Technical Foundations Track

The Technical Glossary

After this module: You'll know what every common technical term means in plain English.

Why this comes first: Every other module in this track refers to concepts defined here. Without this vocabulary, the rest of the track does not land. Read this first to absorb the language, then revisit it as a reference throughout.

Topics covered: Every technical term you will encounter in discovery calls: CRM, attribution, attribution modeling, lifecycle automation, RevOps, ETL, webhooks, APIs, technical debt, MQL, CRO, data warehouses, event tracking, CI/CD, cloud infrastructure, identity resolution, and more. For each term: what it actually is, what business problem it relates to, what good looks like versus bad, what clients typically misunderstand, and how The North approaches it.

How CRMs Actually Work

After this module: You'll understand what a CRM does, why they break, and what makes one trustworthy.

Why this comes before module 3: Attribution requires reliable CRM data as a dependency. Understanding CRMs deeply prepares you to recognize when attribution work is being proposed on top of a foundation that cannot support it.

Topics covered: How data flows into a CRM and what makes it trustworthy versus broken. Why adoption fails even when implementation succeeds. What pipeline stages actually mean in practice. Clean vs. messy data and how to assess CRM health in discovery without being technical. HubSpot vs. Salesforce vs. GoHighLevel: when to recommend each.

This builds on "The Technical Glossary" , we recommend completing that first.

What Attribution Really Means

After this module: You'll understand what attribution is, why iOS 14+ broke it for most clients, and how to explain it simply.

Why this comes before module 4: Attribution shapes the conversation about why we build the systems we build. Workflow automation often gets recommended to fix attribution problems, so understanding attribution first lets you spot when workflow is the actual answer.

Topics covered: What attribution is and why it has become harder since iOS 14+. First-touch vs. last-touch vs. multi-touch attribution. Why platform-reported ROAS is consistently misleading. What UTMs are and why discipline matters. Closed-loop attribution and how to explain the problem to a CMO in 60 seconds.

This builds on "How CRMs Actually Work" , we recommend completing that first.

Automation vs. Integration vs. Workflow

After this module: You'll be able to explain the difference between these three concepts without confusing clients.

Why this comes before module 5: These are the building blocks. Once you know what each one is and how they differ, the stack architecture conversation becomes much clearer.

Topics covered: What a trigger is, what an action is, what a workflow is. The difference between connecting two tools with an integration and automating work across many tools with a workflow. When to recommend Zapier or Make vs. n8n vs. custom code. What AI-enabled workflows actually add versus where they are buzzwords.

This builds on "What Attribution Really Means" , we recommend completing that first.

What a Tech Stack Is

After this module: You'll understand what a tech stack is, what technical debt looks like, and what questions to ask about it.

Why this comes before module 6: Understanding the stack lets you have substantive conversations with technical buyers. Without it, technical discovery questions are surface-level.

Topics covered: What a tech stack is and how it accumulates over time. How integrations work between tools. What technical debt actually means in practice and what it costs a business. What stack consolidation looks like. How to ask about a prospect's stack in discovery without sounding technical.

This builds on "Automation vs. Integration vs. Workflow" , we recommend completing that first.

How to Talk to a CTO

After this module: You'll know what a CTO cares about, fears, and what language to use with them.

Why this comes before module 7: CTOs and RevOps leads have overlapping concerns but distinct priorities. Mastering CTO conversations first builds the foundation for RevOps because much of the technical credibility carries over.

Topics covered: What a CTO actually cares about, and how it differs from a CIO. What makes them trust an external vendor versus shut them down immediately. What 'black box' means and why CTOs fear it. Handling objections about engineering an internal build. Language and phrases to use vs. avoid.

This builds on "What a Tech Stack Is" , we recommend completing that first.

How to Talk to a RevOps Lead

After this module: You'll understand what RevOps is and how to have a credible conversation with someone in that role.

Why this comes before module 8: Scenarios test your ability to navigate complex multi-stakeholder situations. Understanding RevOps specifically prepares you for those cases.

Topics covered: What RevOps is and what they own. How RevOps thinks about tooling and data quality. Why RevOps leads are often skeptical of external vendors. What evidence of operational sophistication they look for. How to make them an ally rather than a blocker.

This builds on "How to Talk to a CTO" , we recommend completing that first.

Technical Scenarios

After this module: You'll practice identifying the right technical solution in a real scenario.

Why this comes before module 9: Practical application of everything you have learned. You will recognize the dependencies, navigate the political dynamics, and make a recommendation that holds up to technical scrutiny.

Topics covered: The VC-Backed SaaS Broken Attribution scenario, applied end to end. Identifying surface ask vs. underlying dependencies. Recognizing political pressure between stakeholders. Building a sequenced recommendation. Comparing your reasoning against the model answer with full step-by-step thinking.

This builds on "How to Talk to a RevOps Lead" , we recommend completing that first.