What is this course about?
Revenue teams accumulate point tools that each charge per seat and each hold a slice of the same data. This course audits that stack, rebuilds the highest-value functions as agents grounded in your own CRM, and covers the consent and attribution work that determines whether the result is usable — including where personalization crosses into deception.
Who is this course for?
- Revenue operations leaders
- Sales enablement and marketing operations
- Demand generation and content teams
- CROs evaluating the go-to-market stack
What do I need before starting?
- Familiarity with your CRM and current martech stack
- No technical background required
What will I be able to do afterwards?
- Audit the revenue stack for overlapping capability and per-seat spend
- Build account research agents grounded in your CRM rather than a vendor's dataset
- Maintain competitive briefs without a subscription
- Identify where outreach personalization crosses into deception
- Attribute agent contribution to pipeline defensibly
What does each module cover?
What does your revenue stack actually do?
40 minThe capability audit that reveals four tools doing three things with the same data.
Objectives
- Inventory tools by capability rather than by vendor category
- Identify overlapping capability
- Compute per-seat spend across the stack
Topics
Activity. Build the capability matrix for your stack and total the per-seat spend.
How do you build account research on your own data?
50 minResearch agents grounded in your CRM history rather than a vendor's enrichment dataset.
Objectives
- Ground research in CRM history and past interactions
- Combine internal and public information appropriately
- Produce briefs a seller actually reads
Topics
Activity. Build an account research agent and test the output with three sellers.
How do you keep competitive briefs current?
45 minMaintaining competitive intelligence without a per-seat subscription.
Objectives
- Build a monitoring and update pipeline
- Verify claims before they reach a seller
- Handle competitor claims fairly and accurately
Topics
Activity. Build a competitive brief pipeline with a verification step before publication.
Where does personalization become deception?
45 minThe line between relevant and manufactured, and why crossing it damages more than it wins.
Objectives
- Identify personalization that implies false familiarity
- Set standards for what an agent may claim
- Design disclosure of automated outreach
Topics
Activity. Audit ten real outreach messages against the standard you set.
What are the consent rules when an agent sends?
45 minCAN-SPAM, GDPR, and the obligations that apply regardless of who composed the message.
Objectives
- Determine consent requirements by channel and jurisdiction
- Implement opt-out that propagates across systems
- Maintain records adequate for an inquiry
Topics
Activity. Audit your outreach process for consent and opt-out propagation gaps.
How do you produce content that is not generic?
45 minContent workflows grounded in proprietary knowledge rather than the model's priors.
Objectives
- Ground content in proprietary expertise and data
- Detect and reject generic output
- Maintain a consistent voice at volume
Topics
Activity. Produce content two ways — grounded and ungrounded — and have a customer compare.
How do you attribute agent contribution to pipeline?
45 minAttribution that survives a CRO's scrutiny rather than claiming everything it touched.
Objectives
- Design attribution that isolates agent contribution
- Build a comparison condition
- Report honestly including null results
Topics
Activity. Design an attribution study with a holdout group for one agent.
Replacing one paid tool with an owned agent
55 minThe build module: a full replacement with a measured comparison.
Objectives
- Replace one point tool with an owned agent
- Compare output quality against the incumbent
- Compute the cost difference honestly
Topics
Activity. Replace one tool and run a blind quality comparison with the team that uses it.
What is the capstone project?
Revenue stack consolidation plan with one replacement built
Audit the revenue stack for overlapping per-seat capability, build one owned agent replacing a paid tool, run a blind quality comparison, and produce a consolidation plan with honest cost and quality figures.
Deliverable: A consolidation plan plus one working agent with blind comparison results.
How are learners assessed?
- Blind quality comparison run with the team that actually uses the tool
- Consent audit findings with remediation for every gap
- Attribution design reviewed for whether it could report a null result
What ships with the course?
Facilitator guide
Session-by-session running order, discussion prompts, and the questions that reliably derail a room.
Learner workbook
Exercises, checklists, and the templates each module's activity produces.
Hands-on lab environment
A sandboxed ibl.ai deployment so exercises run against real agents, not screenshots.
Assessment bank
Scenario questions and rubric criteria mapped to each stated learning outcome.
Source bibliography
Every primary regulation and standard cited on this page, linked and dated.
Which AI agents does this course use?
The hands-on modules run against agents already deployable on the ibl.ai platform for enterprise.
Where does the course material come from?
Every module is grounded in primary sources — the regulation, standard, or research itself, not a summary of it. Each was resolved at authoring time.
- Business guidance
Federal Trade Commission
Advertising, endorsement, and AI claim guidance for Modules 4 and 6.
- General Data Protection Regulation
GDPR text
Consent and legitimate interest analysis in Module 5.
- Ideas Made to Matter
MIT Sloan
Research on go-to-market technology consolidation.
- Course structured data
Google Search Central
Reference for the content and SEO workflow material in Module 6.
Delivery notes
Binding guidance for anyone preparing and delivering this course.
- Module 4 is an ethics module in a sales course and will be resisted. Ground it in brand consequence and reply-rate data rather than moral argument, and it lands.
- The blind comparison in Module 8 must be genuinely blind and run with actual users. Teams building the replacement always rate it higher than its users do.
- Do not name and attack specific martech vendors. The audit is of capability overlap, and vendor attacks make the cost analysis look motivated.
- Module 7's attribution work should acknowledge that most marketing attribution is weak. Overclaiming rigor here undermines the credibility of the honest parts.
- Cost comparisons must include the engineering time to build and maintain the replacement. A consolidation case that ignores build cost is not a case.
Why run AI training on a platform you own?
You own the course, not a licence to it
Course content, learner data, and the platform run inside your perimeter — you own all the code and the data.
Model-agnostic delivery
Run the course's AI components on any LLM — Claude, GPT, Llama, Gemini, Command — and switch anytime.
No per-seat training licences
Usage-based or self-hosted, so cost tracks actual use rather than headcount.
Deploy anywhere
Cloud, private VPC, on-premise, or fully air-gapped — including for cohorts that cannot use public AI tools.
Frequently asked questions
What does the Sales and Marketing Agents Without the SaaS Bill course cover?
Revenue teams accumulate point tools that each charge per seat and each hold a slice of the same data. This course audits that stack, rebuilds the highest-value functions as agents grounded in your own CRM, and covers the consent and attribution work that determines whether the result is usable — including where personalization crosses into deception. It runs 5.5 hours across 8 modules across 8 modules, at intermediate level, and closes with a capstone: Revenue stack consolidation plan with one replacement built.
Who should take Sales and Marketing Agents Without the SaaS Bill?
It is written for Revenue operations leaders, Sales enablement and marketing operations, Demand generation and content teams, CROs evaluating the go-to-market stack. Prerequisites: Familiarity with your CRM and current martech stack; No technical background required.
Can we run this course on our own infrastructure?
Yes. ibl.ai is model-agnostic and deploy-anywhere — cloud, private VPC, on-premise, or fully air-gapped — and you own all the code and the data. Cohort data, submissions, and any material learners upload stay inside your perimeter, which matters for enterprise teams that cannot send work to a public AI tool.
How do we get access to Sales and Marketing Agents Without the SaaS Bill?
Request access and we will set it up for your cohort — hosted by ibl.ai, or running against your own deployment. Tell us the group size and timing you need, and whether it should run inside your own perimeter.
How much does AI training for enterprise cost on ibl.ai?
There is no per-seat pricing — you pay for usage or self-host and pay only for the infrastructure, so a 5,000-person rollout does not cost 5,000 licences. 1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.