Language
Preparing your course and saved progress.
PATH OVERVIEW
Build an AI Business Autopilot - not a collection of disconnected workflow demos.
A product-driven path from process mapping and Python foundations to controlled AI-assisted automation, built around one evolving business operations system.
WHO THIS PATH IS FOR
What you'll build
Build a business automation system that can receive events, validate data, make bounded decisions, integrate with external tools, route uncertain cases to humans, and execute side effects through explicit safety boundaries.
The system evolves across the complete curriculum. Each published phase delivers a bounded capability; later capabilities are added only when their curricula are published.
A · Published capability
Process Mapping · Python · Testing · HTTP APIs · Webhooks · Structured AI
Turn a manual business process into a controlled automation system while building the first capability of AI Business Autopilot: process mapping, Python data flow, deterministic qualification, validation, JSON/JSONL inputs, packaging, typing, tests, outbound HTTP, inbound webhooks, integration boundaries, configuration, safe side effects, and a structured AI qualification candidate.
B · Published capability
SaaS APIs · OAuth 2.0 + PKCE · Signed Webhooks · CRM Integration · Slack · Google Calendar
Turn Intelligent Lead Intake into Connected Revenue Operations: normalize external API contracts, handle pagination and rate limits, understand OAuth 2.0 Authorization Code with PKCE, authenticate signed webhooks, integrate a CRM, Slack, and Google Calendar behind replaceable connectors, minimize data crossing system boundaries, preserve partial-failure evidence, and demonstrate one controlled multi-system revenue workflow.
PREREQUISITE EXPECTATION
No prior automation-engineering experience is required. You need a computer that can run Python and Git, basic programming familiarity, and readiness for focused implementation, testing, and debugging.
Curriculum
Automation Foundations
Turn a manual business process into a controlled automation system while building the first capability of AI Business Autopilot: process mapping, Python data flow, deterministic qualification, validation, JSON/JSONL inputs, packaging, typing, tests, outbound HTTP, inbound webhooks, integration boundaries, configuration, safe side effects, and a structured AI qualification candidate.
12 units
Free preview
A01 · Automation Foundations
A02 · Automation Foundations
A03 · Automation Foundations
Starter path
Start with three complete units from AI Engineering Foundations and use the same learning system as the full course. No account or credit card is required to begin.
Environment, terminal, Git, and the automation project shell
A01
Map the manual lead process and choose automation boundaries
A02
Python data flow and lead-event representation
A03
METHODOLOGY
TRUST & METHODOLOGY
This path maps authored curriculum skills to practical automation-engineering work. Coverage is not a job-readiness score, hiring promise, certification, or substitute for demonstrated work.
Course outcomes come from the projects, tasks, and checks learners actually complete.
Practical gates and completion are learner-controlled. Quick Checks are formative and the product does not fabricate competence claims.
Course completion is not a hiring promise, certification, rating, or substitute for demonstrated work.
ACCESS
FREE PREVIEW
The public roadmap and complete preview units from the real course.
Start freeFULL PATH
One-time access to every published unit plus progress, Quick Checks, lesson notes, and backup tools.
Choose one course or the four-course All-Access bundle.
Compare access optionsC · Published capability
PostgreSQL · Durable State · Idempotency · Transactional Outbox · Retries + Jitter · Worker Leases · Crash Recovery
Turn Connected Revenue Operations into a durable automation runtime. Persist workflow and step state in PostgreSQL, make mutating operations idempotent, commit state and outbound work atomically with an outbox, classify retryable failures, calculate bounded backoff with jitter, claim jobs safely across multiple workers, recover expired leases, resume state-machine execution after crashes, separate deadlines from retries, preserve manual-recovery evidence, and prove the system survives duplicate delivery and worker death without blindly repeating completed side effects.
D · Published capability
Function Calling · Strict Tool Schemas · Authorization Policy · Human Approval · Prompt Injection Defense · AI Evals · Shadow Mode
Add a policy-governed AI decision layer to the durable AI Business Autopilot. Define strict tool contracts, call functions through the Responses API, separate model proposals from application authorization, persist human approvals for sensitive writes, defend tool execution against prompt injection, require evidence and abstention, validate tool results and postconditions, evaluate tool selection and arguments, control model cost and latency, and prove that AI can dispatch bounded business actions without becoming an autonomous agent.
E · Published capability
Agents SDK · Bounded Autonomy · MCP · Playwright · ComputerTool · Handoffs · Agentic Evals
Turn the policy-governed AI dispatcher into a bounded multi-step operator. Build explicit agent-loop budgets and stop conditions, use the OpenAI Agents SDK without surrendering application authority, connect filtered MCP capabilities, apply approval and trust policy to MCP tools, automate a controlled browser target with Playwright and ComputerTool, preserve Phase C durability around side effects, coordinate a small number of specialists through explicit handoffs, trace every run, evaluate agentic trajectories, and prove useful multi-step autonomy without open-ended permissions.
F · Published capability
Docker · Alembic · GitHub Actions · OpenTelemetry · SLIs + SLOs · Security Hardening · Automation Control Center
Productionize the complete AI Business Autopilot. Define environment and service boundaries, build reproducible containers, manage PostgreSQL schema changes safely, enforce CI and release gates, deploy with health checks and rollback evidence, correlate workflows, agents, tools, browser actions, and integrations through OpenTelemetry, define actionable SLIs and incident runbooks, harden secrets and audit trails, expose a least-privilege Automation Control Center, and complete a production-readiness release drill without adding recruitment or job-search material.
OUTCOMES
OUTCOME 01
Grow AI Business Autopilot phase by phase from a mapped manual process into a controlled automation system.
OUTCOME 02
Build Intelligent Lead Intake with typed validation, deterministic qualification, webhooks, connector boundaries, and a structured AI candidate.
OUTCOME 03
Model automation decisions and side effects explicitly before integrating external systems.
OUTCOME 04
Test failure paths, human-review boundaries, and provider disagreement without relying on live services.
Connected Operations
Turn Intelligent Lead Intake into Connected Revenue Operations: normalize external API contracts, handle pagination and rate limits, understand OAuth 2.0 Authorization Code with PKCE, authenticate signed webhooks, integrate a CRM, Slack, and Google Calendar behind replaceable connectors, minimize data crossing system boundaries, preserve partial-failure evidence, and demonstrate one controlled multi-system revenue workflow.
10 units
Durable Workflows
Turn Connected Revenue Operations into a durable automation runtime. Persist workflow and step state in PostgreSQL, make mutating operations idempotent, commit state and outbound work atomically with an outbox, classify retryable failures, calculate bounded backoff with jitter, claim jobs safely across multiple workers, recover expired leases, resume state-machine execution after crashes, separate deadlines from retries, preserve manual-recovery evidence, and prove the system survives duplicate delivery and worker death without blindly repeating completed side effects.
10 units
AI Decisions & Tools
Add a policy-governed AI decision layer to the durable AI Business Autopilot. Define strict tool contracts, call functions through the Responses API, separate model proposals from application authorization, persist human approvals for sensitive writes, defend tool execution against prompt injection, require evidence and abstention, validate tool results and postconditions, evaluate tool selection and arguments, control model cost and latency, and prove that AI can dispatch bounded business actions without becoming an autonomous agent.
10 units
Bounded Agents
Turn the policy-governed AI dispatcher into a bounded multi-step operator. Build explicit agent-loop budgets and stop conditions, use the OpenAI Agents SDK without surrendering application authority, connect filtered MCP capabilities, apply approval and trust policy to MCP tools, automate a controlled browser target with Playwright and ComputerTool, preserve Phase C durability around side effects, coordinate a small number of specialists through explicit handoffs, trace every run, evaluate agentic trajectories, and prove useful multi-step autonomy without open-ended permissions.
10 units
Production Platform
Productionize the complete AI Business Autopilot. Define environment and service boundaries, build reproducible containers, manage PostgreSQL schema changes safely, enforce CI and release gates, deploy with health checks and rollback evidence, correlate workflows, agents, tools, browser actions, and integrations through OpenTelemetry, define actionable SLIs and incident runbooks, harden secrets and audit trails, expose a least-privilege Automation Control Center, and complete a production-readiness release drill without adding recruitment or job-search material.
10 units