AI & Dev

Graph Engineering

Intermediate
Workflow Graphs Claude Code Fan-out / Fan-in Bounded Retries Verification Gates
Graph Engineering agent-hub case study

Overview

This course helps software engineers and technical leads design reliable agent workflows that branch, run independent work in parallel, and reconcile results. Participants model nodes and dependencies, define shared contracts for parallel work, and connect retries to observable verification gates. The agent-hub graph-engine protocol provides a concrete case study of contract-first fan-out, fan-in checks, and evidence-based validation.

Who Is This For

  • Software development, AI engineering, and platform teams coordinating agent-assisted work
  • Software engineers, AI engineers, platform engineers, solutions architects, and technical leads

Prerequisites

  • Working proficiency in Python or TypeScript for reading and testing development workflows
  • Experience with Git, command-line tools, and automated test runs
  • Familiarity with AI coding agents, tool calls, and sequential development workflows

Learning Path

  • Model an agent workflow as nodes, shared state, and sequential, conditional, parallel, and loop-back edges
  • Evaluate when a graph offers a useful alternative to a sequential chain
  • Design a contract-first fan-out that keeps independent agents from relying on each other's unfinished work
  • Implement fan-in checks that reconcile outputs against the contract and route mismatches for correction
  • Apply bounded retries and evidence-based gates to test workflow behavior and production readiness

By the end: You can decide when a graph is warranted and review one before using it for production development work.

What You'll Receive

  • Hands-on lab exercises and a sample code repository to keep
  • Course slides and reference guides for every module
  • Session recordings for review after class
  • Certificate of completion
  • A post-course support window for follow-up questions

Delivery Options

Online Classes

Live, interactive sessions from anywhere. Small batches for personalized attention.

1-to-1 Coaching

Personalized mentorship with flexible scheduling tailored to your goals.

Enterprise Training

Customized programs for teams, delivered online or on-site, scoped to your stack.

Learn More

Your Instructor

Taught by a practicing engineer with hands-on experience building and scaling test automation, CI/CD, and AI-assisted tooling across enterprise teams. Every session is delivered by the instructor - no recordings-only courses, no junior stand-ins - with real-world examples drawn from production projects.

Frequently Asked Questions

This course is pitched at Intermediate level - you should already be comfortable with Git, automated test runs, and AI coding agents. We can advise on readiness during a free consultation.

Both. We deliver live online classes, 1-to-1 coaching, and on-site or remote enterprise sessions for teams.

Yes. For enterprise engagements we tailor examples, exercises, and the detailed outline to your application, tools, and timeline.

Yes - a certificate of completion is provided at the end of the course.

Working proficiency in Python or TypeScript for reading and testing development workflows; Experience with Git, command-line tools, and automated test runs; Familiarity with AI coding agents, tool calls, and sequential development workflows.

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