Open to Opportunities

Harshit Sharma

AI Product Manager

Product manager building at the frontier. I ship real products, work across the AI stack, and think obsessively about evals, reliability, and what makes AI systems trustworthy.

Selected Work, 6 Projects

Eval Studio

Which prompt, which model, at what cost?

Live ProductEvalsAI ToolsDeveloper Tools

The Problem

AI teams pick prompts and models using spreadsheets, gut feel, or generic benchmarks that have nothing to do with their actual product.

The Solution

Browser-based LLM eval tool. Test prompts and models on your own data with multi-model judge council, cost tracking, and ranked results.

3 Providers2-Judge CouncilPer-row Cost TrackingLive

claude-code-bridge

Context compounds. It never resets.

Live ProductDeveloper ToolsAI Tools

The Problem

Every time you switch from Claude to Cursor, context is lost. You re-explain decisions, repeat constraints, and rebuild mental state from scratch.

The Solution

A local MCP server that auto-syncs strategy decisions from Claude to your project files. When you open Cursor, Claude Code already knows where things stand.

ShippedContext EngineeringUsed Daily

Explainable AI Coding Assistant

Trust Through Transparency

Case StudyDeveloper ToolsAI Tools

The Problem

Developers waste hours verifying AI suggestions because tools optimize for speed, not trust, creating a “trust tax” that blocks adoption.

The Solution

Calibrated confidence scores + explainable reasoning. Show developers WHY a suggestion works and WHEN to be skeptical.

Market researchFigma prototypePDF case study

Job Market Pulse

The labor market, visualized

Live ProductAnalytics

The Problem

Job market data is scattered across government sites, ugly portals, and paywalled reports. Nobody has a clean, real-time view of what is actually happening.

The Solution

A real-time dashboard pulling from FRED API, DOL, and USCIS. Labor market trends, H-1B sponsor rankings, PM salary ranges, and approval rates in one view.

Live4 Data SourcesReal-time FRED API

Dear Her

Some feelings are too big for a text message

Live ProductAI Tools

The Problem

Most people feel things deeply about the women in their lives but never find the words to say it. The gap is not feeling. It is articulation.

The Solution

Write three honest prompts about her. Claude transforms them into a beautiful animated letter she can open from any link, no login required.

Shipped in 3 Hours59% Conversion10 CountriesZero Paid Distribution

PM Salary Ace

Practice Like the Job Depends On It

Live ProductAI Tools

The Problem

PM candidates don't know what skill level they're actually at. Generic prep doesn't map to real compensation gaps.

The Solution

336 questions across 5 salary tiers. Practice what a $350K Staff+ PM actually needs, not generic frameworks.

Shipped in 3 Hours336 Questions49% Activation Rate

Background

Building AI Products That Scale Reliably

I started in electrical engineering, designing power systems where failure meant explosions, not just bad user reviews. That taught me to think through failure modes obsessively because in safety-critical systems, “it works in the demo” isn’t good enough.

For five years I shipped products at scale: complex enterprise software, data platforms, and revenue tooling that supported a $150M+ sales pipeline. I learned how to work with large cross-functional teams, drive adoption across organizations, and own outcomes end to end.

At Berkeley (M. Eng.), I’ve sharpened both edges: technical depth in ML, deep learning, and RL, combined with hands-on AI evals productization. I build products daily, not just study them.

I’m a daily AI power user: I code with Claude, build agents for automation, and live in the products I want to help build.

My focus: bridging the gap between AI capability and reliable deployment at scale because the companies that win won’t just have the most capable models, they’ll have the most trustworthy ones.

WHERE I STARTED

Non-traditional: safety-critical systems to enterprise SaaS. I’ve worked where failure = lawsuits and casualties, not just bugs.

WHERE I AM

Berkeley MEng. Deep in ML/RL/AI evals. Daily power user across frontier models. Building real products, shipping them, iterating.

WHERE I’M GOING

Making AI systems reliable enough to trust in production. Where models are powerful but reliability is everything. Hard problems, high stakes.

Connect

Let's Connect!

Interested in AI product strategy? Building something cool? Just want to chat about agents and reliability? I'm easy to reach.

Currently: Getting back into chess, dominating the table tennis table, and planning my next trip to Japan.

If it's easier, pick a time directly

Quick intro call · 15 min · we can go over if we're on a roll :)