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Agentic AI Training Program:
Production LLM Systems for Engineers
A 16-week program for engineers who can already build software and now need to own AI delivery, not just contribute to it.
Most GenAI training stops at a demo. Your engineers can already wire up a chatbot in an afternoon. What they can’t yet do is ship a RAG system that survives a security review, defend a multi-agent architecture in front of a review board, or put a number on what an AI initiative actually costs to run. That’s the gap this program closes: no introductory content, no toy examples, fourteen modules built around named enterprise capstones.
Own AI Delivery, End-to-End.
Stop playing with prompts. Start building multi-agent systems with reliability-focused architectures, evaluation harnesses, and security hardening.
Why This Course?
Your engineers don’t need another framework overview.
They need the depth to lead. Here’s what separates this program from the GenAI training most vendors are still selling.
What most GenAI training gives you
- A tour of prompting basics your engineers already picked up on their own
- One RAG demo, built once, never stress-tested against evaluation metrics
- Single-agent examples with no orchestration, memory, or cost governance
- A certificate with no artifact that would survive a production review
- No answer for how to talk to leadership about AI risk, cost, or ROI
What this program builds instead
- Two reliability-focused mini-apps in week one alone, no introductory content
- A RAG system iterated v1 to v2 against a formal faithfulness, hit-rate, latency and cost harness
- Two full orchestration tracks — workflow automation and CrewAI multi-agent systems
- An enterprise-grade capstone with a business case, cost model, and security hardening
- A simulated architecture review board where participants defend their design
How It Compares
Advanced Agentic AI Training Program vs. Standard GenAI Courses
This program shares its depth with NextAgile’s Freshers track, but every week is rebuilt for experienced engineers, faster ramp-up, and enterprise-scale concerns from day one.
|
Dimension |
Typical Online GenAI Course |
Standard Vendor Bootcamp |
This Program |
|---|---|---|---|
|
Starting Point |
Assumes no coding background |
Mixed-level cohorts, generic pacing
|
Working engineers only, zero ramp-up on basics |
|
RAG depth |
One walkthrough build |
Single iteration, rarely evaluated |
v1 → v2, scored on faithfulness, hit-rate, latency, cost |
|
Orchestration |
Single-agent demos |
One framework, surface-level |
Two full tracks: workflow automation + CrewAI multi-agent |
|
Capstone |
Optional, illustrative |
Templated project, low stakes |
Named enterprise scenario, defended before a review board |
|
Security & governance |
Not covered
|
One slide deck
|
Dedicated week: red-teaming, compliance, incident response |
|
Leadership readiness |
Not addressed |
Not addressed |
Business case, vendor evaluation, stakeholder communication |
What You'll Build
A portfolio that survives a production review, not a demo folder.
Week 1: Reliability-First Apps
Two production-style builds in week one, a constrained brief generator and a policy-driven support reply drafter, with automated format validation from day one.
Weeks 3-4: Production RAG
A grounded RAG assistant with citations and access-control-aware retrieval, iterated to v2 and scored against a formal evaluation harness.
Weeks 6-10: Multi-Agent Systems
An MCP-based agent extended into a full multi-agent workflow, then scaled with agent-to-agent communication and shared memory architectures.
Weeks 8-16: Enterprise Capstone
A complete build spanning RAG and autonomous agents, with a business case, cost governance model, security hardening, and a live review board defense.
Orchestration Tooling
Both patterns employers are hiring for not one.
Week 7 forks into two tracks. Every participant builds one end-to-end mini-project matched to a realistic enterprise scenario.
