Program Map — Stages, Modules, and the Path¶

The complete map of the journey. Each module links to its spec. Durations are facilitation estimates for a live session; self-serve versions run shorter.

A · AWARENESS ──▶ B · LITERACY ──▶ C · TOOLS ──▶ D · ENGINEERING ──▶ E · CLOUD ──▶ F · THE OS
   (decide)         (everyone uses)    (power use)     (build)            (own infra)    (deploy)
   Gate 1            Gate 2                              Gate 3             Gate 4

Stage A — Awareness · Decide to move¶

Primary persona: Leaders. Goal: an informed decision and a named sponsor.

M01 · AI Awareness for Leadership — 90 min. The shift, what's now possible, real ROI and real risk, and what "an AI operating system" means for a company this size. Output: go/no-go decision + executive sponsor named.
M02 · The AI Maturity Assessment — 90 min. Score the company across data, tools, skills, process, and leadership. Output: scored maturity baseline + prioritized path proposal.

Gate 1 — Committed.

Stage B — Literacy · Everyone can use it¶

Primary persona: Everyone. Goal: a competent, confident workforce.

M03 · Understanding LLMs & the Model Landscape — 90 min. (exemplar — fully built) What an LLM actually is, Claude vs. GPT vs. Gemini vs. open models, and choosing the right model for a task. Output: company model-choice cheat sheet.
M04 · Prompting & Context Engineering — 120 min. From one-line prompts to context engineering: structure, examples, system prompts, files, projects. Output: company prompt library v1.
M05 · The Claude Ecosystem (Web, Projects, Desktop) — 90 min. Claude.ai, Projects, Artifacts, and Claude Desktop set up for real work. Output: team onboarded into Claude with shared Projects.

Gate 2 — Literate.

Stage C — Tools · Power use¶

Primary persona: Operators + Builders. Goal: leverage beyond the chat box.

M06 · Claude Code (CLI) — 120 min. (exemplar — fully built) Terminal-native, agentic AI: editing files, running commands, doing real multi-step work. Output: one real company task completed in Claude Code.
M07 · Skills & Connectors (MCP) — 120 min. Skills, and connecting Claude to the company's tools and data via MCP connectors. Output: one tool or data source connected and queried.

Stage D — Engineering · Build¶

Primary persona: Builders. Goal: working automation on company data.

M08 · Building Agents & Automations — half-day. Turning repeated work into agents and automations; choosing what to automate first. Output: one automation running.
M09 · Integrating Company Data & Tools — half-day. Mapping the company's data and systems and wiring them in safely (MCP servers, APIs). Output: data/tool map + a connected source.

Gate 3 — Building.

Stage E — Cloud · Own the infrastructure¶

Primary persona: Builders (+ Leaders for policy). Goal: the company controls its own AI infra.

M10 · Setting Up Your Cloud — half-day. Cloud/VPS accounts, deployment basics, the infrastructure the OS will live on. Output: cloud account provisioned + first successful deploy.
M11 · Data Security & Sovereignty — 120 min. Keeping data on the company's own infrastructure; access control, secrets, residency. Output: signed security & data-residency policy.

Gate 4 — Ready.

Stage F — The Operating System · Deploy ◀ the destination¶

Primary persona: All. Goal: a running company OS.

M12 · Deploying Your Analytica AI OS — 4 weeks. The Analytica AI OS deployment methodology: kernel, memory, connectors, management, and the company's apps on top. Output: a running Analytica AI OS on the company's own cloud.

À la carte vs. the path¶

Any module can be sold and delivered standalone. The gates define the path to the OS; they are met by the existence of the prior stages' deliverables, not by attendance. See PROGRAM.md §5.