Ship Your Multi-Agent System Build, Orchestate and Evaluate

A fast, practical **2-hour free masterclass** on designing, orchestrating, and **shipping a production-ready multi-agent system with CrewAI**. Build the core blueprint, learn the patterns, and leave with templates you can deploy. \# What you’ll learn * **Architecture:** Roles, tools, memory, routing, retries, and guardrails for agent teams. * **Orchestration with CrewAI:** Tasks, handoffs, planning vs. execution loops, evaluation hooks. * **Shipping mindset:** From notebook to users—logging, simple CI, and lightweight deployment options. * **Quality & safety:** Prompt hygiene, testable behaviors, evals that catch regressions. * **Blueprint & templates:** A starter repo and checklists you can adapt to your use case. \# Who should attend * Data scientists, ML/LLM engineers, builders, product hackers. * Technical founders exploring agentic apps for real users. * Teams evaluating CrewAI for internal tools or external products. \# Live Agenda \(120 minutes\) 1. **Foundations (15 min):** Agent vs. tool vs. planner, when to use multi-agent patterns. 2. **Design (25 min):** Defining roles, capabilities, and the task graph; failure modes and recovery. 3. **Build (30 min):** CrewAI walkthrough—agents, tasks, memory, tools, evaluators; run a demo crew. 4. **Ship (20 min):** Packaging, environment variables, secrets, logs, simple deployment paths. 5. **Quality (15 min):** Evals, prompts-as-contracts, measurable outcomes. 6. **Challenge Q&A (15 min):** Your use cases, blockers, and next steps. 7. **Pathway (10 min):** How this masterclass feeds into the **AI Residency** for deeper practice. \# Outcomes * A **working multi-agent blueprint** you can adapt after the session. * **Copy-paste templates** for roles, tasks, tools, and evals. * A clear **checklist for production-readiness** (observability, tests, fallbacks). * Direction on scaling your project via the **AI Residency**. \# Prerequisites * Basic Python familiarity. * Laptop with a browser; **Google Colab** or local environment works. * Optional: an LLM API key to run the full demo. \# Speaker **Mohammad Arshad** — Founder, Decoding Data Science; Principal Data Scientist. Leads AI strategy, education, and community initiatives across the region. \# Logistics * **Date:** 25th Oct, Saturday * **Time:** 11:00 AM GST · 12:30 PM IST · 07:30 AM UTC * **Format:** Live online, interactive Q&A * **Cost:** Free \# FAQ * **Will the recording be shared?** Y**Will the recording be shared?** No—recording will not be provided. * **Will code and slides be provided?** Yes, templates and resources will be shared. * **Is this beginner-friendly?** Yes—focused on practical patterns; advanced tips included. * **Is this a sales session?** No. It’s hands-on and outcome-driven. We will briefly outline the AI Residency for those who want to go deeper. Part of AI Residency [https://academy.decodingdatascience.com/airesidencyfasttrack](https://academy.decodingdatascience.com/airesidencyfasttrack)