Production-grade AI engineering experience for final-year students and recent graduates — proof of work an interviewer can actually inspect, not another certificate.
Hiring has shifted decisively toward proof of work: what you built, what problem it solved, and what changed as a result. Companies are deploying agentic AI faster than they can find engineers who have ever worked on one. Graduates arrive with strong theory and no production exposure. That gap is precisely what this programme closes.
EpicureAI Labs is a Bengaluru-based, DPIIT-recognised AI product company. You train on the architecture, constraints and trade-offs of products we are actually shipping — guided by the team that builds them, on the stack the industry uses.
Every module taught across ten products in active development.
Eight of ten drawn from Y Combinator's Requests for Startups.
Senior leaders bring you their real problems. You choose one.
Products built toward venture stage — you work at founder altitude.
A conventional course teaches retrieval-augmented generation once, with one example. You will see it across ten products — where the retrieval strategy changes, where the cost of a wrong answer changes, and where the right trade-off flips entirely. Understanding that transfers. A single worked example does not.
Worked example — grounding & retrieval · one technique, ten contexts
A wrong answer is a safety event. Grounding is mandatory; refusal beats a guess.
A wrong answer erodes trust. Provenance and citation matter more than fluency.
A wrong answer carries regulatory weight. The system must never advise, only inform.
A wrong answer teaches the wrong thing. Correctness must survive personalisation.
Anchored to one product — where you write code, own scope, and ship.
Structured contrast across the other products — how would this decision differ, and why?
Your capstone runs as a spine — accumulating a prototype, PRD, business model and governance review.
Why this is hard to replicate: a training company cannot manufacture ten in-production AI products. A product company will not open ten codebases to learners. This programme exists because EpicureAI is both.
Normally students pitch to industry. Here it runs the other way. Senior leaders present the real, unsolved problems on their desks — with context, constraints and what a good answer would be worth. Teams question them directly, then choose which problem to carry as their capstone.
Eight of the ten problem statements are drawn from Y Combinator's published Requests for Startups — problem areas the world's most prominent accelerator has publicly stated it wants solved. The remaining two are EpicureAI's own products in active development.
You aren't building against a problem invented for a syllabus. You're building against demand independently articulated by the market.
Three live sessions per week, two hours each — roughly seventy-eight contact hours plus guided project work. Every session is live and interactive; none are pre-recorded.
Weeks 1–6 · Foundation and build
PRDs, user journeys, personas, KPIs and prioritisation — built on ISB Product Management frameworks, applied to live product decisions.
Deliverable · PRD draft & KPI planProblem validation, business model design, unit economics and startup finance — on frameworks from Stanford's Launching Your Startup. Finance led by a practising Chartered Accountant.
Deliverable · Validated business model canvasIndustry leaders present real, unsolved problems from their organisations. Teams interrogate the brief, assess feasibility, and lock their capstone direction.
Deliverable · Capstone selected · team · positioningVersion control and collaborative workflow on a real repository; environment setup on the production stack; how features are actually conceived, prioritised and shipped.
Deliverable · Dev environment & first merged PRModel APIs in production, structured output enforcement, response validation, and prompt design treated as an engineering discipline rather than a craft.
Deliverable · Working LLM-powered mini-appAgent roles and coordination; parallel versus sequential architectures; latency budgeting; handoff design and failure containment across agents.
Deliverable · Working multi-agent prototypeWeeks 7–13 · Build, ship, incorporate
Retrieval strategies, grounding outputs in verified sources, hallucination measurement, and evaluating retrieval quality — contrasted across four very different risk profiles.
Deliverable · RAG prototype with measured groundingData modelling for real products, pipelines, cloud services, and the analytics instrumentation that makes outcomes measurable.
Deliverable · Data layer wired into the capstoneTesting and code-review discipline, secure coding, India's DPDP requirements, and AI-specific risk — hallucination control, output validation and evaluation method.
Deliverable · Tested feature & AI-governance checklistA two-week ship cycle on the chosen problem, with 1:1 mentorship and code review from the EpicureAI senior engineering team.
Deliverable · Shipped capstone feature & portfolioIncorporation mechanics, entity structure, cap table fundamentals, the fundraising process, and pitch construction with live practice.
Deliverable · Pitch deck & incorporation readinessResume building, mock interviews, profile optimisation and a personalised market roadmap — culminating in the Capstone Showcase before a judging panel.
Deliverable · Final integrated portfolioDesign multi-agent systems with distinct roles, coordinated into one product, with a safety layer governing output.
Treat prompts as engineering artifacts, integrate model APIs, enforce structured outputs, and ground responses in verified data.
Constraint enforcement, contraindication logic, output validation and hallucination control — the most in-demand applied AI skill.
Contribute to real codebases across modern front ends and API-driven back ends, with version control and code-review discipline.
Model product data, work with document stores and analytics warehouses, and build the pipelines behind outcome tracking.
Write an employer-grade PRD, map user journeys, define KPIs, and prioritise using structured frameworks.
Validate a problem, design a business model, understand startup finance, construct a pitch, and grasp what incorporation involves.
Apply privacy-by-design and DPDP requirements; produce an AI-governance checklist and risk assessment for your capstone.
Issued on successful completion — formal recognition of supervised engineering work on in-production AI systems, backed by the capstone portfolio that evidences it. The combination is what carries weight: a certificate alone proves attendance; a certificate plus inspectable work proves capability.
In-kind, guided incubation for the standout capstone team.
Engineering time plus cloud and AI-tooling access.
Entity structure, registration and startup compliance guidance.
Working sessions across product, engineering and go-to-market.
Introductions within our network, with pitch preparation.
Support is in kind, valued up to ₹2,00,000, awarded to the standout team in the cohort at EpicureAI's sole discretion. EpicureAI may split the award or make no award if no capstone meets the bar. Detailed terms are shared at enrolment.
We would rather you decide against joining than join on a misunderstanding. Everything below is stated plainly, and forms part of the terms shared at enrolment.
Strong performers may be considered for a number of paid internship opportunities at EpicureAI Labs or associated ventures, based on individual capstone evaluation. Offers are competitive and subject to business need.
Where capstone work is developed further, any commercial arrangement is agreed separately in writing. Enrolment confers no equity, founding role or claim over EpicureAI Labs or its products.
Admissions run on a rolling basis and close once the cohort is full. Cohorts are deliberately capped to protect the quality of live, mentored learning.
Submit the application form with your background, current year of study and what you want to build.
Applications are reviewed by the EpicureAI team for fit and readiness.
Selected candidates receive an offer and confirm their seat.
Complete the application form below. If the form does not load, write to founder@epicureailabs.com and we will send you a direct link.
epicureailabs.com · Bengaluru, India
References to Stanford (Launching Your Startup) and ISB (Product Management) indicate frameworks from programmes pursued by the EpicureAI founding team and adapted for this cohort. This programme is offered independently by EpicureAI Labs and is not affiliated with, endorsed by, or sponsored by Stanford University or the Indian School of Business. References to Y Combinator's Requests for Startups indicate publicly published problem areas used as source material; EpicureAI Labs is not affiliated with, endorsed by, or sponsored by Y Combinator. Guest participation in the reverse pitch is subject to confirmation and availability. Fees are exclusive of GST. Full terms, privacy and refund policies are available at Terms, Privacy and Refund Policy.