Interactive guide
Build a CRM AI context layer
Start with an agent that gives a confident wrong answer. Add the meaning, trust rules, access controls, and tests that make its answer defensible.
You will build Your Context Layer against one CRM case. Each chapter adds or validates one part of the system, and the saved artifact stays inspectable as you move through the guide. Progress is stored in your browser.
Trace the answer back to its evidence with Priya.
Continue with Priya Shah and the Acme Manufacturing case. Help investigate what the fields mean, which sources to trust, and what the agent is allowed to use before anyone relies on its answer.
Start with a broken answer
The Context Problem
Chapter 1 of 10 · 8 min
The learning path
The same case follows the whole path: first diagnose why a plausible answer is unsupported, then add business meaning, authority, retrieval, permissions, tests, and operating controls until the answer can be traced back to evidence.
- 01The Context ProblemSee why CRM access alone produces plausible, unreliable answers.~8 min · exercise
- 02Give the Data Business MeaningAdd definitions that turn stored values into business meaning.~10 min · exercise
- 03Decide What the AI Should TrustResolve authority, freshness, provenance, and conflict.~9 min · exercise
- 04Build the Context LayerTurn the rules into a small, structured implementation.~14 min · exercise
- 05Connect It to Live DataCombine reliable tool access with business context.~12 min · exercise
- 06Control What AI Can See and DoEnforce permissions and write boundaries outside the prompt.~11 min · exercise
- 07Test the SystemTurn known failures into a regression suite.~10 min · exercise
- 08Operate ItDebug drift, stale context, and production failures.~12 min · exercise
- 09Expand Beyond the First WorkflowCarry the architecture into other systems and teams.~8 min · exercise
- 10Capstone: Trace a Reliable AnswerRun one business question through the complete system and inspect every decision.~15 min · exercise