FDE Playbook on Complex AI Automations: Production Multi-Crew Systems
Denis Vasiliev
AI Infrastructure Engineer and Universit
Go beyond multi-agent. Ship deterministic, production-ready agent networks.
Most tutorials teach simple multi-agent loops that break under production traffic. This workshop teaches you to ship deterministic, production-ready agent networks.
Go beyond basic multi-agent systems. You will learn to build multi-crew architectures where specialized teams of AI agents are integrated with non-AI components — reducing unnecessary LLM calls and token consumption while giving you greater control, reliability, and observability.
What You Will Master:
Hybrid Engineering: Split workflows into pure Python for deterministic tasks (DB queries/calculations) and multi-crew networks only for abstract reasoning, cutting token costs by up to 60%.
Enterprise Infrastructure: Prevent API timeouts by decoupling ingestion with Django REST Framework, orchestrating async workers with Prefect, and containerizing with Docker Compose.
Type-Safety & Evaluation: Enforce data integrity with Pydantic validation boundaries and evaluate multi-turn trajectories using Maxim AI.
The Tangible Outcome:
You will leave with a fully functional, containerized multi-crew repository that you can immediately deploy inside your company. Stop building AI toys. Start engineering resilient enterprise software.
What you’ll learn
Transform from an AI developer writing experimental agent scripts into an architect engineering production-ready, hybrid multi-crew systems.
Merge agent crews with non-AI components
Define explicit agent role boundaries
Balance reasoning with static logic
Build robust background task workflows
Implement conditional system routing
Track state across pipeline steps
Apply Pydantic type safety layers
Sanitize volatile input payloads
Guarantee predictable JSON outputs
Trace multi-turn paths with Maxim AI
Catch agent reasoning deadlocks early
Run full production simulations
Enforce system-level circuit breakers
Deploy smart step-level state caching
Isolate free Python from costly LLMs
Containerize API and database layers
Link Prefect orchestrators with Crews
Manage the stack with Docker Compose
Workshop agenda
The Multi-Crew Paradigm & Data Integrity
Establish role boundaries across specialized agent crews. Implement strict Pydantic schemas to validate input data and ensure predictable, type-safe JSON outputs from volatile LLMs.
Decoupled API Ingestion & Worker Setup
Code an asynchronous API ingestion gate to instantly accept payloads. Learn to eliminate gateway timeouts by offloading heavy, multi-minute reasoning loops directly to background workers.
Prefect Automation & Cost Protection
Configure Prefect tasks to isolate zero-token operations from LLM loops. Wire up system circuit breakers to freeze runaway token consumption and apply caching to prevent redundant API calls.
Maxim AI Tracing & Docker Compose
Connect Maxim AI to track agent trajectories and intercept reasoning deadlocks. Package the entire multi-service backend into Docker Compose for a portable, push-button deployment asset.
Learn directly from Denis
Denis Vasiliev
Agentic Practitioner, Freelance AI Engineer, univeristy educator
Who this workshop is for
Aspiring Forward Deployed AI Engineers (FDEs) wanting to master the battle-tested, full-stack deployment patterns enterprise clients demand.
AI Tech Leads & Architects needing to move past fragile single-agent scripts into robust, deterministic multi-crew backend infrastructure.
Backend & Data Engineers who want to cleanly wrap non-deterministic multi-agent networks into containerized Python & Prefect data pipelines.
Prerequisites
Required Technical Background
Ability to code. Python is preferred, but comfort with async loops, objects, and basic JSON structures is acceptable.
Core Environment & Local Tools
Local installation of Python 3.10–3.12, the uv package manager, Docker Desktop with Docker Compose running, and VS Code.
Compilation Fixes (Windows & Mac)
Windows: Visual Studio C++ Build Tools installed. macOS: Working Rust compilation toolchain active (prevents crew package errors).
What's included
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Shippable Production Repo Template
Get full source access to our workshop blueprint. A ready-to-use, production-grade template containing the Django, Prefect, Pydantic, and CrewAI boilerplate code.
Production Docker Compose Blueprint
Receive a pre-configured multi-container infrastructure blueprint. Spin up your full API gateway, database, background workers, and multi-crew networks locally with one command.
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Free resource
Beyond Multi-Agent: Designing Production-Ready Multi-Crew AI Systems
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