEW YORK
+$3.0B
Annual TPV sized for Trustly Black, a 0→1 loyalty program
+5.5%
Initiate-to-capture rate across the Pay by Bank funnel (2026)
200
Closed-beta users for the GoConsumer AI coaching app
  • Built GoConsumer 0→1, an iOS AI financial-coaching app on Claude LLMs with eval-gated releases, and launched a closed beta; shipped frontend code to production with Claude Code.
  • Built the business case and secured leadership approval for Trustly Black, a 0→1 loyalty program for high-value gaming users, also sized at +$32M net revenue.
  • Ran A/B and A/B/C experiments across the Pay by Bank funnel; as Trustly Product's AI champion, designed and built Product Cockpit, an internal product OS integrated with GitHub, Jira, Confluence, Figma, and Linear via MCP.
Zillow
Helps people find, tour and buy homes.
Product Lead, Core Shopping2024 — 2026 · NEW YORK
+23%
Compare engagement on the search listing page
+12%
Tour-success rate with touring agreements on mobile
+2.2%
Twice-weekly retention from Collections
  • DRI for multiplayer / collaborative experiences across Zillow Shopping — defined the vision, strategy, and roadmap for Zillow's first collaborative features (0→1), grounded in research on Real Estate IDX presented to senior leadership.
  • Launched Collections across iOS, Android, and Web — invite, share, compare, and collaborate on saved homes; shipped Compare on the search listing page (A/B), which also lifted tour submits +2.8% and added ~$3.5M/yr incremental revenue.
  • Launched touring agreements on mobile (A/B); delivered dynamic scrolling on Saved Homes for +2.42% submits and +$3M/yr revenue.
Wayfair
Online store for furniture, decor and home goods.
Product Lead, Middle & Lower Funnel2022 — 2024 · CHICAGO
+$63.9M
GMV a year from funnel experiments
−$2.8M
Customer-contact cost a year
+$24.9M
GMV a year from reviews and return policy on the PDP
  • Global product lead managing 2 PMs across Browse, PDP, Cart, Checkout, and Receipt — owned the vision and roadmap.
  • Launched customer reviews and return policy on the PDP (A/B) — +2.62% / +0.59% CVR.
  • Shipped an order-status / explore-more home surface with upsell + cross-sell (+$30M GMV/yr) and address auto-complete & validation, each cutting contact costs by $2.7M/yr.
Ahold Delhaize
Grocery group behind Giant, Martin's and Stop & Shop.
Sr. Product Manager, Mobile Apps2020 — 2022 · CHICAGO
20 → 700+
Stores running Click & Collect, pilot to scale
+10%
Click & Collect 2.0 opt-in
3.2 → 2.5 min
Curbside wait time, down from 3.2
  • Led end-to-end discovery and delivery of Click & Collect curbside pickup across Giant, Martin's, and Stop & Shop, from a store pilot to a wide rollout.
  • Spearheaded Click & Collect 2.0 across research, design, engineering, ops, and marketing — lifting check-in +13% and cutting curbside wait times.
  • Led the native mobile-app transformation across ADUSA brands; owned executive updates for four mobile squads.
Whirlpool
Maker of home appliances: Whirlpool, KitchenAid, JennAir and Maytag.
Product Manager (Global Leadership Program)2015 — 2020 · MICHIGAN
2.0 → 4.2
JennAir app-store rating, up from 2.0
2.9 → 4.3
B2B portal CSAT, up from 2.9
−16%
Call-center touchpoints
  • Led the end-to-end transformation of the JennAir connected app, improving its app-store ratings; managed an Associate PM on the KitchenAid app transformation.
  • Owned cart & checkout for whirlpool.com and maytag.com (US & Canada).
  • Led a B2B portal transformation that lifted customer satisfaction and cut call-center load.

Earlier · Bangalore, 2009–2013. Senior Associate at Burson-Marsteller (PR for Flipkart, a Walmart company) and Systems Engineer at Tata Consultancy Services (Bank of America).

Education
MBA · Strategy & Marketing
Purdue University — Krannert School of Management
B.E. · Industrial Engineering & Management
BMS College of Engineering, Bangalore

Highlights & achievements

🏆 Awards

Golden Lever Award — CIO (Whirlpool) Customer 1st Mindset — President (Whirlpool)

🤖 AI learning

Agentic AI Crash Course '25 AI Evals Crash Course '25 AI Bootcamp '24 Reforge — Growth & Retention

🛠️ AI tools

Claude Code CLI Replit Cursor Figma Make n8n Databricks AI NotebookLM GitHub GitHub Pages

📜 Certifications

AWS Cloud Practitioner Intro to Generative AI SQL Basics Tableau 10 A–Z

🏃 Beyond work

Chicago Marathon 2024

How I run product

↻ data flywheel AI PM OPERATING LOOP 1Listen 2FrameTide’s one question:what’s safe to spend? 3DesignTrustly Black:0→1 loyalty program 4ShipEval-gated releasesClaude Code to production 5MeasureA/B on every launch:+23% Compare, Zillow 6LearnSurprises become testsin nightly evals EXPLICIT · what users say IDX research · 200-user beta IMPLICIT · what users do A/B tests · Coach traces · evals
  1. Listen IDX research, the 200-user beta, A/B tests, Coach traces and evals
  2. Frame Tide’s one question: what’s safe to spend?
  3. Design Trustly Black, a 0→1 loyalty program
  4. Ship Eval-gated releases, Claude Code to production
  5. Measure A/B on every launch: +23% Compare at Zillow
  6. Learn Surprises become tests in nightly evals
Customer & business outcomes
🧭

Customer Discovery & Obsession

Start with the customer and work backwards. Continuous discovery — interviews plus real behavior — over a spec written once and frozen.

🎯

Outcomes Over Output

Roadmaps anchored to a North Star and business impact — activation, retention, conversion — not a feature checklist.

AI-native craft
🤖

AI Engineering & Agents

Claude & AWS Bedrock pipelines, agent tooling, prompt and structured-output design — turned into features users actually feel.

📐

AI Evals

Dimensions, fixtures, ground-truth, judge scoring. Evals are the new success metric — AI quality you can actually move.

🌀

The Data Flywheel

Every interaction is a signal. Corrections and usage feed back so the model gets sharper the more the product is used.

Git by the numbers

A pace of about 5.0 contributions a day since January 1, with about 6 in 10 commits co-authored with AI.

Week of 2026-03-16: 19 commitsWeek of 2026-03-23: 81 commitsWeek of 2026-03-30: 91 commitsWeek of 2026-04-06: 1 commitsWeek of 2026-04-13: 81 commitsWeek of 2026-04-20: 35 commitsWeek of 2026-04-27: 1 commitsWeek of 2026-05-04: 1 commitsWeek of 2026-05-11: 1 commitsWeek of 2026-05-18: 1 commitsWeek of 2026-05-25: 82 commitsWeek of 2026-06-01: 112 commitsWeek of 2026-06-08: 137 commitsWeek of 2026-06-15: 17 commitsWeek of 2026-06-22: 14 commitsWeek of 2026-06-29: 14 commitsWeek of 2026-07-06: 14 commitsWeek of 2026-07-13: 14 commitsWeek of 2026-07-20: 14 commitsWeek of 2026-07-27: 14 commitsWeek of 2026-08-03: 14 commitsWeek of 2026-08-10: 14 commitsWeek of 2026-08-17: 14 commitsWeek of 2026-08-24: 14 commitsWeek of 2026-08-31: 14 commitsWeek of 2026-09-07: 14 commitsWeek of 2026-09-14: 57 commitsWeek of 2026-09-21: 75 commitsWeek of 2026-09-28: 29 commitsWeek of 2026-10-05: 33 commitsWeek of 2026-10-12: 14 commitsWeek of 2026-10-19: 16 commitsWeek of 2026-10-26: 7 commits2026-03-162026-10-26 (this week)busiest week: 137
Commits per week. Last 30 days: 95 commits, against 164 in the 30 days before.
1,507
GitHub contributions
commits, PRs & reviews · public + private · 2026 to date
62%
AI-built commits
I build with AI, and keep the receipts
181
eval fixtures
AI quality measured, not guessed
390
changes shipped via PR
reviewed — never straight to main
11
automated guardrails
hooks that enforce my own discipline
the stack
what I actually build with, across every repo
TypeScript 43.4%JSON 21.2%Markdown 20.8%HTML 11.1%Shell 2.1%YAML 1.5%
All the numbers (10 more)
1,059
commits shipped
across 5 repos · 2026 to date
4.8
commits a day
steady, iterative cadence
90%
Conventional Commits
structured, readable history
11
custom AI tools
skills & commands I built to extend my own workflow
108
knowledge atoms
notes + concepts wired into one map
545
lessons captured
institutional memory, written as I go
115
documented changes
every ship explained in plain English
310
docs & diagrams
documentation as a living spec
1,094
files under version control
full-stack breadth
5
active projects
public + private

Counted from git history across 5 repos, public and private, 2026-03-21 → 2026-10-29. File and tooling counts are a current snapshot. No private code or content. See the work →

Get in touch

I'm open to AI product roles where product and engineering sit close together. If that sounds like something you're working on, I'd be glad to chat.