COURSE 001 · FDE ENGINEERING

Engineering Long-Running AI Agents

Learn how to design agents whose work survives failures, restarts, long waits and changing context.

16 modules · 5 industry cases · 14 optional labs · reference repo

Start course Introduction video coming soon View repo

Course content and API examples last verified: 2026-08 · exact dependency versions live in the reference repo lockfile

What you'll learn

  • explicit durable state, with evidence instead of claims
  • checkpoints, replay semantics, and recovery
  • replay-safe steps and what may execute twice
  • idempotent side effects and reconciliation
  • worker ownership: claims, leases, heartbeats, fencing, orphan recovery
  • failure-specific retry policies, timeouts, and honest degradation
  • durable human approval that never holds a worker
  • artifact-based context management and handoffs
  • traces, events, and an operator dashboard
  • security boundaries untrusted content cannot cross
  • trajectory evaluations and validated judges
  • a Deep Agents implementation, interrogated against your invariants
  • a deployable runtime with startup reconciliation and a runbook

Industry cases

You build one canonical system, the Vendor Review Agent, all the way through. The concepts are grounded in five industry cases along the way: incident investigation, claims and document workflows, customer operations, enterprise data, and coding agents. One app to build, five systems to understand.

Healthcare

Claims Processing Agent

A document-heavy claims workflow where policy rules, human review, and a complete audit trail are the product, and the model is the smallest part.

documentspolicyhuman review

SaaS

Customer Account Agent

An operations agent that acts on customer accounts through real APIs, where every action is a side effect someone has to approve, dedupe, or reverse.

tool permissionsside effectsidempotency

Financial Services

Enterprise Data Agent

A question-answering agent over enterprise data where the hard problems are permissions, business definitions, and proving the answers are right.

context engineeringdata permissionsSQL

Developer Tools

Repository Migration Agent

A coding agent that migrates a large codebase over many sessions, with plans, parallel workers, and verification that does not take "I finished" on faith.

coding agentsplanningrepository context

Enterprise Operations

Incident Response Agent

A production investigation agent that fans out across logs, metrics, deploys and tickets, survives partial failure, and synthesizes a defensible incident narrative.

parallel executionpartial failurelong-running agents

Course modules

Each module answers one production question. Watch or read to follow the course completely; the labs and the repo are optional depth.

Technologies used

Python

The whole reference implementation; modules 00-02 are plain Python so the loop is visible.

LangGraph

Graph execution, persistence, checkpoints and interrupts, adopted in Module 03 after the failures make them necessary.

PostgreSQL

Durable state, leases, event log, side-effect records. The load-bearing component.

Deep Agents

The higher-level harness Module 12 ports to and interrogates.

FastAPI + HTMX

The run API, review endpoints and operator dashboard, with no frontend framework.

Render + Neon

The free-tier public deployment whose restarts double as failure injection.

Why this stack, in depth →

Optional labs

14 Failure Labs break the running system on purpose: kill the worker, duplicate the publish, poison a page, race two workers. Entirely optional; the lessons describe each failure well enough to learn from without running anything.

Browse the labs

Reference implementation

The Vendor Review Agent lives in an open repo with the fixture server the labs run against. Clone it if you want your hands on the system; skip it if you are here to watch and read.

github.com/ogkranthi/air-course-long

Additional resources

Every module links one to three primary sources with a sentence on why each is worth your time. The full annotated list lives on the course sources page, and the site-wide library is at /resources.

Local progress only: your Watched/Read marks and exit-criteria checklists live in this browser, never on a server.