Live Multi-Agent Workshop
Multi-Agent Systems: Build Agent Teams
Single agents are useful, but some tasks benefit from coordination: planner, specialist, reviewer, router. This workshop shows how to build agent teams with explicit roles, shared context, and orchestration that makes sense rather than chaos that only looks sophisticated.
If you have been searching multi agent systems, agent orchestration, CrewAI, or AutoGen multi agent, this live session is the practical bridge from framework curiosity to architectural judgment.
Planner-worker architecture
See how decomposition improves complex task handling.
Framework-independent thinking
Useful whether you later use CrewAI, AutoGen, or custom orchestration.
Coordination over hype
Learn when multiple agents help and when they only add complexity.
2 hours
Orchestration-focused session
₹499 / $19
Geo-aware pricing
Recording included
Review the patterns later
Search intent
Why this page is intentionally built to rank for high-intent workshop searches
Search visibility is strongest when a page resolves the real question behind a keyword. This section turns the page into a stronger resource for people actively searching for this exact topic.
Single agents are useful, but some tasks benefit from coordination: planner, specialist, reviewer, router. This workshop shows how to build agent teams with explicit roles, shared context, and orchestration that makes sense rather than chaos that only looks sophisticated.
If you have been searching multi agent systems, agent orchestration, CrewAI, or AutoGen multi agent, this live session is the practical bridge from framework curiosity to architectural judgment.
The future is not “more agents everywhere.” The future is better decomposition and cleaner interfaces. Teams that understand orchestration will build more useful systems than teams that simply stack multiple chatbots together.
If you want to understand when agent teams create leverage and how to orchestrate them cleanly, this workshop is built for you.
Keyword focus for this workshop page
- multi agent systems
- agent orchestration
- crewai
- autogen multi agent
- agent teams workshop
What you will build
What you will build in this multi-agent systems workshop
This is not a vague webinar page. You should know exactly what you are getting before you register. The bullets below are intentionally specific so the workshop attracts serious learners with real engineering intent.
Planner-worker flow
Decompose tasks across specialized agents.
Role-specific prompts
Define responsibilities so agents do not duplicate effort.
Shared context flow
Move information between agents without flooding everyone with noise.
Tool-routed execution
Give different agents different capabilities.
Review loop
Add a critic or reviewer role to improve output quality.
Architecture judgment
Know when multi-agent systems are worth using.
1planner = Agent(role="planner")2researcher = Agent(role="researcher")3builder = Agent(role="builder")4reviewer = Agent(role="reviewer")5 6plan = planner.run(task)7research = researcher.run(plan.step_one)8draft = builder.run(research)9final = reviewer.run(draft)This preview is representative, not decorative. The workshop is built around code, architecture reasoning, and the exact implementation details that make these workflows usable in real projects.
Outcome and social proof
Why orchestration skills matter more than agent count
The future is not “more agents everywhere.” The future is better decomposition and cleaner interfaces. Teams that understand orchestration will build more useful systems than teams that simply stack multiple chatbots together.
Outcome
A working team-of-agents blueprint
You leave with a structure you can extend.
Outcome
Framework independence
Reason across CrewAI, AutoGen, or your own orchestration.
Outcome
Better decomposition judgment
Know which tasks deserve multiple roles.
Outcome
Cleaner coordination patterns
Understand how context, handoffs, and review loops should work.
Practical application
How you can use Multi-Agent Systems: Build Agent Teams after the workshop ends
The goal is not just to attend a live session. The goal is to leave with a mental model and implementation pattern you can reuse in interviews, portfolio work, internal projects, or customer-facing products.
Implementation takeaways
Planner-worker flow
Decompose tasks across specialized agents.
Role-specific prompts
Define responsibilities so agents do not duplicate effort.
Shared context flow
Move information between agents without flooding everyone with noise.
Tool-routed execution
Give different agents different capabilities.
Career and project leverage
A working team-of-agents blueprint
You leave with a structure you can extend.
Framework independence
Reason across CrewAI, AutoGen, or your own orchestration.
Better decomposition judgment
Know which tasks deserve multiple roles.
Cleaner coordination patterns
Understand how context, handoffs, and review loops should work.
Who this is for
Who should join this multi-agent workshop?
The strongest SEO pages also help visitors self-qualify quickly. These personas make it obvious whether the workshop matches your current stage and goals.
AI application engineers
You want a deeper mental model than just “add more agents.”
Platform teams
You care about orchestration and tool routing.
Founders building automation products
You want to know if agent teams create real leverage.
Framework experimenters
You want concepts that outlast library trends.
Agenda
Detailed agenda: what happens in the live multi-agent session
This is a detailed live workshop, not a teaser. The timeline below shows exactly how the two-hour session is structured so you can assess whether the depth matches what you need.
When do multiple agents help?
We start by separating valid use cases from unnecessary complexity.
Planner-worker and specialist patterns
Understand the core orchestration shapes.
Role design and prompts
Define responsibilities and handoff contracts.
Shared context and memory
Move information across the team cleanly.
Tool routing
Let the right agent use the right tools.
Review and critique loops
Improve quality through structured collaboration.
Map the ideas to CrewAI and AutoGen
Translate concepts into popular frameworks.
Q&A
Ask about your own agent-team use cases.
Prerequisites
Short prerequisites, realistic expectations
You should not have to guess whether you are ready. This section keeps the bar honest and practical.
- Helpful if you understand basic agents already.
- No CrewAI or AutoGen experience required.
- No research background required.
- Best for builders who want architecture clarity.
Mid-page CTA
A fast decision checkpoint
If you want to understand when agent teams create leverage and how to orchestrate them cleanly, this workshop is built for you.
You get live delivery, recording access, code-first teaching, and a clear path to applying the material immediately after the workshop.
What is included
What you get beyond the live session
Good workshop pages do not stop at the headline. These are the assets and follow-through pieces that make the purchase feel durable rather than disposable.
Recording
Rewatch the orchestration patterns later.
Reference architecture notes
Keep the mental models for planner-worker and review loops.
Prompt templates
Use sample role structures later.
Certificate
Track completion formally.
Q&A access
Get feedback on your use case.
Why now
Why this topic deserves deliberate practice right now
A good workshop is not only about the content. It is about timing. These topics are becoming more valuable in hiring, product work, and AI engineering portfolios because they sit at the intersection of implementation skill and system judgment.
2 hours
Orchestration-focused session
₹499 / $19
Geo-aware pricing
Recording included
Review the patterns later
This extra depth is intentional. High-intent visitors searching for a serious workshop should be able to understand the outcomes, the agenda, the delivery style, and the credibility of the instructor before deciding to register. That is how this page is structured.
Instructor
Learn from Debasish Maji
Debasish Maji teaches multi-agent systems with engineering skepticism and practical depth. That combination matters because not every problem deserves multiple agents, and the builders who know the difference will win.
Why this matters
12+
Years of engineering depth across product, backend, and AI systems.
Rovo
Built Atlassian's Rovo AI Agent, bringing direct practitioner credibility.
PhonePe
Experience in high-scale engineering environments where reliability matters.
Infosys
Strong software-delivery foundation that shows up in how the material is taught.
Real agent-builder credibility
Debasish built Atlassian's Rovo AI Agent.
Systems thinking
The session emphasizes interfaces, control, and evaluation.
Framework independence
You learn ideas that outlast current libraries.
Practical teaching style
Everything is optimized for builders who want useful signal.
FAQ
Questions people ask before registering
Each answer below is also marked up as JSON-LD FAQ schema so both humans and search engines understand exactly what this page resolves.
Final CTA
Reserve your seat and learn multi-agent systems with a builder's level of clarity.
This workshop page is intentionally detailed because serious learners want substance before they buy. If the depth here matches what you were hoping to learn, the live session will be even more valuable.