Week 01
Customer Discovery
business contextstakeholder mappingdiscovery questioningsymptoms vs root problemsuser workflowsconstraints
Deliverable Customer Discovery Brief
Founding Cohort · Starts 1 September 2026 · Every Tuesday 9–11 PM IST
Forward Deployed
AI Engineer Residency
Build the system. Solve the customer problem. Defend the decisions. Drive adoption.
A 12-week applied residency for experienced technology professionals who want to learn how real AI opportunities move from ambiguous customer problems to scoped solutions, architecture decisions, evaluations, deployment plans, stakeholder adoption, and measurable outcomes.
12 WeeksWeekly Live Case LabsApplied DeliverablesArchitecture DefenceFinal FDE Capstone
Join the Founding Cohort →₹44,999 + GST$699 · 12 weeks · Starts 1 Sep
Book a 1:1 Review First →Fee credited 100% towards enrolment
Diamond Members receive this residency as part of their membership. Experienced professionals can also enroll directly in the founding cohort.
Founding Cohort · Starts 1 September 2026Every Tuesday 9:00–11:00 PM IST12 WeeksWeekly Live Case Lab + Applied DeliverableLearn → Apply → Submit → Review → Defend
Why This Residency Exists
Building the AI System
Is Only Half the Job
Strong engineers can build the system. But customer-facing AI delivery opens a second set of questions — and they rarely appear in a technical requirement document.
- What problem are we actually solving?
- Should this workflow even use an LLM or agent?
- What should remain deterministic?
- Who are the users and stakeholders?
- What does success look like?
- What data is actually available?
- What are the security and compliance constraints?
- What is MVP versus future scope?
- What trade-offs are acceptable?
- How should the system be evaluated?
- How does it move from prototype to production?
- How will users actually adopt it?
Forward Deployed AI Engineering sits at the intersection of software engineering, AI architecture, customer discovery, solution delivery, and adoption. The job is not simply to build what was requested — it is to help determine what should be built in the first place.
The FDE Operating Model
Six Stages. One Delivery Loop.
The residency is built around realistic customer scenarios that evolve as you move from discovery and scoping through architecture, delivery and adoption.
01
Discover
Understand the customer, workflow, constraints, users, and the actual problem underneath the request.
02
Scope
Define the use case, MVP boundaries, success metrics, dependencies, assumptions, and risks.
03
Architect
Choose the right AI pattern, integrations, model strategy, retrieval, tools, evaluation, security, and deployment architecture.
04
Deliver
Move from prototype toward a reliable implementation with clear milestones, ownership, evaluation, and rollout planning.
05
Adopt
Design feedback loops, human workflows, user onboarding, escalation, monitoring, and measurable adoption.
06
Defend
Present and defend technical decisions clearly to engineers, architects, business leaders, and customers.
The Outcome
What You Leave With
Alongside the weekly cases, you choose one Forward Deployed AI capstone scenario and develop it progressively across all twelve weeks. Every deliverable feeds the same body of work.
01Customer Discovery Brief
02Current & Future-State Workflow
03AI Feasibility Assessment
04Solution Scope
05Solution Architecture
06Security & Governance Review
07Evaluation & Acceptance Plan
08Production Delivery Roadmap
09Stakeholder Proposal
10Adoption Plan
11Architecture Defence
12Final FDE Case Study
Not twelve disconnected assignments. One body of work demonstrating how you think from customer problem to AI delivery.
12-Week Curriculum
Three Phases. Twelve Artifacts.
Every week pairs a live case lab with a professional deliverable you complete, submit, and defend — each one advancing your chosen capstone scenario.
Phase 1 · Weeks 1–4
Discover & Scope
Week 02
Workflow & AI Opportunity Mapping
current-state workflowbottlenecksfailure pointsdecision pointswhere AI adds valuehuman + AI design
Deliverable Current-State + Future-State Workflow Map
Week 03
Success Metrics & Feasibility
business outcomesdata availabilityquality expectationscostlatencycomplianceAI suitability
Deliverable AI Feasibility & Success Metrics Document
Week 04
Solution Scoping
MVP definitionin / out of scopedependenciesrisk registerbuild vs buydelivery sequencing
Deliverable Solution Scope & Delivery Proposal
Phase 2 · Weeks 5–8
Architect & Deliver
Week 05
Forward Deployed Solution Architecture
agent vs workflowRAG vs tool usesingle vs multi-agentmodel strategyhuman-in-the-loopfailure pathsADRs
Deliverable Solution Architecture + Key Architecture Decisions
Week 06
Security, Governance & Enterprise Constraints
data ownershipauthn / authzPIItool permissionsauditabilityprompt injectionlogging boundaries
Deliverable Security, Governance & Risk Review
Week 07
Evaluation & Acceptance Strategy
golden datasetsacceptance criteriaretrieval evalreliability checksfailure categoriesgo / no-go
Deliverable Evaluation & Acceptance Plan
Week 08
Prototype to Production
prototype vs productionasync executionqueue patternsobservabilitycost planningrollout sequencing
Deliverable Prototype-to-Production Delivery Roadmap
Phase 3 · Weeks 9–12
Adopt & Defend
Week 09
Stakeholder Communication
technical stakeholdersbusiness stakeholdersexecutive summariesexplaining trade-offshandling objections
Deliverable Customer / Stakeholder Solution Proposal
Week 10
Adoption & Change Management
human-AI adoptionuser onboardingfeedback loopsadoption metricsescalationhuman override
Deliverable Adoption & Rollout Plan
Week 11
Architecture Defence
cost vs latencyaccuracy vs reliabilitybuild vs buymodel selectionfailure scenariosscaling questions
Deliverable Recorded Architecture Defence
Week 12
Forward Deployed AI Engineering Capstone
customer problemdiscovery findingsarchitecturerisk analysisevaluationproduction roadmapadoption planprototype / demo
Deliverable Forward Deployed AI Engineering Case Study
The Level-Up Model
Every Week Produces
a Professional Artifact
This is not a watch-and-complete course. Each residency week ends with a Level-Up Challenge — a document, diagram, plan or defence you produce yourself.
LearnApplySubmitReviewImprove
01Discovery Brief
02Workflow Map
03Feasibility Analysis
04Scope Document
05Solution Architecture
06Security Review
07Evaluation Plan
08Production Roadmap
09Stakeholder Proposal
10Adoption Plan
11Architecture Defence
12Final Case Study
These are the kinds of artifacts professionals could reasonably produce while working on real AI initiatives — adapted to your own scenario, in your own words.
Live Case Lab Format
Not Another Lecture Series
A typical residency session moves through five stages — from an ambiguous brief to a completed artifact.
Stage 01
Customer Case
Start with an ambiguous business or customer problem — the kind that arrives without a specification.
Stage 02
Framework
Learn a reusable discovery, architecture, evaluation, or delivery framework you can apply again.
Stage 03
Working Session
Apply the framework to the scenario live, alongside the cohort.
Stage 04
Review
Compare approaches, trade-offs, mistakes, and alternative solutions across the room.
Stage 05
Level-Up Challenge
Complete the professional artifact for that stage, submit it through the Level-Up Challenge, and use the review framework to improve it. Selected submissions will be reviewed live.
Selected learner submissions may be reviewed live during sessions.
Example Scenarios
Residency Cases May Include Scenarios Such As
Each case arrives ambiguous — exactly as it would in the field.
Enterprise Knowledge Assistant
A company wants an internal AI assistant, but documentation is fragmented, permission boundaries are unclear, and accuracy expectations are undefined.
Customer Support Agent
A retailer wants to automate order enquiries, amendments, refunds and escalations — without creating unsafe autonomous behaviour.
Claims Processing Assistant
An insurer wants AI support across document understanding, policy lookup, decision support, and human approval gates.
Developer Productivity Agent
An engineering organization wants AI-assisted development integrated with repositories, documentation, tickets, and internal tools.
Compliance Review Assistant
A regulated organization wants AI-assisted document review while preserving auditability, approval gates, and sensitive-data controls.
Entry Level
This Residency Assumes You Can Already Build
The residency does not teach Agentic AI fundamentals from scratch. You should already be reasonably comfortable with the following.
- Python or another software-development language
- APIs and SDKs
- Basic LLM application development
- Structured outputs
- Tool / function calling concepts
- Basic RAG concepts
- Agent and workflow concepts
- Git and GitHub
- Basic cloud / software-system thinking
Advanced machine-learning mathematics is not required.
Newer to Agentic AI development? Diamond Membership includes the Agentic AI Developer Bootcamp, giving you a structured foundation in LLM APIs, tools, MCP, RAG, LangGraph and Agentic AI development before you take on the more applied FDE work.
Already comfortable with those foundations? You can enter the residency directly through selected founding-cohort access.
Who This Is For
You Already Know How Technology Gets Built
You do not need “Forward Deployed Engineer” in your current job title. If your work increasingly requires you to translate ambiguous business problems into technical AI solutions, this residency is designed around that capability.
Software / Backend / Full-Stack Engineers
You ship systems. Now learn to shape what gets built and why.
Data / ML / AI Engineers
You build models and pipelines. Now own the problem definition around them.
Cloud / DevOps / Platform Engineers
You know constraints deeply. Now translate them into solution decisions.
Solution Architects
Extend architecture reasoning into customer discovery and adoption.
Technical Consultants
Add applied AI delivery structure to client-facing engagements.
Engineering Leads
Scope AI initiatives your team can actually deliver and defend.
Experienced Professionals Moving Toward Applied AI Delivery
You have the engineering base. This adds the field-delivery layer.
Designed around capabilities increasingly expected in customer-facing and forward-deployed AI engineering roles — including work associated with titles such as Forward Deployed AI Engineer, AI Solutions Engineer, Applied AI Engineer, Agentic AI Engineer, AI Solutions Architect, Generative AI Consultant, and AI Technical Lead.
This residency is probably not the right fit if…
- You are completely new to programming
- You have never worked with APIs or software systems
- You only want prompt-engineering techniques
- You want a no-code AI course
- You only want theoretical lectures
- You are looking for guaranteed job placement
Led By
Led by Nachiketh Murthy
Nachiketh Murthy
Founder · Manifold AI Learning
- ›Author of Agentic AI Interview Questions: A Practical Guide for ML, Backend, and AI Engineers — published on Amazon.
- ›Author of the NVIDIA Certified Agentic AI Professional (NCP-AAI) Exam Prep Guide — published on Amazon.
- ›Founder of Manifold AI Learning, building live cohort programs across Agentic AI, RAG, MLOps and enterprise AI.
- ›Designs programs specifically for experienced engineers — not beginner audiences.
The residency is designed around the decision-making patterns, trade-offs and communication required when technical teams move from an AI idea to something that must work for real users.
Learner Voices
Engineers Who Have Built
in Nachiketh’s Live Cohorts.
The Forward Deployed AI Engineer Residency is a new program and this is its founding cohort. The experiences below are from experienced engineers who previously attended Nachiketh’s live Manifold AI Learning cohorts. They reflect the teaching quality, hands-on depth and live learning experience — not this exact curriculum.
★★★★★
“I wanted a curated course on how we actually build solutions and make them production-level rather than only building POCs. Enterprise RAG, observability, prompt versioning — I can explain all of it better now.”
BKBhakti KanungoSenior Tech Lead – AI
★★★★★
“The weekend bootcamps are well-structured, combining concepts with hands-on experiential learning — a strong blend of theory, practical implementation, and real-world lessons.”
RSRishi SaraswatDirector, Engineering · Salesforce
★★★★★
“An amazing program — it covered every aspect of a production project, from requirements to testing to final deployment.”
NGNitin GuptaData Scientist · 12+ yrs
★★★★★
“I’m a backend Java engineer. With no prior exposure to AI, I got a good solid foundation and a clear direction. This program changed my thinking about how we should implement enterprise-level RAG and build production-ready agents.”
ARAnshul RajputBackend Engineer (Java) · 9–12 yrs
★★★★★
“Before joining, I struggled with GenAI concepts. The cohort helped me bridge the gap between a Data Scientist role and a GenAI role. I would highly recommend it to anyone who wants to transition with a strong foundation.”
KKrishnaLead Data Scientist · 12+ yrs
9.6/10
Average cohort experience rating
From our latest live cohort feedback survey. Nachiketh has taught 100,000+ engineers across courses, YouTube and live cohorts — including senior engineers and engineering leaders from companies such as Micron and Salesforce.
The founding cohort is where this residency’s own track record starts. That is why it is small, why it is priced as a founding cohort, and why every submission gets read.
Not Sure Yet?
Need help deciding if this is
the right step for you?
Twelve weeks is a real commitment. Before you decide, book a 1:1 AI Career Positioning & Interview Readiness Review directly with Nachiketh — and get an honest read on whether this residency is your correct next move, or whether something else is.
Your review fee is applied 100% towards enrolment
If you go on to join the Residency or Diamond Membership after the call, the full fee you paid for the review is credited to your enrolment. The clarity effectively costs you nothing.
Free · 60 seconds · No email required
Not sure you’re at the right stage yet? Start free.
Answer six honest questions and get a straight recommendation — including whether this residency is the wrong step for you right now, and what the right one would be.
What the call covers
- Where you actually stand today — your engineering base, and the real gap between it and forward-deployed work.
- Whether this residency is your correct next step — or whether the Developer Bootcamp, or something else entirely, serves you better right now.
- How your experience maps to the roles — Forward Deployed AI Engineer, AI Solutions Engineer, Applied AI Engineer, AI Solutions Architect.
- A direct read on your interview readiness — what is already working, and what to fix first.
Book the review
A focused 1:1 session with Nachiketh. No sales pitch — a straight assessment of your position and the most useful path forward from where you actually are.
Schedule Your 1:1 Review →Ask a question on WhatsAppFee credited in full towards Residency or Diamond Membership enrolment.
Diamond Pathway
How the FDE Residency
Fits Inside Diamond
Development. Production. Architecture. Communication. Field delivery. One guided Diamond pathway.
Diamond Members have access to the broader Manifold learning ecosystem around the residency. Use each layer based on your current readiness — the FDE Residency is where customer discovery, solution architecture, delivery and adoption come together.
Recommended Diamond Journey
This is not a mandatory prerequisite chain. Diamond Members use the pathway based on their existing experience and readiness.
Foundation
Agentic AI Developer Bootcamp
Build fluency across LLM APIs, tool calling, MCP, RAG, LangGraph, multi-agent frameworks, cloud AI, and evaluation fundamentals.
Production
Agentic AI Enterprise Mastery
Engineer reliable, observable, secure, deployable Agentic AI systems.
Architecture
AI Architect System Design
Develop stronger architecture reasoning and technical trade-off thinking.
Communication
Agentic AI Interview Playbook + Senior Engineer Positioning Challenge
Learn to articulate technical decisions with greater clarity.
Field Delivery
Forward Deployed AI Engineer Residency
Bring everything together through discovery, scoping, architecture, delivery, adoption, and customer-facing problem solving.
Diamond Membership gives experienced technology professionals one guided pathway instead of a collection of disconnected courses.
Developer Bootcamp is the recommended starting point for new Diamond Members. Experienced practitioners can accelerate through foundational material based on readiness.
Residency Access
Founding Residency
Starts 1 September 2026
Twelve weeks of live case labs, applied deliverables, structured review frameworks and selected live submission reviews.
- 12 Weeks
- Weekly Live Case Lab
- Weekly Level-Up Challenge
- Applied Templates
- Selected Submission Reviews
- Architecture Defence
- Final FDE Capstone
- Cohort Community
- Session Recordings
Why a Founding Cohort?
This first residency is intentionally small and highly applied. Founding participants will work through the live cases, templates and review frameworks together, and their questions and implementation challenges will help shape future editions of the residency. The founding cohort gets the complete live, case-driven experience from Day 1.
Founding Cohort Access
Join the Founding Residency
A limited number of professionals who already meet the technical prerequisites can join the 1 September founding residency directly. Founding-cohort seats are limited because the residency includes applied submissions and live review.
₹44,999 + GST$699India · GST extra at checkoutInternational
Join Founding Cohort →Complete Manifold Pathway
Included with Diamond Membership
Diamond Members receive the FDE Residency together with Developer Bootcamp, Enterprise Mastery and the broader architecture and learning ecosystem — as one guided progression.
Explore Diamond Membership →Live case labs run every Tuesday, 9:00 PM to 11:00 PM IST. Recordings are shared with the cohort.
FAQ
Questions Worth Asking
Is this an Agentic AI beginner program?
No. This is an applied residency for professionals who already understand basic software and Agentic AI concepts.
What if I am new to Agentic AI?
Diamond Membership includes the Agentic AI Developer Bootcamp, which provides the recommended foundation before progressing deeper into the residency.
Do I need to complete Developer Bootcamp first?
Not necessarily. It is the recommended Diamond starting point, but experienced practitioners with equivalent skills can accelerate based on readiness.
Is this the same as Enterprise Mastery?
No. Enterprise Mastery focuses on engineering production-style Agentic AI systems.
The FDE Residency focuses on customer discovery, workflow analysis, solution scoping, architecture proposals, evaluation strategy, delivery planning, adoption, and stakeholder communication.
They complement each other but have different outcomes.
Is this only available to Diamond Members?
The live residency is included with Diamond Membership. A limited number of founding-cohort seats are also available separately for experienced professionals who meet the technical prerequisites.
When does the founding cohort start?
1 September 2026. Live case labs run every Tuesday from 9:00 PM to 11:00 PM IST.
How long is the residency?
12 weeks.
Is it live?
Yes. The residency includes weekly live case-based sessions along with applied deliverables. Live case labs run every Tuesday from 9:00 PM to 11:00 PM IST. Recordings are shared with the cohort.
Will I build a project?
The program culminates in a complete Forward Deployed AI Engineering case study and capstone, drawing together discovery, architecture, evaluation, delivery planning, adoption, and stakeholder communication.
Is there a job guarantee?
No. Manifold AI Learning does not offer or imply any job, placement, hiring, salary, role-transition, or income guarantee.
Is Manifold affiliated with companies hiring Forward Deployed Engineers?
No affiliation should be implied. The program is an independent learning pathway designed around capabilities relevant to modern customer-facing and forward-deployed AI engineering work.
Learn to Own the AI Solution —
Not Just the Code
Move from receiving a technical requirement to understanding the customer problem, shaping the right solution, defending the architecture, planning delivery, and measuring adoption.
Founding Residency starts 1 September 2026 · 12 weeks · Every Tuesday 9:00–11:00 PM IST
Founding Residency · Starts 1 Sep 2026 · Tue 9–11 PM IST · ₹44,999 + GST$699
Join Founding Cohort →