Naren Krishna
hi, i'm

Naren Krishna

AI-native Product Operations Lead. Ruthless Prioritizer. Team Player. First principles thinker.
TL;DR

I build systems that fix things. I bring structure to chaos. And drama.

About me

Product & Support Operations leader, 12+ years across Meta and EarnIn. I help organizations turn any growth idea into reality. I own the launch framework that aligns EPD, Marketing, Sales, Finance, and Support on goals, positioning, and metrics. I run the planning cadences and demo forums that keep the company in step, build voice-of-customer loops from GTM and Support back into the roadmap, and shape the PM operating system: planning, tracking, decisions, and the tools PMs live in. Where AI and agents can change how product work actually gets done, that's where I push hardest.

Stack: Hands-on with SQL (Databricks), Amplitude, Braze, Zendesk, Jira, BERT/NLP, n8n, and Claude.

Roles I shine in: Product Ops · AI PM · Customer Strategy · Deployment · Cloud Alliances
EarnIn
Meta
Apple
Deloitte
Microsoft
Ericsson

MBA, IIM Lucknow · CS, IIT Madras

Clients I've worked with
HPEArgoCargillTargetVerizon
Receipts

What I've delivered at work.

Selected outcomes across EarnIn, Meta, Apple, and Deloitte.

AI pipelines that ship
$990K
saved per year
Voice-of-customer streamlined with a BERT + KNN ticket classifier at EarnIn
Launch readiness at scale
12M+
users on the product I run
Shipped through a launch-readiness process I own end-to-end at EarnIn
Fast domain ramp, high throughput
100+
Meta launches in 2 years
Across Integrity and Commerce. Ramped each domain fast and kept the cadence
Mastery of A/B experimentation
+13%
registrations lift
Proactive Care framework at EarnIn (also +5% bank connections)
Efficiency gains I bring in
3 days → 3 hrs
VNF provisioning time
Whitebox network function automation, Deloitte engagement
0 → 1 work I'm proud of
0 → 1
Transactional comms on Braze
Set up at EarnIn across every channel: email, SMS, push, in-app
Weekend builds · shipped end-to-end with Claude Code

Projects

6 projects

pzle.day

pzle

Problem: AI is moving faster than most people can absorb. Abstracts feel intimidating, so daily engagement falls off and the field stays opaque.

What it is: A daily 4×4 grouping puzzle with AI-themed words. Solving reveals the hidden theme behind the 16 terms and recommends one paper to read. Daily AI literacy as a ritual. One Claude call per day, edge-cached for millions of plays at ~$1.50/month.

Next.js 15SupabaseClaude Sonnet 4.5Vercel CronISR + Edge caching
TypeScript

Paper Radar

paper-radar

Problem: 200+ ML papers drop on arXiv every day. Abstracts don't tell you which ones are actually being built on or gaining momentum.

What it is: Daily arXiv tracker that scores ML papers by real-world traction: GitHub repos building on each paper, citation velocity, and time-decayed shipping signals. Two-tier LLM pipeline: Haiku classifies 150 papers daily, Sonnet writes narratives for the top 10.

Next.js 16Supabase + pgvectorClaude Haiku + SonnetVoyage embeddingsarXiv / GitHub / Semantic Scholar
TypeScript
MVP · June 2, 2026

StackMap

stackmap

Problem: The AI ecosystem changes faster than any static market map. Most maps don't help you decide what to actually ship. They just list companies.

What it is: A living architecture explorer that maps companies as blocks across 12 layers, connected by typed wires, assembled dynamically around the solution someone is shipping. Stays alive via a five-agent pipeline (Scout, Classifier, Comparator, Synthesizer, Auditor), each with its own eval cohort.

Multi-agent systemAnthropic SDKEval-driven devTypeScriptSVG rendering
Progress90%
TypeScript
MVP · June 10, 2026

Digital Twin

digital-twin

Problem: Your knowledge (resume, docs, history, links) lives in 20 silos. Other people can't reach the useful parts, and you can't even chat with your own context.

What it is: An AI alter-ego platform. Upload your resume, docs, and links to build a private knowledge base, then chat with an agent that represents you. Includes PII detection, per-user RLS, and an MCP server so other agents can talk to your twin.

Next.js 16Anthropic SDK + AI SDK v6MCP serverSupabase Auth + RLSpdf-parse
Progress75%
TypeScript
MVP · June 30, 2026

NYBF: Not Your Best Friend

nybf

Problem: Companion chat products are easy to ship as toys but break under real use. They drift out of persona, miss context, or get flagged by safety. Manual QA can't keep up.

What it is: A companion chat product with multiple personas (Partner, Big Sibling, Friend). The interesting half is the autonomous eval loop: simulated user agents stress-test the app, a product-head agent triages findings, a dev agent writes code diffs, a QA agent re-simulates to validate, all in one command.

Next.js 16Supabase AuthMulti-agent eval loopAnthropic ClaudePWA
Progress55%
TypeScript

Social Media Content Generation Pipeline

social-media-pipeline

Problem: Daily social posting is the kind of work that kills momentum. Most automation pipelines stop at generation. A human still has to hit publish, every day.

What it is: Fully autonomous daily social-content pipeline. A scheduled n8n trigger kicks off a Mastra workflow that generates copy with Claude, synthesizes images and videos in Python, then publishes via the Publer API. Zero human touch per post. Runs on a private host, not a Next.js app.

Mastran8nClaude HaikuPython (image + video synthesis)Publer API
Python
How I work

The loop I run

01

I find signal others miss.

Patterns in data, conversations, and systems that other people walk past. The unnamed thing is usually where the leverage is.

02

I build the system that acts on it.

Not a deck. The actual pipeline, classifier, workflow, or metric framework that turns the insight into a behavior change.

03

I make sure it lands.

Adoption is designed in, not bolted on at launch. Every team that has to live with the system actually uses it.

When the path is unclear

I run on a Rumsfeld matrix, known unknowns versus unknown unknowns. Three steps that survive every project:

  1. 01
    Map what you know and don't know.
    Knowns, known unknowns, and the blindspots. Write them down before deciding anything.
  2. 02
    Bias toward cheap experiments.
    Test with a small cohort before any full rollout. Cheap is the point.
  3. 03
    Measure as you go.
    Validate assumptions weekly, not at the end. Most plans are wrong by week 2.
Off the keyboard
💃
I dance.

Choreography, freestyle, and the occasional reel that goes harder than it should.

@narenkris
✈️
I'm a student pilot.

Training is currently paused, but the logbook is open. Single-engine, VFR.

🛠️
I prototype with Claude Code.

Most weekend builds below get from idea to shipped in 1-2 sittings. The compression is real.

Books on my shelf

What I've read, what I'm flipping through now, and what's queued up next.

Read
The Secret
Rhonda Byrne

My take: The belief that focused, emotionally charged thought attracts matching outcomes. The Law of Attraction as a self-reinforcing loop of expectation, gratitude, and visualization.

Read
The Art of War
Sun Tzu

My take: A timeless playbook for winning conflicts through positioning, deception, and economy of force. The conviction that the supreme victory is the one won before the battle begins.

Flipping pages
Screenplay
Syd Field

My take: To learn how three-act structure shapes pitches, decks, and product narratives.

Up next
The Almanack of Naval Ravikant
Eric Jorgenson

My take: Wealth, happiness, and freedom compound the same way: through specific knowledge, leverage, and the patience to play long games with the right people.

Up next
Meditations
Marcus Aurelius

My take: You don't control what happens to you, only your judgment of it, and that single distinction is the source of every freedom worth having.

Up next
Man's Search for Meaning
Viktor Frankl

My take: When everything can be taken from you, one thing remains: the freedom to choose your response, and in that choice lies the meaning of a life.