Why FDE skills for AI now?
Organizations need engineers who can make agents reliable in real customer environments, not just in demo sandboxes.
INTENSIVE WORKSHOP · PRODUCTION DELIVERY
Learn the Forward Deployed Engineering skills AI companies now expect.
Bridge strategy, engineering, and delivery to make AI work in real customer environments.
Bridge the gap between AI demos and customer-ready systems with hands-on modules covering agent design, reliability, and cloud deployment.
Start
Flexible 2-3 day format
Format
Live workshop + team exercises
Commitment
10 modules · labs + reviews
2-3 days or 6 half-days
Delivery modes
3
Core modules
10
Chapters
GCP + Vertex AI patterns
Cloud focus
In This Session
Everything you need to evaluate your next move
What will we build during the workshop?
An end-to-end agent with retrieval, tool use, guardrails, observability, and deployment architecture planning.
How practical is this workshop?
Every module is tied to hands-on exercises including failure debugging, incident response, and architecture trade-offs.
What can teams take back immediately?
A working prototype, deployment-ready architecture sketch, and a production failure-mode/evaluation checklist.
What You Will Leave With
Practical outcomes, not just theory
- Engineer agent systems that move beyond happy-path demos into production-ready behavior.
- Diagnose retrieval, tool-calling, and model failure modes with structured incident workflows.
- Apply safety guardrails and human-approval checkpoints for high-risk decisions.
- Design deployment strategies with explicit latency, cost, and reliability trade-offs.
Certificate
Completion certificate for verified track milestones.
Capstone Project
Build and present a portfolio-ready final implementation.
Practical Labs
Hands-on exercises focused on real engineering workflows.
Assessments
Project-based evaluation with actionable instructor feedback.
Curriculum roadmap
Workshop Track
Part 1
Chapter 1 - FDE Mindset
Production ownership expectations and delivery accountability.
Part 2
Chapter 2 - LLM Constraints
Context windows, token budgets, and reliability implications.
Part 3
Chapter 3 - RAG Failure Modes
Diagnose retrieval misses and precision/recall problems.
Part 4
Chapter 4 - Tool Calling Loops
Planner-executor control flow and schema-safe interfaces.
Part 5
Chapter 5 - End-to-End Agent Build
Assemble retrieval, tool routing, synthesis, and fallbacks.
Part 6
Chapter 6 - Guardrails + HITL
Policy checks and human-approval gates for critical paths.
Part 7
Chapter 7 - Evaluation + Observability
Define pass/fail metrics and monitor latency, cost, and quality.
Part 8
Chapter 8 - Deployment on GCP
Vertex AI hosting patterns and architecture choices.
Part 9
Chapter 9 - Incident Playbooks
Triage and rollback flows for production agent incidents.
Part 10
Chapter 10 - Capstone Review
Present and defend architecture with business-impact framing.
Inside the learning experience
Every session is built around implementation outcomes. These modules show exactly what you will build, practice, and carry into real projects.
Module 1
Chapter 1 - FDE Mindset
Production ownership expectations and delivery accountability.
Module 2
Chapter 2 - LLM Constraints
Context windows, token budgets, and reliability implications.
Module 3
Chapter 3 - RAG Failure Modes
Diagnose retrieval misses and precision/recall problems.
Module 4
Chapter 4 - Tool Calling Loops
Planner-executor control flow and schema-safe interfaces.
Module 5
Chapter 5 - End-to-End Agent Build
Assemble retrieval, tool routing, synthesis, and fallbacks.
Session Host
Experience
25 years of IT experience across engineering delivery, quality, and modern platform transformation
Focus
AI, Automation, and Production Engineering
Deepak Kamboj
Founder and Lead Instructor
Deepak Kamboj is an AI and quality engineering mentor who helps teams move from tutorial-level learning to production-ready implementation. His teaching style combines architecture clarity, real delivery constraints, and execution patterns that engineers can apply immediately.
- Founder of DevBuild Studio with hands-on focus on modern engineering skills
- Mentors engineers across Playwright automation, agentic AI, and production architecture
- Known for practical frameworks, implementation checklists, and career-focused coaching
Where our learners and teams operate
Vertex AI
Google Cloud
LangGraph
Enterprise APIs
Observability
Guardrails
HITL
Incident Response
Learner outcomes
"The workshop made our team rethink AI delivery as an operations discipline, not just a model selection task."
"The incident playbooks and evaluation patterns were immediately applicable to our customer deployments."
"We left with a concrete architecture and a practical risk checklist stakeholders could understand."
Frequently asked questions
Can teams attend together?Open
Yes. Team-based participation is encouraged and improves architecture review outcomes.
Is coding required during the workshop?Open
Yes. There are guided hands-on labs, but templates and support are provided.
Do we cover deployment trade-offs?Open
Yes. Deployment architecture and cost/reliability trade-offs are core workshop outcomes.
Final call
Build the skillset teams are prioritizing right now
Reserve your spot and receive your onboarding details, prep material, and implementation roadmap.