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Contextual AI Stack
Casey Field Guide: AI Service Journey
Trace your service journey from first market signal through run operations, and flip between Insight (why) and Enablement (how) whenever you need perspective.
Casey is our Contextual AI Stack: field guides, frameworks, playbooks, reference architectures, and accelerators for AI-native teams building across the major clouds and the verticals we serve.
Tool, framework, and methodology picks reflect today’s benchmarks and will evolve with the market.
Signal Scan
Market Discovery & Business Analysis
LLM copilots synthesize VoC, regulatory shifts, and competitive signals into decision-ready briefs within hours.
Opportunities
- • Mine VoC, macro trends, and regulatory bulletins to spot demand swings or compliance triggers earlier.
- • Automate synthesis so discovery outputs are presentation-ready for execs.
Pitfalls
- • Hallucinated insights without source traceability.
- • Stale research pushing backlog choices out of sync with the market.
Ideas & Plays
- • Ground AI briefs in approved data feeds with citations.
- • Run lightweight scenario scoring for seasonal retail spikes vs. fintech policy shifts.
- • Save curated findings inside Casey research playcards for reuse.
Tier-1 Tools
- • AlphaSense
- • Databricks Lakehouse + Azure OpenAI
- • Tableau Pulse
Alternatives
- • Crayon
- • CB Insights
- • BloombergGPT research connectors
Methods
- • Opportunity-solution trees
- • Jobs-to-be-Done interviews with AI transcription
Casey Framework
- • Research Playcards
- • Source-of-truth prompt guardrails
Context Lens
Retail / CommerceCasey Focus
- • Research Playcards
- • Source-of-truth prompt guardrails
Prioritize
Portfolio & Agile Planning
AI backlog groomers cluster epics, surface dependencies, and run capacity simulations so priorities link to ROI.
Opportunities
- • Automate backlog clustering and dependency surfacing pre-planning.
- • Simulate capacity trade-offs with financial impact before committing.
Pitfalls
- • Auto-estimates that ignore historical velocity or compliance deadlines.
- • Optimizing purely for velocity instead of value and risk.
Ideas & Plays
- • Pair AI grooming with value-vs-risk scoring.
- • Capture decision rationale using Casey value maps.
- • Bake compliance cutoffs into prioritization prompts.
Tier-1 Tools
- • Jira Align + Atlassian Intelligence
- • Productboard AI
Alternatives
- • Dragonboat AI Planner
- • ServiceNow Strategic Portfolio Management
Methods
- • WSJF with AI dependency heatmaps
- • AI Line-of-Sight maturity workshop
Casey Framework
- • Value Maps
- • Prioritization prompt packs
Context Lens
Retail / CommerceCasey Focus
- • Value Maps
- • Prioritization prompt packs
Design
Experience & Service Design
Generative UX copilots produce personas, flows, and copy variations tied back to requirements traceability.
Opportunities
- • Generate persona variations, conversational flows, and copy tests tied to KPIs.
- • Validate concepts faster with AI-driven user research syntheses.
Pitfalls
- • Over-stylized concepts that break accessibility or legal wording.
- • Losing traceability between UX artifacts and business goals.
Ideas & Plays
- • Blend generative prototypes with rule-based UX heuristics.
- • Enforce regulated copy libraries via prompts.
- • Auto-sync approved designs back into requirement cards.
Tier-1 Tools
- • Figma AI
- • Adobe Firefly
- • Maze (AI usability tests)
Alternatives
- • Uizard
- • Galileo
- • Voiceflow AI
Methods
- • Service blueprinting with AI personas
- • Accessibility heuristic reviews with LLM critique
Casey Framework
- • Experience heuristics library
- • Regulated voice/tone prompt packs
Context Lens
Retail / CommerceCasey Focus
- • Experience heuristics library
- • Regulated voice/tone prompt packs
Architect
Solution / Application Architecture
AI-assisted patterns translate capabilities into mobile, serverless, and web stacks while maintaining guardrails.
Opportunities
- • Draft reference architectures, threat models, and API contracts across stacks.
- • Evaluate NFR trade-offs quickly with AI simulations.
Pitfalls
- • Pattern mismatch (e.g., serverless for latency-sensitive fintech).
- • Hidden infra cost from unvetted AI suggestions.
Ideas & Plays
- • Capture NFRs in prompts and templates.
- • Run AI-driven stress models against compliance/latency constraints.
- • Archive accepted patterns in Casey reference catalogs.
Tier-1 Tools
- • Lucidscale
- • AWS/Azure/GCP Well-Architected Tooling
- • Backstage + AI plugins
Alternatives
- • Structurizr DSL
- • Cortex.io context hubs
Methods
- • PASTA threat modeling
- • Domain-Driven Design with NL summaries
Casey Framework
- • Reference pattern catalog
- • Guardrail playbooks
Context Lens
Retail / CommerceCasey Focus
- • Reference pattern catalog
- • Guardrail playbooks
Intelligence Fabric
Data, BI & ML Platform
Auto lineage, feature explanations, and NL analytics keep dashboards and models trustworthy and real-time.
Opportunities
- • Auto-map lineage and recommend features for faster experimentation.
- • Expose NL BI so execs ask questions without analyst bottlenecks.
Pitfalls
- • Shadow feature creation and undocumented data movement.
- • Dashboards lacking governance approvals.
Ideas & Plays
- • Enforce data contracts and Responsible AI Navigator gates.
- • Publish “decision room” kits for real-time KPI reviews.
Tier-1 Tools
- • Snowflake Cortex
- • Databricks Unity Catalog + AI Assistant
- • dbt Semantic Layer
Alternatives
- • ThoughtSpot Sage
- • Looker + PaLM NL
- • Apache Iceberg + OpenAI
Methods
- • Data contracts
- • CRISP-DM with MLOps scorecards
Casey Framework
- • Decision room kits
- • Responsible AI checklists
Context Lens
Retail / CommerceCasey Focus
- • Decision room kits
- • Responsible AI checklists
Build
Build & Code Quality
Coding copilots, architectural linters, and NL test generation speed delivery across classic web, neo web (serverless), and mobile.
Opportunities
- • Pair coding copilots with linters to accelerate multi-stack delivery.
- • Use AI diff explainers to improve review focus.
Pitfalls
- • Secret leakage through prompts.
- • Divergent code styles or brittle ownership from over-reliance.
Ideas & Plays
- • Provide secure prompt patterns and repo policies.
- • Use AI diff summaries but keep human sign-off.
Tier-1 Tools
- • GitHub Copilot Enterprise
- • SonarQube + Clean Code AI
- • Snyk DeepCode
Alternatives
- • Codeium
- • Sourcegraph Cody
- • GuardRails.ai
Methods
- • Trunk-based development with AI diff explainers
- • Secure prompt engineering SOPs
Casey Framework
- • Engineering prompt patterns
- • Coding guardrails crib sheet
Context Lens
Retail / CommerceCasey Focus
- • Engineering prompt patterns
- • Coding guardrails crib sheet
Assure
Verification & Compliance
AI stabilizes regression suites, synthesizes edge-case data, and drafts audit-ready evidence.
Opportunities
- • Generate risk-based test plans and edge-case data quickly.
- • Draft compliance evidence packets automatically.
Pitfalls
- • AI-invented tests that never run.
- • False confidence in automated attestations without proof.
Ideas & Plays
- • Keep human oversight on critical flows.
- • Log every AI artifact with provenance.
- • Align outputs to Responsible AI Navigator checkpoints.
Tier-1 Tools
- • Tricentis Tosca AI
- • Mabl
- • Microsoft Copilot for Testing
Alternatives
- • Testim
- • Delphix synthetic data
- • Functionize
Methods
- • Risk-based testing matrices
- • Compliance evidence automation (PCI/SOX)
Casey Framework
- • Assurance ledger templates
- • Responsible AI Navigator gates
Context Lens
Retail / CommerceCasey Focus
- • Assurance ledger templates
- • Responsible AI Navigator gates
Launch
Release & DevSecOps
Predictive release scoring and IaC copilots prevent bad pushes and remediate drift across clouds.
Opportunities
- • Predict release health and auto-remediate IaC drift.
- • Run policy-as-code explainers pre go-live.
Pitfalls
- • Treating AI scores as gospel and skipping CAB/security approvals.
- • Ignoring change-freeze windows in regulated fintech.
Ideas & Plays
- • Blend AI scoring with SLO error budgets.
- • Document overrides for auditors.
- • Bake compliance calendars into deployment prompts.
Tier-1 Tools
- • Harness AIDA
- • GitHub Advanced Security + Copilot
- • GitLab Duo Deploy
Alternatives
- • Terraform Cloud Drift Detection
- • OpsLevel
- • Spacelift
Methods
- • Progressive delivery with AI scorecards
- • OPA policy-as-code
Casey Framework
- • Release playbooks
- • Compliance calendar prompts
Context Lens
Retail / CommerceCasey Focus
- • Release playbooks
- • Compliance calendar prompts
Sense & Respond
Observability & Run Ops
Telemetry copilots summarize incidents, recommend fixes, and feed updates back into Casey playbooks.
Opportunities
- • Summarize incidents and recommend fixes within minutes.
- • Push run insights back into knowledge bases.
Pitfalls
- • Alert fatigue from chatty assistants.
- • Missing forensic detail for regulators.
Ideas & Plays
- • Tune AI responders to severity tiers.
- • Auto-log summaries into Casey insight hooks.
- • Link recommendations to runbook steps.
Tier-1 Tools
- • Datadog Bits AI
- • New Relic Grok
- • PagerDuty Copilot
Alternatives
- • Grafana Cloud LLM summaries
- • Honeycomb Query Assistant
Methods
- • Incident Command System with AI augmentation
- • SLO-based error budgets
Casey Framework
- • Insight hooks
- • Telemetry story templates
Context Lens
Retail / CommerceCasey Focus
- • Insight hooks
- • Telemetry story templates
Learn & Enable
Support, Documentation & Knowledge Ops
Unified knowledge fabric powers internal/external chatbots, playbooks, and NL searchability.
Opportunities
- • Offer NL search plus chatbots for consistent answers.
- • Keep internal and external messaging aligned.
Pitfalls
- • Drift between support channels.
- • Bots hallucinating policies or outdated SOPs.
Ideas & Plays
- • Use Casey as the single publishing pipeline.
- • Trigger auto-refresh workflows when code/infra changes.
- • Provide human override on every surface.
Tier-1 Tools
- • Zendesk Advanced AI
- • Intercom Fin
- • Microsoft Copilot for Service
Alternatives
- • Guru AI Cards
- • Atlassian Confluence AI
- • ServiceNow Autopilot
Methods
- • Knowledge-Centered Service with LLM guardrails
- • Voice-of-Customer sentiment loops
Casey Framework
- • Knowledge fabric
- • Support override macros
Context Lens
Retail / CommerceCasey Focus
- • Knowledge fabric
- • Support override macros
Next step
AI Line-of-Sight Workshop
Half-day working session where we score service-journey maturity, pick two or three launches worth funding, and lock the measurement plan.
Who joins
- • Product leads / GMs
- • Engineering partners
- • Data & Analytics owners
- • Security & Compliance
What we cover
- • Phase heatmap
- • Opportunity & pitfall list
- • Tooling readiness
- • Data prerequisites
- • Evidence capture plan
Agenda snapshot
- • 90m discovery & review
- • 60m prioritization lab
- • 60m enablement roadmap
- • Optional follow-up