Discover and scope customer problems
Diamond Exclusive · 12-Week Practical Residency · Tue 9–11 PM IST
Forward Deployed AI Engineer ResidencyTurn customer ambiguity into AI delivery.
Systems ship. Demos don’t.
Develop the judgment to discover the real problem, scope the work, defend an architecture and drive adoption. A twelve-week residency with practical customer case labs, available through Diamond Membership.
With Nachiketh MurthyFounder, Manifold AI Learning · Systems ship. Demos don’t.
12 Weeks
Weekly Live Case Labs
Applied Deliverables
Architecture Defence
Final FDE Capstone
Explore Diamond Membership →
Available only inside Diamond Membership · 12 weeks · Intake dates confirmed by support
Book a 1:1 Review First →
Fee credited 100% towards enrolment
This residency is not sold separately. It is one of the programs reserved for Diamond Members, alongside the rest of the Manifold pathway and direct founder access.
Defend trade-offs and delivery decisions
Diamond-exclusive practical case labs
Founding Cohort · Confirm intake dates with support
Every Tuesday 9:00–11:00 PM IST
12 Weeks
Weekly Live Case Lab + Applied Deliverable
Learn → Apply → Submit → Review → Defend
Why This Residency Exists
Building the AI System
Is Only Half the Job
You can already build the system — that is not in question. But the moment AI work touches a real customer, a second set of questions arrives, and none of them appear in a technical requirement document. These are the questions that decide whether a project ships or quietly dies.
- 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 01
Customer Discovery
business contextstakeholder mappingdiscovery questioningsymptoms vs root problemsuser workflowsconstraints
Deliverable Customer Discovery Brief
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.
Learn
Apply
Submit
Review
Improve
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.
Phase 1
Customer Case
Start with an ambiguous business or customer problem — the kind that arrives without a specification.
Phase 2
Framework
Learn a reusable discovery, architecture, evaluation, or delivery framework you can apply again.
Phase 3
Working Session
Apply the framework to the scenario live, alongside the cohort.
Phase 4
Review
Compare approaches, trade-offs, mistakes, and alternative solutions across the room.
Phase 5
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 Respects What You Already Know
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 Enterprise Mastery Bootcamp, where you learn to engineer reliable, observable, deployable Agentic AI systems before you take on the more applied FDE work. It stands on its own: Python and LangChain foundation bonuses come free, so nothing is required before it.
Already comfortable with those foundations? The residency opens to you through Diamond Membership — it is not available as a standalone purchase.
Who This Is For
You Already Know How Technology Actually Gets Delivered
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
Your Guide: Nachiketh Murthy
Nachiketh Murthy
Founder · Manifold AI Learning
“I help experienced technology professionals move beyond AI demos and build production-ready AI systems — without losing the value of their existing experience. You already bring something valuable. My job is to help you add the AI engineering and architecture layer on top of it.”
- ›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 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 Enterprise Mastery, 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 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
Python & LangChain Foundations
Included free with Enterprise Mastery. Refresh Python for agentic work and get fluent in LangChain before week one — not a separate purchase, and not a gate.
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.
Agentic AI Enterprise Mastery is the recommended starting point for new Diamond Members — it carries its own Python and LangChain foundations, so nothing is required before it. Experienced practitioners can accelerate through foundational material based on readiness.
Residency Access
Founding Residency
Confirm intake dates with support
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.
Diamond Exclusive
The Residency is a Diamond Member program.
There is no separate ticket for this one. The Forward Deployed AI Engineer Residency sits inside Diamond Membership, together with the rest of the Manifold pathway, lifetime ecosystem access and direct founder guidance — because the people who get the most out of twelve weeks of live case labs are the ones already committed to the whole journey, not a single course.
If the work on this page is where you are heading, Diamond is how you get there.
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?
Start with the Agentic AI Enterprise Mastery Bootcamp. It assumes nothing before it — Python and LangChain foundation bonuses are included free — and it builds the production ground this residency stands on.
Do I need to complete another programme first?
No. Enterprise Mastery is the recommended Diamond starting point, but experienced practitioners with equivalent skills can enter the residency directly 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?
Yes. The Residency is a Diamond-exclusive program — there are no separate seats, and there is no standalone ticket. Twelve weeks of delivering AI systems into real environments only works when the room stays small and everyone in it has already walked the path. Diamond is the way in.
When does the founding cohort start?
Intake dates are confirmed by support. 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.
You Brought the Experience.
Add the Layer That Makes It Ship.
Stop waiting for a technical requirement to arrive. Understand the customer problem, shape the right solution, defend the architecture, plan the delivery, and measure whether anyone actually uses it. That is the job. This is where you learn it.
Diamond-exclusive Residency · 12 weeks · Every Tuesday 9:00–11:00 PM IST
Your instructor · Founder, Manifold AI LearningExperience is your foundation.
Experience is your foundation.
Build what comes next.
I am Nachiketh. I help experienced technology professionals move beyond AI demos and build production-ready AI systems.
Systems ship. Demos don’t.Meet Nachiketh Murthy →Founding Residency · Intake dates confirmed by support · Tue 9–11 PM IST · Diamond Members only
Explore Diamond →