Applied AI for go-to-market
Build one AI-assisted campaign-to-pipeline workflow on your own or supplied data, launch it inside the permissions your team already has, and prove what it changed.
Free
12 modules
6 weeks
18 to 22 hours
What you will learn
- Choose the right model and workflow for a go-to-market task across Claude, Codex and an approved open model.
- Connect agents to business systems through MCP or approved connectors, with least privilege and human approvals.
- Build evidence-backed positioning, SEO content, ad creative, short video and a conversion asset.
- Analyze Google Ads through the official read-only MCP, and run Meta changes through supervised, authorized workflows.
- Measure workflow impact from campaign activity through to lead and pipeline evidence.
- Hand the workflow to another operator with an SOP, a permission record and an approval log.
Your instructor
Course content
Method step 1, Profile
Treat marketing, sales and revenue operations as one system, then pick the narrow part of it you will rebuild.
- Map the revenue system and pick one workflow
- Score three candidate workflows and record the baseline
- The workflow charter and baseline scorecard
Start module 1 now
Open to everyone. No account, no card, nothing to cancel.
Enroll for freeStarts Aug 12Method step 2, Build
Choose a model by task and data sensitivity rather than by brand, and write the choice down.
- Match the model to the task and the data
- Run one buyer-research task through three models
- The model comparison rubric
Method step 2, Build
Give an agent the smallest access that does the job, and keep a record of what it may touch.
- How MCP hosts, servers and scopes fit together
- Build the connector inventory and assign least privilege
- The permission worksheet and connection runbook
Method step 2, Build
Turn interviews, reviews, calls and CRM notes into a buyer picture you can defend line by line.
- Turn evidence into a defensible buyer picture
- Build the ICP and an account research brief
- The evidence brief and objection bank
Method step 2, Build
Translate buyer evidence into positioning, proof and a calendar that a team can actually run.
- From buyer evidence to positioning and proof
- Write the message house, five ad angles and a four-week calendar
- The claims checklist and brand context brief
Method step 2, Build
People-first search work, with generative-engine visibility treated as an extension of it.
- People-first SEO, and what GEO adds to it
- Audit one page and rewrite a section with first-hand evidence
- The query and entity brief
Method step 2, Build
Move from brief to art direction to a controlled variation system, with claims and rights intact.
- Creative brief, art direction and safe claims
- Produce a six-asset creative matrix across two concepts
- The ad spec sheet and rights log
Method step 2, Build
Hooks, shot lists, captions and continuity for short paid and organic video that works without sound.
- Hooks, shot lists and continuity for short video
- Cut one master vertical video and three hook variations
- The storyboard and platform export sheet
Method step 4, Measure
Connect the official read-only ads connector, query it reproducibly, and turn what it returns into reviewed recommendations.
- Connect the Google Ads MCP and read what it returns
- Diagnose one account issue and write the recommendation
- The GAQL query pack and change ticket
Method step 3, Deploy
Analysis and proposals by default, with every spend-affecting action behind a logged approval.
- Business assets, permissions and safe automation
- Analyze performance and simulate an approval-controlled change
- The change-control template and spend ceiling
Method step 3, Deploy
Build and publish the landing page, calculator or internal tool the campaign needs, with review and analytics intact.
- Lovable and Codex for landing pages and internal tools
- Build and publish one landing page or calculator
- The requirements brief and QA checklist
Method step 5, Document
Assemble everything into one governed workflow, run a bounded launch, and report what changed.
- One governed workflow, end to end
- Run the bounded pilot and present continue, change or stop
- The impact report and handoff SOP
Requirements
- One go-to-market workflow you own, and permission to change it.
- Access to your CRM, ad and content tools, or the supplied sandbox data.
- Three to four hours a week for six weeks.
- Comfort with ad and CRM concepts. The labs supply every prompt, template and rubric.
About this course
This course is for the people who run go-to-market as a system: marketing, sales, RevOps, growth and founder-led teams. It treats campaign work, selling and reporting as one measurable workflow with handoffs and shared evidence, which is the join most comparable courses leave to the learner.
Twelve modules follow the same shape. A recorded lesson teaches the durable decision, a guided lab runs it on your own or supplied material, and the module closes with one artifact another person can review, reproduce and improve.
Platform work is isolated on purpose. The business decision sits in the core lesson and the interface sits in a replaceable tool lab, so a changed screen dates one recording rather than the course. The current official Google Ads MCP is read-only, so module 9 teaches analysis and reviewed recommendations, and every spend-affecting action in module 10 runs behind a logged approval and a defined ceiling.
The capstone is a governed workflow rather than a set of prompts: a charter with a baseline, an evidence-backed message house, a creative and video set, a reproducible ads analysis, a working growth asset, a permission record and an impact report. Roan Weigert records the core lessons, and the agent loop at the centre of module 3 is the subject of his AGI Summit SF 2026 keynote, The Multimodal Agent Loop: Orchestrating AI for GTM.
Completion record
Finish Applied AI for go-to-market and your record is issued the same moment
Ticking the last lesson issues it. It arrives with your name on it, downloads as a PDF or an image, and carries a reference that anyone you send it to can check on this site.
What is printed on it
- Your name
- As it is on your account, with your photograph if you added one.
- The course
- Applied AI for go-to-market, and confirmation that all 36 lessons in it are complete.
- A reference
- Unique, permanent, and readable aloud over a phone.
- The date
- The day you finished, recorded when it happened.
Common questions
It is free. The first module of every course opens instantly, and one free account unlocks the rest of that course. Everything on this site is free to use.
A course completes when your workflow runs live and you have measured it. You record a baseline in module 1, launch the workflow into a working environment, then measure the same thing again. That pairing is what makes the completion record worth sharing.
Yes. The first module of every course plays for everyone, with a free account needed only from module 2.
Name, role, organization, and a few questions about the workflow you want to improve. It takes about a minute, and it is what lets the guided labs use your own workflow as the project.
One workflow you own, permission to change it, and the tools your team already uses. Applied AI infrastructure fundamentals also assumes a computer you can install software on, hybrid filmmaking assumes a phone or camera, and AI starter for small business runs on everyday business tools. Every course supplies sample data for the labs where your own material is restricted.
A one-page record inside the course. Before you launch, you note a baseline on time, cost, or quality. After you launch, you measure again. The sheet holds both numbers and the difference between them.
Instructor
Roan Weigert
Records all five courses
Hackathon judge and AI content creator, and host of the AI Insights San Francisco podcast. Writes this curriculum and records every core lesson.
Other courses
The other four courses
Each one takes a different kind of work through the same five steps. Pick the one closest to your job.
You buildA finished hybrid short filmHybrid filmmaking: traditional craft and applied AI
Film craft first, then controllable AI, ending in a finished short film with its production evidence.
You buildA responsible implementation packAI education, ethics and data compliance
Teaching and learning decisions first, then the policies, data rules and reviews that make them safe to adopt.
You buildA small AI service, deployedApplied AI infrastructure fundamentals
The whole picture of an AI system, taught to the depth one real deployment needs.
You buildTwo workflows in thirty daysAI starter for small business
Two safe AI workflows in daily use within thirty days, with the business result written down.
Start with module 1
Choose the revenue workflow and the metric
Open to everyone, with no account. You finish it holding a workflow charter and baseline scorecard.