- Enterprise SaaS and 0→1 / 1→N product work
- AI agents, AI evaluation and GenAI product systems
- RAG, LLM workflows and human-in-the-loop design
- International product delivery across distributed teams
Product Partner + AI Product Managerturning ambiguous, complex product problems into shippable systemsand measurable product outcomes.
Welcome!
I’m Sriharika Nallagorla
Product Partner · Experience Designer · AI Systems Strategist · Technology Enabler
I bring afresh product perspectiveto complex problems —helping businesses build whatcustomers actually value.
01 / ABOUTPRODUCT THINKING · AI SYSTEMS · OWNERSHIP
I like taking a messy product problemand giving it structure —from the first question to thedecision, build, launch and next iteration.
I work across discovery, product strategy, experience design, AI systems and delivery. I like complex problems where user needs, business outcomes and technology have to meet.
My work spans enterprise SaaS, AI agents and evaluation, RAG and LLM product systems, GenAI, travel, mobility, commerce and consumer products across international teams.
- MBA — Indian Institute of Management Kozhikode · QS #78 Business & Management Studies (2026)
- Focus: Product Management · Product Strategy · Marketing · Supply Chain
- International Certificate in Product Management ↗
- AI Product Management — certificate due from the institute
- International Business Certification ↗
- Figma · Miro · Jira · Confluence
- SQL · Power BI · Mixpanel · Amplitude · Hotjar
- Supabase · n8n · React · Vite
- AI systems: agents · evals · RAG · LLM product design
THE RIKA FOCUSSCROLL-DRIVEN PRODUCT LOOP
Product work is a lens. The clearer the focus, the better the decision.
The lens moves. The goal stays the same: solve the right problem and keep improving.
02 / HOW I HELPSTART WITH THE PRODUCT PROBLEM, NOT THE JOB TITLE
Start with the product problem, not the job title.
I can join where the product needs the most clarity — from discovery to learning.
Discovery, ideation, build, launch or learning: the scope changes with where the product is today.
Discover the opportunity
Find the customer problem worth solving and turn research into a testable direction.
Define the product
Clarify the job, outcome, proposition, priorities and trade-offs before building.
Build & validate
Turn decisions into flows, prototypes, requirements and systems that can be tested.
Launch & commercialise
Connect positioning, pricing, GTM and launch choices to measurable product outcomes.
Improve adoption & retention
Understand activation, friction, habits and drop-off; design experiments around behavior.
Learn from data & evolve
Use product data, feedback and system performance to decide what changes next.
03 / EXPERTISEPROBLEM → APPROACH → PROOF
Start with the product problem,not the job title.
Tell me where the product is stuck. The capabilities come after that.
WHAT KIND OF PRODUCT PROBLEM ARE YOU SOLVING?
WHY DO YOU NEED ME?
From thinking with you to improving what is already live.
Think with me
Discovery, research, framing, opportunity and product strategy.
Share with me
Journey, UX, roadmap, prioritisation, PRDs and metrics.
Build it with the team
Architecture, AI flows, APIs, evals and engineering handoff.
Launch & improve it
GTM, experiments, adoption, analytics, economics and iteration.
CAPABILITIES ACROSS THE WORK
Product
Discovery · Strategy · Roadmaps · PRDs · Prioritisation · Experiments
AI
Agents · RAG · Evals · HITL · AI UX · Guardrails · Model/tool decisions
Data
Metrics · Analytics · Event design · Data models · Decision systems
Business
GTM · Adoption · Retention · Pricing hypotheses · Economics · Market entry
Delivery
APIs · Architecture · Stakeholder alignment · UAT · Rollout · Governance
“Consistency transforms average into excellence.
Consistency is my superpower.”
04 / PROOF OF WORK9 PROJECTS · DECISIONS, SYSTEMS, EVALS & WORKING PRODUCT JOURNEYS
Don’t just take my word for it.
See the decisions behind the products.
Nine projects, numbered 01–09. Each opens into a complete Product Decision Record: problem, users, decisions, PRD, architecture, AI/evaluation logic, product journey, GTM and inspectable evidence.
HOW TO READ THE EVIDENCE
FOUNDER / ENTERPRISE START HERE
Aperture AI
Secondary research = market / system context. Prototype-tested = behavior exercised in a prototype. Synthetic eval = designed technical test. Hypothesis = still needs primary validation.
AI estate → ownership → spend → quality → risk → Outcome Contracts → scale / fix / stop.
Inspect the enterprise AI product case ↗THE 60-SECOND VIEWCHOOSE THE JOURNEY THAT MATCHES WHY YOU’RE HERE
Product Partnership
You have an idea, product or product problem and want a product partner who can bring structure, curiosity and execution.
Recruitment
You’re considering me for a product role and want the fastest route through experience, expertise, proof of work and my own resume.
05 / DEEP THOUGHTSPRODUCT · AI · BEHAVIOR · SYSTEMS
Products are full of decisions
that rarely appear on the screen.
Six product questions explained simply first — with the research, reasoning and deeper analysis one click away.
AI & AUTONOMY
A confidence score is not an autonomy policy
A model can sound very sure and still be handling a decision that should not be automatic. This thought is about separating confidence from permission to act.
Read the thought ↗SYSTEMS & SCALEUsage is not ROI
High AI usage does not automatically mean business value. This thought asks what changed for the customer, the workflow or the economics.
Read the thought ↗BEHAVIOR & DECISIONSA recommendation system is not successful because someone clicked
A click only proves attention for a moment. This thought looks at whether the recommendation actually helped someone make a satisfying choice.
Read the thought ↗AI QUALITYRAG can fail before the LLM even starts answering
Sometimes the wrong answer begins before generation: the system never found the right evidence. This thought separates retrieval failure from model failure.
Read the thought ↗ATTENTION & DISCOVERYThe best discovery product may help you ignore more
When information is endless, the useful product may be the one that helps you decide what is not worth your attention.
Read the thought ↗PRODUCT QUESTIONSNavigation is not the same as deciding when to leave
Maps can calculate routes. This thought explores the adjacent recurring decision: when should someone leave to arrive the way they want?
Read the thought ↗What should I think about next?
Suggest a product question, AI topic or industry tension. This opens an email draft to me; nothing is sent automatically.
A PRODUCT PROBLEM IS A GOOD PLACE TO START.
Tell me what you’re trying to make better.
This does not commit you to hiring me. I am naturally curious about product problems and happy to decode an idea, brainstorm over coffee, or explore whether working together makes sense.
Curious to hear what you’re building. Looking forward to the conversation.