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Durlabh Daryani

AI ProductManager.

I turn fuzzy AI product ideas into researched, scoped, and testable MVPs.

Four product builds, six PM case studies, and clearly marked proof placeholders where public evidence is still being prepared.

About

I build AI-first product prototypes from discovery to launch-ready MVP: user interviews, JTBD framing, prioritization, PRDs, QA, and post-launch measurement plans.

My BA and QA background gives me the practical PM muscle: requirements clarity, acceptance criteria, stakeholder communication, bug triage, release validation, and translating fuzzy customer problems into buildable scope.

This portfolio is designed around proof. Where a public demo, PRD, or pilot artifact is not available yet, I show a clearly marked placeholder so the claim is visible without pretending the evidence is final.

Product Builds
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Case Studies
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Frameworks Practiced
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AI Experiments
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Featured Products

Product Builds

Researched, scoped, and prototyped from 0 to 1 — swipe to explore each build.

View all projects →
Deep Dives & Case Studies

Case Studies

Problem → Research → JTBD → PRD → Evidence → Lessons.

6 studies
Problem

Shoppers waste hours comparing products across marketplaces with inconsistent specs, reviews and pricing.

Research

12 user interviews across three shopping personas; competitive teardown of Amazon, Perplexity Shopping and Google Shopping.

JTBD

When I'm buying a considered product, I want a trusted advisor that asks the right questions, so I can decide confidently without opening 20 tabs.

PRD

Conversational search with clarifying follow-ups, memory of preferences, structured comparison and a recommendation with reasoning.

Career Trajectory

Greenfinch Global Consultancy

Business Analyst & QA Intern

Recent

Gathered requirements, wrote BRDs and PRDs, ran QA cycles and validated user flows alongside developers and clients.

  • ·Owned requirement clarity across sprints
  • ·Bug triage and regression coverage
  • ·Client discussions and acceptance criteria

Assert InfoTech

Business Analyst

Earlier

Stakeholder communication, workflow analysis and functional specifications across product discussions and testing support.

  • ·Requirement gathering and documentation
  • ·Feature validation and acceptance criteria
  • ·Process improvement across teams

Founder Track

Tapinfi

Digital Business Card SaaS
Founder

Built a SaaS platform enabling professionals to instantly share digital profiles using NFC-enabled smart cards.

Product VisionPricing StrategyGTM & GrowthRoadmap

Bharat Svarga

AI Tourism Platform
Founder

AI-powered travel platform focused on spiritual and heritage circuits in Rajasthan — starting with Jaipur–Pushkar–Ajmer — that pairs personalised itineraries with a curated network of local vendors (homestays, guides, transport). Onboarded ~25 pilot vendors in Jaipur before scaling into a second circuit.

Product DiscoveryBusiness ModelAI Itinerary EngineVendor Onboarding
Product Thinking

Notes on how I build, decide and ship

Essays on discovery, AI products, growth loops and decision-making.

9 essays
Read all essays→
Writing & Thoughts

Thoughts

4 posts
#AI

The best AI PMs I know spend 80% of their time on evals and 20% on prompts. Here's the loop I run every week…

Read Post →@durlabhdaryani
#Discovery

Customer discovery without a research team: 5 interviews, one spreadsheet, and the JTBD you actually ship against.

Read Post →@durlabhdaryani
#Playbook

How I ship an MVP in 6 weeks — the exact week-by-week breakdown for Kartify.

Read Post →@durlabhdaryani

Framework Library

The mental models I lean on to decide what to build, what to cut and what to test next.

Discovery
JTBD

Understand the underlying job customers hire your product to do — beyond features.

Applied in: kartify case study →

Working Style

How I Operate

Six non-negotiable habits that shape every product I touch — from the first discovery call to the post-launch cohort review.

Discovery before build

I talk to users before writing a line of spec.

Five interviews per week, a four-column quote-behaviour-workaround-emotion note doc, and a shared 'kill list' that keeps every stakeholder accountable to evidence over opinion.

PRDs as communication contracts

A PRD is not a document — it's a decision log.

I write one-page briefs: problem statement, JTBD, North Star, out-of-scope list, and acceptance criteria. Engineers and designers review it before a single wireframe exists.

Treat the MVP as an experiment

Every MVP has exactly one riskiest assumption.

I define the assumption, the kill metric, and the learning deadline before the first sprint. If the signal doesn't come by week 6, we pivot or kill — not drag on.

Three events before Amplitude

Track activation, core action, retention proxy. That's it.

Instrument what matters on day one, review cohort curves every Monday, and only buy tooling when manual analysis costs more than the tool. Most seed products hit that at month 9.

Ship, Measure, Repeat

Shipping is not the end state — measurement is.

Every release ships with a pre-registered metric and a 2-week check-in. If the number didn't move, that's the next sprint's bug — not a retrospective footnote.

Write the memo first

Decisions get a one-page memo, not a deck.

What I'd do today, what changes with a week of research, and what evidence would flip me. The act of writing usually resolves the ambiguity before anyone reads it.

These principles are grounded in real builds — see the Case Studies for where each one shows up in practice.

Social Proof

What People Say

Excerpts from colleagues, pilot partners, and collaborators. ⚠ Placeholder — replace with verified quotes before sharing broadly.

"Durlabh's ability to translate ambiguous product requirements into clear, testable acceptance criteria saved our sprint multiple times. He thinks like a PM but writes like a BA — rare combination."

SD
Senior Developer
Greenfinch Global Consultancy

"The CafeOS requirement spec was the clearest I've seen from someone who hadn't held the PM title yet. Stakeholder alignment was zero-drama. He'd read the room better than people twice his experience."

OL
Operations Lead
3-Cafe Pilot Partner

"He ran our JTBD workshops with real discipline — not the fluffy 'jobs-to-be-done' buzzword stuff, but genuine hypothesis framing followed by user interviews. The insights were actionable on day one."

CF
Co-Founder
AI Startup Cohort

"Durlabh joined mid-sprint and still wrote the tightest PRD I've reviewed in the last 12 months. One page, clear north star, explicit out-of-scope — no fluff, no feature sprawl."

EM
Engineering Manager
Edtech Engagement

"What impressed me most was the eval mindset. He wasn't just prompting the model — he built a test set, tracked regressions, and treated the AI as a product requirement, not a black box."

AP
AI Product Lead
Mentorship Session

"His feedback on our onboarding flow was sharper than the UX consultant we'd hired. He tied every suggestion directly back to a drop-off metric we could track. Extremely results-oriented."

PD
Product Designer
SaaS Collaboration

The Lab

AI experiments, prototypes and workflow tools I build for myself.

01
Experiment

Prompt Engineering

Structured prompt libraries, evals and prompt-as-spec workflows.

02
Experiment

AI Agents

Tool-using agents with planning, memory and reflection loops.

03
Experiment

Multi-Agent Systems

Coordinated agents for research, comparison and synthesis tasks.

04
Experiment

MCP

Model Context Protocol tooling to give assistants safe access to real systems.

05
Experiment

n8n Automation

Product-ops workflows: research, outreach, monitoring and triage.

06
Experiment

RAG + Vector DBs

Grounding LLMs in private knowledge with retrieval-quality evals.

Education & Certifications

Degree
Bachelor of Computer Applications (BCA)
Artificial Intelligence & Data Science · Vivekananda Global University, Jaipur
Certifications
Google Product ManagementAI Product ManagementScrum FoundationsAgile PractitionerPrompt EngineeringGenerative AIProduct AnalyticsUX Fundamentals