ACQUIRE

Referral

Learn the customer, business, technology, AI, controls, and KPIs for referral.

Learning model: business goal → customer journey → systems/data → failure modes → AI opportunity → human control → KPIs.

Agent patterns

Referral Copilot

Copilot for Referral, using approved data and bounded actions.

Blueprint

Referral Monitor

Monitor for Referral, using approved data and bounded actions.

Blueprint

Referral Recovery Agent

Recovery Agent for Referral, using approved data and bounded actions.

Blueprint

Referral Analyst Agent

Analyst Agent for Referral, using approved data and bounded actions.

Blueprint

Referral QA & Control Agent

QA & Control Agent for Referral, using approved data and bounded actions.

Blueprint

36 prompts

/human

Referral — /human

/human Explain Referral to a fresher using a human story, then a D2C example, workflow, risks, and KPIs.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/visualize

Referral — /visualize

/visualize Visualize Referral as an end-to-end D2C flow with customer actions, systems, decisions, exceptions, and outcomes.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/diagram

Referral — /diagram

/diagram Create an architecture diagram for Referral, showing storefront, services, APIs, data, events, and human approvals.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/flowchart

Referral — /flowchart

/flowchart Create a decision flowchart for Referral, including normal path, exception path, retry, escalation, and safe stop.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/mindmap

Referral — /mindmap

/mindmap Create a mind map for Referral: customer, business, data, technology, AI, risks, KPIs, and owners.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/analysis

Referral — /analysis

/analysis Analyse Referral performance for a fictional D2C electronics business. Segment results, find root causes, quantify impact, and recommend actions.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/RCA

Referral — /RCA

/RCA Create an RCA for a failure in Referral: timeline, symptoms, hypotheses, evidence, root cause, containment, corrective action, prevention, and owner.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/BRD

Referral — /BRD

/BRD Write a detailed BRD for improving Referral: problem, users, scope, process, rules, integrations, errors, analytics, acceptance criteria, and exclusions.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/PRD

Referral — /PRD

/PRD Create a product requirements document for an AI-enabled Referral capability with user needs, UX, logic, APIs, controls, metrics, and rollout.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/userstories

Referral — /userstories

/userstories Write user stories and acceptance criteria for Referral across customer, operations, support, product, and admin personas.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/testcases

Referral — /testcases

/testcases Generate 50 test cases for Referral: happy, negative, boundary, integration, performance, security, accessibility, and business-rule cases.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/UAT

Referral — /UAT

/UAT Create a UAT plan for Referral with scenarios, preconditions, data, steps, expected result, owner, severity, and sign-off.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/API

Referral — /API

/API Design APIs for Referral: endpoints, request/response JSON, validation, idempotency, errors, auth, rate limits, and observability.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/JSON

Referral — /JSON

/JSON Create realistic JSON payload examples for Referral, including success, failure, partial, retry, and exception states.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/SQL

Referral — /SQL

/SQL Write SQL analysis questions and example queries for Referral: funnel, failures, cohorts, anomalies, SLA, and business impact.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/dashboard

Referral — /dashboard

/dashboard Design an executive and operations dashboard for Referral with metric formulas, dimensions, thresholds, alerts, owners, and decisions.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/KPI

Referral — /KPI

/KPI Define a KPI tree for Referral: north-star, leading, lagging, customer, commercial, operational, quality, and risk metrics.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/agent

Referral — /agent

/agent Design an AI agent for Referral: objective, trigger, state, tools, APIs, memory, rules, confidence, approval, audit log, KPIs, and tests.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/multiagent

Referral — /multiagent

/multiagent Design a multi-agent workflow for Referral, separating planner, specialist agents, deterministic services, and human approval.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/automation

Referral — /automation

/automation Map Referral and label every step: deterministic automation, AI assist, agent action, human approval, or human only.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/guardrails

Referral — /guardrails

/guardrails Create AI guardrails for Referral: permissions, PII, policy grounding, confidence, financial thresholds, irreversible actions, audit, and rollback.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/evaluate

Referral — /evaluate

/evaluate Create an evaluation framework for AI in Referral: accuracy, hallucination, precision/recall, latency, cost, safety, and business impact.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/monitor

Referral — /monitor

/monitor Design production monitoring for AI-enabled Referral: technical health, model quality, drift, customer harm, business metrics, and alerts.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/incident

Referral — /incident

/incident Create an incident playbook for Referral: detect, classify, contain, communicate, recover, reconcile, and learn.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/SOP

Referral — /SOP

/SOP Write an operations SOP for Referral with roles, prerequisites, normal process, exception handling, escalation matrix, and daily controls.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/checklist

Referral — /checklist

/checklist Create a launch-readiness checklist for Referral: business, UX, content, data, API, QA, security, analytics, support, and rollback.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/roadmap

Referral — /roadmap

/roadmap Create a 90-day roadmap to improve Referral: baseline, quick wins, experiments, AI opportunities, dependencies, milestones, and KPIs.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/prioritize

Referral — /prioritize

/prioritize Prioritise 15 improvement ideas for Referral using impact, effort, confidence, customer value, risk, and dependency.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/executive

Referral — /executive

/executive Create a one-page executive review for Referral: performance, customer impact, revenue impact, top risks, actions, owners, and decisions.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/interview

Referral — /interview

/interview Create 20 interview questions and model answers about Referral for ecommerce, product, and AI manager roles.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/quiz

Referral — /quiz

/quiz Create a 15-question quiz on Referral: beginner to advanced, with answers and explanations.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/project

Referral — /project

/project Create a portfolio project for Referral using fictional data: problem, dataset, analysis, AI solution, architecture, prompts, evaluation, and presentation.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/promptEvolution

Referral — /promptEvolution

/promptEvolution Improve a weak Referral prompt through beginner, structured, expert, and agent-level versions.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/sales

Referral — /sales

/sales Create five D2C sales scenarios for Referral, including intent, recommendation logic, objection, guardrail, and conversion KPI.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/cs

Referral — /cs

/cs Create five customer-service scenarios for Referral, including customer message, system checks, grounded response, escalation, and KPI.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.

/ops

Referral — /ops

/ops Create five operations scenarios for Referral, with exception, evidence, decision, owner, SLA, and preventive control.

Expected: Structured answer with assumptions, data, workflow, controls, KPIs, and actions.