AI layer
Models and agents
Used for classification, drafting, handoff, summarization, enrichment, qualification, and structured decision support.
- OpenAI and other LLMs
- Agent workflows
- Prompt and evaluation patterns
Tech stack = sprint components
Conversion System uses AI models, agents, automation tools, CRM workflows, analytics, and dashboards as components inside one revenue system. The stack is not the offer. The Revenue System Sprint is.
Core stack
A serious implementation usually needs multiple layers: model behavior, workflow logic, CRM fields, conversion surfaces, and reporting.
AI layer
Used for classification, drafting, handoff, summarization, enrichment, qualification, and structured decision support.
Ops layer
Used to connect forms, calendars, pipelines, tasks, notifications, lead follow-up, and sales handoff.
Proof layer
Used to show what started, what submitted, what booked, what qualified, and what moved.
How we decide
We do not start by prescribing tools. We start by identifying the gap, the available data, the operating constraint, and the metric worth moving.
Input
Revenue, budget, revenue metric, urgency, CRM, website, and lead volume determine whether the sprint is worth planning.
Build
The selected stack should be the minimum toolset needed to move one number and keep proof visible.
Guardrail
If a tool does not support the revenue metric, workflow, or measurement layer, it should not be in the sprint.
Next step
If there is a measurable revenue problem worth fixing, the Revenue Audit shows whether a Revenue System Sprint is the right next move.
Apply for a Revenue Audit