by TensorHub Technologies
Programs / Agentic AI Designer
Design & Architecture

Agentic AI Designer

Learn to design multi-agent workflows that actually hold up in enterprise environments: planning, memory, tool selection, human-in-the-loop checkpoints, and agent collaboration patterns — the design layer that sits between a prompt and a production system.

Duration
14 Weeks
Commitment
10–12 hrs/wk
Format
Live + Self-paced
Level
Intermediate
Curriculum

From workflow design to agent UX

Each module ends with a working agent artifact reviewed against enterprise design standards.

1

Foundations of Agentic Design

Weeks 1–3
  • Why agents fail: reasoning patterns, planning loops, and failure modes
  • ReAct, chain-of-thought, and reflection patterns
  • Agent workflow mapping vs. rigid pipelines
  • Introduction to LangGraph, CrewAI, and Google ADK
2

Memory, Tools & Context

Weeks 4–6
  • Short-term vs. long-term memory architectures
  • Tool selection strategy & Model Context Protocol (MCP)
  • Vector store design (Pinecone, Weaviate, Chroma) for agent recall
  • Context window budgeting & retrieval-augmented planning
3

Multi-Agent Collaboration

Weeks 7–9
  • Orchestrator / worker and supervisor agent patterns
  • Inter-agent communication protocols
  • Conflict resolution & task delegation strategies
  • Cost, latency, and reliability trade-offs in multi-agent graphs
4

Human-in-the-Loop & Agent UX

Weeks 10–12
  • Designing approval checkpoints & escalation paths
  • Trust, transparency, and explainability in agent UX
  • Guardrails and safe-failure design (NeMo Guardrails)
  • Designing for non-technical end users
5

Capstone: Enterprise Agent System

Weeks 13–14
  • Design and present a full multi-agent architecture for a real business case
  • Peer + instructor design review against enterprise standards
  • Portfolio-ready architecture diagram and design rationale
Outcomes

What you'll be able to do

  • Design multi-agent architectures with clear planning and memory strategies
  • Select the right tools and orchestration framework for a given workflow
  • Build human-in-the-loop checkpoints that manage risk without killing velocity
  • Evaluate design trade-offs between reliability, cost, and latency
  • Present agent architecture to technical and non-technical stakeholders
Real-World Use Cases

Built on enterprise scenarios

Manufacturing

Multi-agent maintenance planner

Agents coordinate sensor data triage, parts lookup, and technician scheduling with human sign-off on high-cost repairs.

Financial Services

Research & compliance co-pilot

Orchestrator agent routes tasks between research, citation-checking, and compliance-review sub-agents.

Telecom

Tiered customer support agent mesh

Specialist agents handle billing, technical, and retention flows with escalation to human agents on low confidence.

Job Market

Compensation & demand

Indicative ranges based on current enterprise AI hiring patterns — actual compensation varies by experience, company, and geography.

RoleIndia (Annual)Global (Annual)
Agentic AI Designer / Architect₹22L – ₹65L$140K – $260K
Senior Agentic AI Designer₹45L – ₹1.1Cr+$220K – $400K
Multi-Agent Systems Engineer₹18L – ₹55L$130K – $230K

Demand is concentrated in AI-native product companies, GenAI consulting practices, and enterprise innovation labs building internal copilots.

Designed and delivered by a Claude Architect–certified Forward Deployed Engineer

Design standards taught in this program come from real agent systems shipped into production — not textbook patterns.

Claude Architect Certified Former Forward Deployed Engineer Multi-Agent Systems in Production
FAQ

Common questions

Do I need coding experience?

Working familiarity with Python and REST APIs is expected. This program focuses on design and architecture decisions rather than teaching programming from scratch.

How is this different from the Foundations program?

Foundations teaches you to build your first agent. Agentic AI Designer teaches you to architect multi-agent systems for real enterprise constraints — reliability, cost, governance, and UX.

Can I go straight into Forward Deployed Engineer after this?

Yes — this program is a strong on-ramp into the FDE track, and graduates receive priority consideration in FDE admissions.

Design agent systems that survive contact with production.

Get the full syllabus and sample capstone architectures.