Curriculum graph

Follow the connections.

Lines show prerequisites and useful neighboring books. Move sideways for a capability, upward when more people depend on the result.

BookUseful connectionScroll inside the map to explore
Connected curriculum graphBooks arranged by track and level, joined by prerequisite and neighboring-book relationships.L01L02L03L04L05T01T02T03T09T15T04T05T06T07T08T10T14T11T12T13T01-L01What AI can and can't do for your workT01-L02Trust but verify: checking output before it leaves your deskT01-L03The simplest thing that works: chat, automation, app or agentT02-L01Getting good answers from a chatbotT02-L02Your daily driver: files, projects and memoryT02-L03A shared assistant for your teamT02-L04A self-hosted assistantT02-L05Running the assistant for everyoneT03-L01Prompting basicsT03-L02Context engineeringT03-L03Test-driven promptingT03-L04Prompts as versioned assetsT03-L05Regression sets and evaluation opsT04-L01Ask questions about your own filesT04-L02A knowledge base your team can askT04-L03Retrieval that cites and doesn't lieT04-L04Permission-aware retrieval over real systemsT04-L05Keeping a knowledge base aliveT05-L01Your first automationT05-L02Automations with AI in the middleT05-L03The pipeline that writes itselfT05-L04Making an automation safe to failT05-L05Operating automationsT06-L02A tool from a promptT06-L03An app your colleagues actually useT06-L04Real data behind itT06-L05Owning and operating your appT07-L03Your first agentT07-L04Agents with real credentialsT07-L05Many agents, and memoryT08-L02Code without being a developerT08-L03Spec-driven developmentT08-L04Working in a real repoT08-L05Agents in CI, and what they pull inT09-L01Images, voice and video for your own workT09-L02Consistent assets for your company or labT09-L03Media pipelinesT09-L04Self-hosted media modelsT09-L05Scale, provenance and rightsT10-L01Ask questions about a spreadsheetT10-L02Clean a messy exportT10-L03A reproducible analysis pipelineT10-L04Pipelines over real dataT10-L05Operating data pipelinesT11-L01A model on your own laptopT11-L02A local model your tools can callT11-L03Containers, honestlyT11-L04Your own AI serverT11-L05Serving at scaleT12-L01What you may and may not paste into AI at workT12-L02Privacy and labelling in everyday workT12-L03Rules for things that run without youT12-L04Put a lock on it: securing a self-hosted stackT12-L05Governance, evidence and handoverT13-L02Show a colleague: the 30-minute demoT13-L03Your AI usage policyT13-L04Rolling it outT13-L05Training records and AI literacyT14-L03Connect an assistant to your toolsT14-L04Build your own connectorT14-L05Operating connectorsT15-L01AI in your research workflowT15-L02Reproducibility with AI in the loopT15-L03Data, ethics and review

List fallback

Connections in plain text

Every node and relationship remains available without using the visual map.

T01Foundations & judgement3
T02Chat & assistants5
T03Prompting & context5
T09Create media5
T15AI in research3
T04Your documents & knowledge5
T05Automation5
T06Build apps4
T07Agents3
T08Write code4
T10Data & analysis5
T14Connect your tools3
T11Run your own AI5
T12Security, privacy & governance5
T13Adoption & enablement4