Systems ship. Demos don't.
8 weeks to go from building agents to reasoning like a senior AI engineer. 48 hours live. You walk out with a production-grade Enterprise Agentic RAG mid-program build, a deployed capstone, and the architecture instincts that separate engineers who own systems from engineers who assemble them.
Enroll Now — $549✓ Live sessions Saturdays & Sundays · 8:00 AM – 11:00 AM IST · Cohort 5 · Starting May 24
3 minutes from Nachiketh on what this program is, who it's for, and why it works.
The gap between building a demo and owning production isn't skill — it's architecture thinking.
Jupyter notebooks that break at scale. Tutorials that stop at "hello world". No understanding of what happens when real users hit your agent at 3 AM.
Latency spikes, runaway token costs, hallucinations in production — without the right observability and guardrails, you can't debug what you can't see.
Everyone can follow a tutorial. Senior engineers know why one design outperforms another under real constraints — and can articulate those tradeoffs clearly to the people around them.
We go from foundations to production deployment in a logical, compounding progression.
From LLM fundamentals and prompt engineering to building your first agents and memory-backed systems. Every concept taught through a working build.
LangGraph multi-agent orchestration, async task queues, FastAPI deployment, Docker containerization, cloud hosting, and observability that catches failures before users do.
Running throughout both phases — new in Cohort 5 — Advanced System Architect Modules that teach you to reason about design decisions the way senior engineers do. Not what to build. How to think about what to build, and why one approach holds under real constraints while another breaks.
Advanced System Architect Modules for Trade-Off Discussions. Production code is table stakes. What distinguishes senior engineers is how they reason through design decisions under real constraints — and communicate those decisions clearly to the people around them. This module teaches that reasoning explicitly.
How to evaluate latency vs cost vs accuracy vs maintainability systematically. Not rules of thumb — structured decision frameworks that production teams use to make and defend architectural choices at scale.
How to architect under real limits: token budget ceilings, team size, data ownership requirements, SLA boundaries, compliance constraints. Real systems are designed inside constraints. This teaches you to think inside them from the start.
How to explain system choices clearly — to engineers, to technical leads, to stakeholders with different mental models. The ability to walk through a design decision with reasoning, not opinion, is what distinguishes senior contributors.
Architecture Decision Records (ADRs) and the documentation patterns that production teams actually use. Leave a paper trail that survives team changes, onboarding cycles, and the questions that come six months after a decision was made.
These modules are woven into the production weeks — not separate theory sessions. Every architect exercise is grounded in code you've already written. This is about how you think on the job, every day.
Every week you ship something real. Click any week to see what you'll build and why.
Understand how LLMs actually work — tokenization, context windows, temperature, and why the same prompt gets different results. You'll learn prompt engineering patterns that professional engineers use, not tutorials.
Build your first real agent. Move beyond wrappers and understand how LangChain chains, agents, and tools actually compose. You'll understand why most agent tutorials break in production and how to fix them.
Memory is where most agents break in production. You'll learn when to use in-context memory vs vector retrieval vs external storage, and how to build systems that remember what matters without ballooning costs.
RAG is table stakes. Agentic RAG — where retrieval triggers actions, multi-hop reasoning, and re-ranking — is what production systems actually need. You'll build both, understand the tradeoffs, and know when RAG becomes a bottleneck.
LangGraph is where serious agent orchestration happens. You'll understand state machines, node and edge composition, conditional branching, and how to build multi-agent networks that coordinate without getting into infinite loops. This week also covers advanced integration patterns — using agents as tools, wiring MCP (Model Context Protocol) servers, exposing RAG as a callable tool, and the production hardening that turns a working prototype into a system you can deploy with confidence.
Real AI systems don't run synchronously. You'll learn how to queue long-running agent tasks, manage state across workers, handle failures gracefully, and give users real-time status on background jobs.
Wrap your agent in a real API. Containerize it. Deploy it. You'll build a FastAPI service with authentication, rate limiting, and proper error handling, then containerize with Docker and deploy to AWS/GCP/Azure.
The final differentiator. You'll instrument your system with Langfuse and LangSmith, write evals with pytest, set up alerting, and ship your capstone — a complete production AI system with documented architecture decisions and verifiable engineering judgment.
Every tool is production-relevant — not what looks good on a tutorial.
Register early and we'll unlock the Advanced Interview Articulation Course — a $1499 USD action layer anchored on Enterprise RAG. Build, explain, and defend systems with the maturity of a senior engineer. Available to a limited number of early learners only.
Eight live sessions structured around one realistic Enterprise RAG system — progressively sharpening how you reason about architecture, articulate trade-offs, and defend design decisions under follow-up questioning.
Activate challenge access and points tracking, attendance, weekly submissions, and leaderboard visibility switch on. Move from passive consumption to visible engineering momentum.
A final defense round where you justify and defend the Enterprise RAG system end-to-end — the moment most engineers realise they've moved from implementer to senior engineer.
This isn't a course. It's a system: curriculum, community, code, and production collateral.
A 4-week articulation layer anchored on Enterprise RAG — eight live sessions to build, explain, and defend systems with senior-engineer maturity. Includes tracked points, leaderboard visibility, weekly submissions, and a final architecture defense. Limited learners only.
8 weeks of live sessions with Nachiketh. Real-time Q&A, architecture reviews, debugging together — not pre-recorded content.
Trade-off frameworks, constraint-driven design, architecture communication, and decision documentation woven through the production weeks. Think like a senior engineer.
A real enterprise-grade Agentic RAG system built mid-cohort — a production portfolio piece that demonstrates you've shipped, not just studied.
A full end-to-end production system with observability, deployment, evals, and documented architecture decisions. A deployed system that speaks for itself.
System design templates for multi-agent pipelines, RAG architectures, and async processing patterns. Reference and extend them in your own work.
Miss a session? Rejoin the next live cohort for the same week at no cost. Your learning never stalls — every concept gets a chance to click live.
A cohort of serious engineers working on the same problems. Debug together, share patterns, stay accountable to each other.
Every build, every pattern, every utility. Fork it, extend it, deploy it. The codebase is yours with lifetime access.
Verified feedback from working engineers, leads, and architects who shipped end-to-end Agentic AI & RAG systems through the cohort.
"I couldn't think about an end-to-end project with real production-grade attributes — LLMs, agents, RAG, guardrails, testing all felt scattered. After this bootcamp, I can build and deploy production-grade Agentic AI & RAG applications and explain why I chose each architectural decision. That second part is what changed everything."
"There are many courses on AI concepts and theory. I wanted a curated course built around how we actually ship solutions to production — not just POCs. That's exactly what this delivered. Enterprise RAG, observability, prompt versioning — I can explain all of it now from a real architectural standpoint."
"I'm a Lead Data Scientist who wanted to move into Agentic AI. The bootcamp bridged the gap between Data Scientist and Gen AI engineer for me — especially the deployment session, where everything clicked. I'd highly recommend it to anyone serious about transitioning into Gen AI with real foundation knowledge."
"I'm a backend Java engineer with no prior AI exposure. This program completely changed how I think about implementing enterprise-level RAG and building production-ready agents. I now have a solid foundation, real direction, and I'm genuinely comfortable with LangChain, LangGraph, and EVAL workflows."
"The program covered every aspect of a real production project — requirements, system design, trade-offs, scalability, security, testing, and deployment. I can now architect a Gen AI project across layers: API, prompt management, A/B testing, deployment. This is the depth most AI courses quietly skip."
"I'm a Python developer with 16 years of experience — struggling to get my hands around AI Agents and RAG. This is one of the few programs in the market that covers Enterprise AI Agents end-to-end. I can now apply these concepts directly to real Gen AI use cases at work."
Real feedback from earlier cohorts. Names & roles published with each learner's explicit consent. Full reviews available on request — support@manifoldailearning.in
Nachiketh has built and shipped production AI systems, taught 100,000+ engineers through Manifold AI Learning, and developed a reputation for teaching architecture thinking — not just syntax. His approach: every concept goes through a build, every build has production context, and every decision gets explained from first principles.
See how senior engineers convert an AI agent demo into a production-style API service — FastAPI, schemas, request/trace IDs, health checks. No card, no commitment.
One-time investment. Lifetime access to recordings, code, and the cohort community.
✓ Secure checkout · EMI available at checkout
🌎 International learners: PayPal available at checkout if your card doesn't go through.
Available to a limited number of early learners. Early registrations unlock a 4-week articulation layer anchored on Enterprise RAG — eight live sessions to build, explain, and defend systems like a senior engineer, with tracked points and a final architecture defense.
For early registrations, we're including the Advanced Interview Articulation Course — a $1499 USD value, free with your bootcamp seat. It is a 4-week articulation layer anchored on Enterprise RAG: eight live sessions, weekly submissions, tracked points and leaderboard visibility, and a final architecture defense round designed to move you from passive learning to visible engineering maturity. You will learn to build, explain, and defend systems with the maturity of a senior engineer — the exact gap most engineers feel in senior interviews. This bonus is available to a limited number of early learners only and closes once seats fill.
3 hours of live instruction on Saturdays and Sundays (6 hours total per weekend), 8:00 AM – 11:00 AM IST. Expect 4–6 additional hours for the weekly build and any debugging. Engineers who put in 10–12 hours per week consistently get the most out of the cohort.
No ML background required. You need solid Python, some experience with APIs, and the ability to think carefully about systems. Backend engineers, full-stack developers, devops engineers, and data engineers all join this program and thrive. We start from LLM fundamentals in Week 1.
All sessions are recorded and available within 24 hours. You can catch up asynchronously. Live sessions are where the real depth comes from — the Q&A, the debugging, the "why did this fail?" discussions. We recommend attending live whenever possible. And with unlimited cohort attendance, you can rejoin the same week in a future cohort if you need to.
New in Cohort 5, these are structured exercises integrated into the production weeks that teach you to reason about architecture decisions the way senior engineers do — trade-off frameworks, constraint-driven design, how to document and communicate decisions clearly. They're not separate theory sessions. They're woven into the builds you're already doing, making the reasoning explicit. This is about how you think on the job, not a separate skill you practice in isolation.
It's designed to give you genuine capability and a portfolio that demonstrates it. Engineers who complete the capstone walk away with a real deployed system and documented architecture decisions — the kind of work you can discuss in depth with any senior technical stakeholder. We don't promise job placement, but we give you something more durable: demonstrated engineering judgment built through real production work.
Yes. EMI options are available at checkout through our payment processor. You'll see installment options when you proceed to payment. International learners can also use PayPal if your card doesn't go through at checkout.
The Bootcamp is a premium, cohort-based program that delivers immediate access to live sessions, mentorship, premium community, and the learning portal the moment your seat is confirmed. Because the full value is unlocked instantly, all enrollments are final and non-refundable once access is provisioned. If you can't attend the current cohort, we'll transfer your seat to a future cohort at no extra cost. Have questions before you commit? Reach out to our team at support@manifoldailearning.in and we'll help you decide with confidence. See our Refund Policy for full details.