Your map to the 7 marketing-specific AI capabilities — pick the right tool per job, extract brand voice, plan campaigns, master Generative Engine Optimization (GEO), build small automations, recognize when AI is your partner vs your trap, and measure with judgment. Orient through the chapter, see the stack-map (hub + 6 spokes), and pick a recommended starting course based on your role and current pain

Map the 8 marketing jobs onto the 4 AI tool families (chat agents, research surfaces, embedded AI, automation), learn the 4-question routing rubric, and assemble the small multi-tool stack that actually fits a marketer's week — the foundation for the rest of the chapter

Workshop the 3 operational moves of brand-voice work with AI — extract 5-7 voice rules from 3-5 sample documents, capture them as a persistent system prompt (Custom GPT, Claude Project + Skill, or Gemini Gem) so every chat starts on-voice, and recognize the 5 drift signals that say it's time to reseed before shipping

Recognize the 4 moments where AI genuinely changes campaign planning (cited audience research, message-variant generation, pre-launch red-team, pre-ship verification) and the 3 dangers where its fluency makes things worse (positioning judgment, stakeholder politics, budget trade-offs) — operational moves with a citation discipline that keeps invented buyers out of your dossier

GEO is not better SEO. Different game, different metrics. Master the 4 operational moves — JSON-LD structured data AI engines prefer, per-engine brand-mention saturation (ChatGPT, Perplexity, AI Overviews each cite from different sources), citation-worthy content formatting (the opening 200 words rule + 5 more), and the hybrid SEO/GEO playbook — plus how to measure visibility with Otterly / Profound

Build 3 small marketing tools end-to-end with an AI coding agent (Claude Code as worked example; Cursor / Codex / Gemini CLI as escape hatches) — a competitor blog tracker from RSS feeds, a campaign data analyzer that turns HubSpot CSV exports into AI-narrated insights, and a content calendar generator that produces voice-matched multi-channel calendars. With the personal-stays-personal discipline that keeps these tools from becoming accidental products

The meta-skill that outlasts every tool churn — AI is useful for thinking, dangerous for deciding. 4 marketing cases (AI buyer personas, market sizing, competitive analysis, campaign ROI prediction) plus a 2-question decision rule (generate or adjudicate? if wrong, reversible or not?) that applies to any AI tool — including ones that don't exist yet

The chapter's analytical close — use AI to interpret analytics faster (compute outside AI, narrate with AI), design tighter A/B tests (hypothesis crispness + sample-size sanity + when to use multi-arm bandits), and recognize the 3 overclaim patterns AI is prone to (confounded variables, cherry-picked windows, vanity metrics) that turn fluent dashboards into bad decisions

Your orientation to creative AI foundations — landscape, inputs, collaboration, rights, and compound systems

Collaboration patterns that make human-AI creative work better than either alone

Build a creative asset system that compounds — every project makes the next one faster and better

Navigate ownership, Content Credentials, and the C2PA standard for AI-generated creative work

A clear-eyed map of AI creative tools in 2026 — what works, what is hype, and how to think about a stack that changes every quarter

How to prepare the inputs that determine whether AI creative tools produce magic or mediocrity — structured briefs, curated references, and living moodboards

Master the combinatorial challenge of managing creative assets across the full matrix of variants, sizes, formats, and languages at production scale.

The mental map for running studio-grade AI creative production -- from designing the factory to governing what it ships.

Design the system that turns one idea into platform-native content across every channel -- without duplicating effort or diluting quality.

Ensure everything your AI creative pipeline produces meets quality, brand, and safety standards before it reaches audiences.

Maintain genuine narrative quality and emotional resonance when producing content at volume with AI creative systems.

Use AI for presentation design that starts with narrative structure and audience needs -- not clip art on steroids.

Architect the concept-to-delivery pipeline that turns AI-assisted creative ops from ad-hoc experiments into repeatable studio-grade production.

Turn a single approved image into a complete multi-format, multi-channel asset library using AI-powered adaptation, outpainting, and batch generation workflows.

Turn brand briefs into production-ready campaign visuals using AI image generators — hero images, social assets, and ad creative at the speed of thought.

A practitioner's map of the Images with AI skill path — from your first marketing visual to a production asset pipeline.

Generate studio-quality product shots, lifestyle scenes, and packaging mockups without a physical studio — master the tools and workflows that turn a single product photo into an entire e-commerce vis

Make AI image generators produce illustration that looks like YOUR brand, not generic AI art.

Transform existing photographs with AI-powered removal, replacement, enhancement, and correction — the other half of the creative workflow.

Use AI image generation to create narrative-driven visuals that support articles, reports, and content series with emotional coherence and editorial intent.

The post-production layer — text-based editing, auto-captioning, multi-platform export, and localization workflows that turn one video into 10 variants

From static frames to motion previews — the AI-accelerated pre-production workflow that tests ideas before you commit budget

The audio layer of AI video production — voiceover, music, and sound effects that don't sound like a robot made them

What AI video tools exist, how they work, what they cost, and where each wins

From concept to 30 variants in a day — the production workflow that turns AI video tools into a repeatable social content engine

The production map — from landscape to post-production, what you'll master and how the six chapters connect

Script-to-video workflows, avatar presenters, screen recording enhancement, and the quality bar for when AI-generated is good enough

A 10-minute orientation across the five-chapter beginner path — what agents are, how they work, where you already use them, when they fail, and how to work alongside them

The mental model shift from AI that answers questions to AI that does work — explained through everyday workplace scenarios, no code required

The three ingredients that turn a chatbot into an agent — tools it can use, memory it can draw on, and goals it can pursue — explained through workplace analogies

A tour of AI agents you probably already encounter at work — Microsoft Copilot, customer service bots, scheduling assistants, and more — with the exact moment each one stops being a chatbot

An honest look at agent limitations — hallucination chains, confident mistakes, and loops — framed as normal challenges with practical responses, not reasons to panic

Practical guidance for working with AI agents daily — writing good instructions, knowing when to intervene, reviewing output, and building your personal agent playbook

Six PM moments where AI accelerates your work — and three where it doesn't

From vague idea to eng-ready spec with AI

Turn interview transcripts into actionable insights

Monitor competitors and synthesize market intelligence with AI

Narrative roadmaps and updates that land with every audience

Design experiments and read results without falling into statistical traps

Build PM tools without writing code — using AI agents

Orientation across the AI for Sales stack — why AI is rewriting EVERY stage of the funnel in 2026, the seven-course map (five funnel-stage courses run linearly: prospecting → outreach → call prep → forecasting → proposals; plus two satellites — Coding-Lite for Sales and Microsoft Copilot for Sales — that cross-cut the funnel), the leverage map separating where AI is decisive (research speed, draft scaffolding, signal ranking, summarization) from where the human stays decisive (judgment, trust-building, accountability, verification), the concrete capabilities at stack end, and the pick-by-pain table that picks your starting course (default: sales-prospecting)

Bridge from knowledge-worker AI use to AI engineering for sales — reframe the "I'm not a developer" mental block (the new floor: reps who can ship a small custom tool are 10× more leveraged than reps who can't), install a coding agent once (Claude Code as the worked example with explicit escape hatch to Cursor / Codex CLI / Gemini CLI), learn the describe-codes-run-fix loop, ship three running mini-projects in your actual workflow (pipeline report extending sales-pipeline-forecasting, custom lead score extending sales-prospecting, outreach personalizer extending sales-outreach-scale Tier 2) with the EXACT reproducible prompts, recognize when NOT to use a coding agent (native CRM/Apollo feature exists, data too sensitive, silently-wrong-numbers in a board deck), and walk away with a coding-lite system — folder structure, three running tools, weekly cadence

A 12-minute orientation across the six-chapter BA skill path — from requirements elicitation to enterprise governance, the complete Copilot toolkit for advanced business analysis

Turn messy stakeholder inputs into structured BRDs, user stories, and acceptance criteria using M365 Copilot in Word, Loop, and Teams — with enterprise-scale context priming.

Use M365 Copilot in Visio, Whiteboard, and Excel to accelerate process documentation, build as-is/to-be comparison matrices, and surface cross-departmental inefficiencies.

Translate technical BA findings into audience-adapted communications using PowerPoint, Outlook, Loop, and Teams — managing competing interests and preserving precision across enterprise stakeholder levels.

Use Excel Copilot, Python in Excel, and Power BI Copilot to pivot, clean, analyze, and visualize enterprise data exports — building stakeholder-ready insights from messy CSVs without writing SQL or Python manually.

Trace how proposed changes ripple through systems, teams, and processes — building impact matrices, risk registers, and readiness assessments that synthesize technical and organizational dependencies for complex enterprise change programs.

Navigate sensitivity labels, DLP policies, data residency constraints, and audit requirements to remain productive with Copilot inside heavily regulated enterprise environments — from financial services Chinese walls to cross-border data boundaries.

A 12-minute orientation across the five-app M365 Copilot deep-dive set — Outlook, Word, Excel, PowerPoint, Teams. One grammar (Agent Mode + License/Graph/Labels + verify-before-trust); five surfaces; no required order. Pick the app where your day actually lives

From 47 emails to 5 minutes — agent-mode triage, thread summarization that doesn't lose detail, on-brand drafting, natural-language rules, and the verification habits that keep Copilot honest in your inbox starting Tuesday morning

From blank page to polished doc with Agent Mode (default since April 22, 2026) — prompt-first drafting grounded in your files, brand-voice rewrites that don't sound like a robot, long-form structure that survives partial regeneration, and the four-check verification that keeps Copilot honest in your memos and proposals starting Tuesday morning

From a 2,000-row export to a board-ready answer in 15 minutes — Agent Mode (default since April 22, 2026), the brand-new =COPILOT() cell function, Python in Excel via natural-language prompts, the seven reliable data cleanups, and the four-check verification habits that keep your numbers honest in spreadsheets starting Tuesday morning

From a 9am brief to a 4pm board deck — Agent Mode (default since April 22, 2026), the Brand Kit + Template combo that fixes the 'why do my Copilot slides look generic' problem, exact-hex-and-template-name prompts, per-slide refinement that doesn't cascade, and the four-check verification habit that keeps your deck on-brand starting Tuesday morning

From eight hours of meetings to five minutes of catch-up — real-time mid-meeting questions, time-bounded prompts, action items with real owners (not fabricated), the Microsoft Tech Community v1.5 prompt for high-fidelity meeting analysis, and the four-check verification habit that keeps Copilot honest in your meetings starting Tuesday morning

A 12-minute orientation across the five-chapter Daily AI Toolkit — name the four AI tool families that the foundation chapter teaches, see how the three daily-surface chapters (docs/decks, email/meetings, research) apply that framework, recognize the ecosystem-routing chapter as the meta-decision overlay, and pick the right starting chapter based on which surface is biting hardest

Map the four AI tool families, build a default stack of three or four tools that fits your week, and learn the meta-skill of evaluating any new tool that lands

From a pile of messy inputs to a polished document and a stakeholder-ready deck — one repeatable 4-step pattern, executed across M365, Workspace, or hybrid stacks

Triage your inbox in minutes, capture meetings cleanly with the right notetaker, and run the post-meeting chain (transcript → summary → actions → per-person follow-up) so nothing falls out — with the privacy and consent layer that keeps it professional

Replace 12 browser tabs with cited answers in minutes — name the four research surfaces, brief deep-research runs that compress 4 hours of manual work into 25 minutes of yours, decide when a browser agent earns the click delegation, and apply the 3-source rule that keeps fabricated facts out of your work

Diagnose whether you are M365-native, Workspace-native, or hybrid — then route every AI task with rules that fit the ecosystem you actually live in, and know when to leave Chapter 2.1 for the deep dives (Copilot Mastery, future Workspace AI, AI Coding for Beginners)

An orientation across the marketing ladder — brand voice into content, SEO audits, multi-channel campaigns, and agency mode at scale.

Drive /draft-content against your brand voice — generate blog posts, social variants, email, and landing copy that pass /brand-review on the first cut.

Run /seo-audit end-to-end — produce a site audit, expand keyword strategy, and ship SEO-optimized long-form content with H1, meta, FAQ, and internal-link maps.

Plan multi-channel campaigns with /campaign-plan and /email-sequence — objectives, channel mix, content calendars, success metrics, and full nurture flows in one session.

Run a digital agency on Cowork — per-client brand-voice Projects, scheduled monthly performance reports as Live Artifacts, and a private plugin marketplace that distributes house style.

Orientation across the five-chapter beginner path — why 2026 is the inflection point, why your soft skills are the moat, why you don't have to wait for technical specialists, what real companies are actually doing, and what to do this week

Why 2026 is the year AI quietly stopped being a side project for technical teams and became a daily tool for everyone else — and what doing nothing now actually costs

Judgment, communication, taste, domain expertise — the soft skills you've spent your career building are the moat. Walk through each one with concrete examples of it in action with AI

AI closes the gap between non-tech workers and the specialists you used to depend on — data analysts, designers, translators, legal reviewers. Concrete moves you can make without becoming a developer

Six to eight named companies, public numbers, and role-level stories — what Klarna, Shopify, Anthropic itself, and a marketer, salesperson, HR partner, and finance analyst actually did with AI in 2025–26

Pick one tool, three tasks, and a 4-question filter for when AI is the right call — the concrete plan you can start Monday morning, and the explicit handoff to AI Foundations as the next path