CRAFT

Cardinality Rapid AI-First Toolchain · Contract to Customer Outcomes
Built on the Cardy AIDLC method
Build and Lead with AI.
Govern with Human Judgment.

Welcome to CRAFT

Cardinality Rapid AI-First Toolchain — Contract to Customer Outcomes. Our AI-native delivery toolchain for Cardy product development and implementation, built on the Cardy AIDLC method. This portal is the orientation guide. Read what is relevant to your role — the Your Role tab personalizes the view — and the path forward will be clear.

What it is

A method, not a tool

Claude Enterprise is the tool. AIDLC is the method that turns Claude usage into consistent delivery quality: skills, context, HITL gates, evals. Same tool, multiplied by structure.

Who it's for

All 300+ of us

BAs, Architects, Developers, QA, DevOps, PMs, Configuration Specialists, Empower Product engineers, onsite and offshore. Different skill packs per persona, same methodology.

Data scope

De-identified working artifacts

Engagements are real. The working artifacts in CRAFT are de-identified per policy. No real PHI, FTI, CJI, or client production data ever enters Claude.

How to use this portal

Tab For you if you…
Claude 101 Want a quick refresher on what Claude, Claude Code, MCP, skills, context, plugins actually are and when to use each.
Methodology Want to understand the 12 stages, 6 buckets, 3 tiers, and HITL gates.
Think The architect's view: what is a skill vs context vs connector, the decision tree, and how to author skills well. Read before proposing your first skill.
Guardrails Want the security, IP, data, and skill-governance rules of the road. Required reading before you start.
Your Role Want the persona-specific view: your skill pack, your daily flow, when you get access.
Pilot The real pilot engagement, end-to-end. Recommended for everyone.
Timeline Placeholder dates. Want to know when your role gets access and what to do beforehand.
FAQ Want the answer to the question you're afraid to ask in the all-hands.
Resources Want the links — strategy doc, skill catalog, Slack channels, CoE contact.
Why Visual gut-check on the case for CRAFT. Share-able battlefield analogy.
If you read one tab, read this one: the Pilot tab. It walks through our live San Diego engagement from RFP ingest to first shipped PR, showing exactly what each persona does at each step. Everything else in this portal makes more sense once you've read that.

Claude 101 — A Cheat Sheet

New to Claude? Start here. Already familiar? This is the shared vocabulary we'll use across the org.

The terms, in plain language

Claude (the model)
The AI itself. We use Anthropic's claude-sonnet-4-6 and claude-opus-4-6 by default. Sonnet for everyday work; Opus for hard problems (design, code, code review).
Claude.ai
The web/desktop chat interface. Where BAs, Architects, PMs do most of their AIDLC work. Has Projects, Skills, and Connectors built in.
Claude Code
A CLI / IDE-integrated version of Claude that lives in your terminal or VS Code. Sees the local repo. Runs commands. This is where developers spend most of their AIDLC time.
Project
A scoped workspace in Claude with its own knowledge files and instructions. We use Projects to implement our 3-tier context model: one Project per implementation (Tier 2), one shared Project for platform standards (Tier 1).
Context
The information loaded into a conversation: project knowledge (attached documents), system prompts, the messages so far. AIDLC's job is to make sure the right context is loaded for the right task — without you having to wrangle it manually.
Skill
A reusable, versioned playbook for one job. Example: prs-generator is a skill that turns an RFP into a PRS. Skills are invoked like slash-commands in Claude. They live in a git repo and the CoE governs them.
Plugin pack
A bundle of skills shipped together. Cardy AIDLC has 6 plugin packs: cardy-platform-base, cardy-pmo-pack, cardy-arch-pack, cardy-dev-pack, cardy-qa-pack, cardy-release-pack.
MCP (Model Context Protocol)
The open protocol that lets Claude talk to external tools and data sources. Each connector (Jira, Bitbucket, Slack, Gmail, Google Drive) is an MCP server. When you wire Jira to Claude, you're using MCP.
Connector
An MCP-based bridge to a specific tool. In AIDLC we use 5 connectors: Google Drive, Jira, Bitbucket, Slack, Gmail. Scoped per project; SSO-authenticated; audit-logged.
HITL gate
Human-In-The-Loop gate. A required human approval between two AIDLC stages. Example: BA Lead approves the PRS before fit-gap begins. Encoded in Jira workflow, not goodwill.
Eval
A measurable quality check. Each AIDLC skill has a rubric and a golden set of 20–50 example inputs. Skills are scored before they can ship.
Tier 1 / 2 / 3
The knowledge architecture. Tier 1 = org-level (Empower platform, coding guidelines, HHS domain). Tier 2 = per implementation (RFP, contract, configuration). Tier 3 = your daily working memory.

When to use which surface

I want to… Use Why
Read an RFP and draft a PRS Claude.ai (Cowork mode for long-form) Drive connector + project knowledge make this trivial. Long file generation.
Run a fit-gap on classified requirements Claude.ai Reasoning + structured output back into Drive.
Draft stories with AC in Jira Claude.ai or directly in Jira (@claude) Either works. In Jira is faster when you have one story.
Write code, run tests, open a PR Claude Code Lives in your editor. Sees the actual repo. Runs commands.
Review a PR against Empower standards Claude.ai with GitHub/Bitbucket connector Posts inline comments; humans approve.
Quick lookup, summarization, classification Claude.ai (Haiku model) Cheap, fast, deterministic enough.

What a typical CRAFT interaction looks like

You open Claude.ai. You switch to the right Project (e.g., "San Diego Implementation"). The Project loads the RFP, response, config decisions automatically as context. You invoke a skill — type /prs-generator or @claude draft AC for this story. Claude pulls from Tier 1 (platform standards) + Tier 2 (this project) and produces the artifact. You review, edit, accept. The system of record (Jira / Drive / Bitbucket) gets updated. Nothing new to learn beyond the slash-commands.

The mental model: Claude is a teammate who knows the standards and remembers the project. CRAFT is the team's toolchain; the Cardy AIDLC method is the team's playbook. The HITL gates are the team's quality control. You're still the senior person on every artifact.

The AIDLC Methodology

12 stages. 6 buckets. 3 tiers. A human approver at every gate. Synthetic data only. That's the whole methodology.

The 12 stages

Stages 1–3 are linear. After classification, work fans out into 6 parallel sub-pipelines — one per bucket. Stages 4–12 are bucket-aware.

STAGE 1 Pre-Sales Ingest RFP · response · outcomes STAGE 2 Detailed PRS flows · UML · AC STAGE 3 Fit-Gap & Classification → 6 buckets HITL gate between every stage Bucket 1 OOTB Empower config Bucket 2 Platform / Product Empower core work Bucket 3 Client Extension State-specific work Bucket 4 Integration External contracts Bucket 5 Data Migration Legacy → Empower Bucket 6 Analytics & BA Dashboards · BI For each bucket, in parallel: STAGE 4 High-Level Design + ER + Data Model STAGE 5 Story Decomposition (into Jira) STAGE 6 Estimation (per bucket) STAGE 7 Low-Level Design (per story) STAGE 8 Test Cases (all layers) STAGE 9 Development (Claude Code, bucket-aware) STAGE 10 Code Review STAGE 11 Test Execution STAGE 12 Ship · Release Notes · Hypercare PARALLEL TRACK · Contract Deliverables Planning System Security Plan · Infrastructure Plan · OCM · Training · Transition — AIDLC produces planning artifacts; humans author final docs. CONTINUOUS · Evals, drift monitoring, production sampling (5%), promotion gates Skills graduate to GA only after passing rubric thresholds. Model and prompt changes are gated.

The 6 buckets

Every requirement, after fit-gap, lives in exactly one bucket. Buckets matter because they have different estimation rhythms, approvers, and skill clusters.

Bucket What lives here Owns it Approves it
OOTB Configuration Workflow, page builder, rules engine configuration on existing Empower Configuration Specialist Empower Config Lead
Platform / Product Feature New capability we'd want in Empower itself Platform / Product Engineer Empower Product Architect
Client Extension Client-specific customization that doesn't belong in the platform Extension Developer Implementation Tech Lead
Integration External-system contracts: county, court, EHR, etc. Integration Engineer Integration Lead
Data Migration Legacy → Empower data migration: mapping, transformation, validation, cutover Data Engineer Data Lead
Analytics & BA Dashboards, BI layer, operational reporting, data marts Report Developer BA Lead

The 3-tier knowledge model

Tier Scope Owner What's in it
Tier 1 Org-level Empower Product + CoE Empower architecture, RBAC, workflow patterns, coding guidelines, HHS domain primer
Tier 2 Per implementation Implementation Squad + CoE RFP/response, contract, config decisions, extensions, integration specs, migration maps
Tier 3 Transaction You Current sprint, today's PR, your scratch notes

HITL gates — non-negotiable

Synthetic only. No real PHI, FTI, CJI, or client production data enters Claude. AIDLC works on contracts (de-identified), design, code, configuration, synthetic personas, synthetic test data.

How to Think — A Senior Architect's View

The single most-confused boundary in any Claude rollout: what is a skill, what is context, what is a connector? Get it wrong and you ship 200 "skills" that are really FAQ entries. Get it right and the library compounds in quality every quarter. Read this before you propose your first skill.

The one rule
Context is what the model knows. Skill is what the model does. Connector is what the model can touch. Project is where the work happens.

1. The five primitives

Primitive What it is Answers Lives where
Model The LLM (Opus, Sonnet, Haiku) Who is doing the thinking? Anthropic's API; selected per call
Context Reference material the model reads to ground answers What does the model need to know? Project knowledge; attached files; connector-retrieved docs
Skill A versioned procedure to do a specific job repeatedly How does the model do this job? Markdown playbook in cardy/aidlc-skills repo
Project A scoped workspace: context + connectors + model + access Where does the work happen? Claude.ai Projects
Connector (MCP) A live integration to an external system What can the model touch? MCP server (Jira, Drive, Bitbucket, Slack, Gmail)

2. The 5-test — is X actually a skill?

A capability deserves to be a skill only if it passes all five. Fail any one and it's something else: context, FAQ, prompt template, or a connector call.

1
Recurrence
Is this job done repeatedly across projects/clients?
2
Procedure (not knowledge)
Is there a defined procedure to follow, distinct from "use this template"?
3
Specific output shape
Does the output have a defined structure that downstream stages depend on?
4
Eval-able quality bar
Can we write a rubric and a golden set that scores whether the job was done well?
5
Worth versioning
Will the prompt and output shape evolve? Will we want to roll back changes?

Worked example: is rfp-ingest a skill?

TestVerdict
RecurrenceYes — every new engagement starts with one.
Procedure (not knowledge)Yes — read RFP, extract outcomes/requirements/NFRs/deliverables, classify into preliminary buckets, cite page numbers, produce a .docx brief.
Specific output shapeYes — downstream Stage 2 (PRS) and PMO depend on the brief's structure.
Eval-able quality barYes — coverage of outcomes, accuracy of citations, classification confidence calibration.
Worth versioningYes — RFP styles vary by state/county; skill will sharpen with feedback.
VERDICT: passes all 5 → it IS a skill.

Counter-examples — what is NOT a skill

3. Decision tree — when you're not sure

Walk through this whenever someone says "let's make a skill for X":
  1. Is X done repeatedly across engagements? No → it's a one-off, just prompt it. Yes → continue.
  2. Does X produce a defined artifact others depend on? No → private workflow, not a skill yet. Yes → continue.
  3. What grounding material does X need? Universal → Tier 1 context. Per-engagement → Tier 2 context. (Skills reference context, never embed it.)
  4. Can quality be scored? No → ship experimental, can't graduate to GA without evals. Yes → write the golden set and rubric alongside the skill.
  5. Should the prompt + output shape evolve? No → it's a template, drop an .md in a shared folder. Yes → make it a versioned skill, CoE-reviewed PRs.

4. Skill anatomy — the 8 sections of a well-formed skill

SectionWhat goes here
1. Frontmatter (YAML)name, version, pack, stage, bucket, persona, triggers, HITL gate, inputs, outputs, context tiers, model routing
2. PurposeOne paragraph: what this skill is FOR (not what it does step-by-step)
3. PreamblePrompt-injection defense boilerplate — required, do not remove
4. StepsThe procedure, numbered, specific, with citation rules
5. Output formatExact shape: headings, fields, file extension, file naming convention
6. GuardrailsData scope, what NOT to do, when to flag for human
7. Eval rubric summaryScored dimensions + link to full rubric in evals/
8. Example invocations3 realistic prompts users would type
The skill is the procedure. It does NOT contain the RFP. It does NOT contain the Empower standards. Those live in context. The skill references context and produces a specified output. That's it.

5. Placement rules — what goes where

AssetWhereWhy
Empower architecture overviewTier 1 project knowledgeStable, org-wide, many skills reference it
Coding guidelines (Angular / Nest / PL/SQL / Drools)Tier 1 project knowledgeSame
RBAC model documentTier 1 project knowledgeSame
HHS domain primerTier 1 project knowledgeSame
Estimation methodology documentTier 1 project knowledgeReference material
Estimation procedure (apply to backlog)SkillDone repeatedly with output shape
San Diego RFP / SOW / responseTier 2 project knowledgeEngagement-specific reference
San Diego config decisions logTier 2 project knowledgeEngagement-specific reference
Per-story PRS / LLD outputsDrive folders, linked from JiraWorking artifacts
Jira / Bitbucket / Drive read+writeConnectorExternal system access
"How do I install Claude Code?"Portal FAQ / ResourcesNot skill-shaped
"Draft AC for this story"Skill (story-ac-gherkin)Recurring, defined shape, eval-able
"Generate the Nest service for this story"Skill (code-nest)Recurring, defined shape, eval-able
"Review this PR against Empower standards"Skill (review-empower-standards)Recurring, defined shape, eval-able

6. The output-quality stack

CRAFT output quality comes from four layers stacked correctly. When something feels off, diagnose from the bottom up — most failures are a Layer 2 or 3 problem, not a Layer 4 (model) problem.

LAYER 4
Model
Opus for hard, Sonnet for normal, Haiku for cheap. Routing per skill.
LAYER 3
Context
Tier 1 + Tier 2 + the specific upstream artifact. Loaded into the project.
LAYER 2
Skill
Steps, output shape, citation rules, guardrails. The procedure.
LAYER 1
Inputs
The user's prompt + connector-retrieved artifacts.

Failure-mode → layer map

SymptomMost likely layerFix
"It made stuff up"Layer 3 (Context)Load the missing doc into Tier 1/2 or sharpen what's there
"It produced a vague generic answer"Layer 2 (Skill)Tighten output shape; add concrete examples in the skill
"It got the standard wrong"Layer 3 (Context)Tier 1 doc is stale; refresh and re-attach
"Too slow / expensive"Layer 4 (Model)Re-route to Sonnet or Haiku where quality allows
"It refused to do the job"Layer 2 (Skill)Guardrail too restrictive; soften with explicit allowed-cases
"It approved its own work"Layer 2 (Skill) or ProcessAdd explicit HITL gate; enforce via Jira workflow / branch protection

7. Authoring sequence — Wave A through D

The right order to author skills, optimized for shortest path to demonstrable value.

WaveWeekWhat ships
Wave A — FoundationWeek 16–10 Tier 1 context docs (NOT skills): Empower architecture, RBAC v4, coding guidelines, workflow/rules patterns, HHS domain primer, NFR baselines, estimation methodology, project template, AI usage addendum template
Wave B — SpineWeek 25 skills exercising the full spine end-to-end: rfp-ingest, prs-generator, fit-gap-classifier, story-ac-gherkin, code-empower-workflow
Wave C — Design + CodeWeek 3hld-functional, er-diagram, lld-extension, code-extension, review-empower-standards
Wave D — Tests + ShipWeek 4tc-unit, tc-system, tc-uat, release-notes, pr-review

After Wave D you have ~20 skills covering the full spine on OOTB and Extension buckets. Enough to demo end-to-end and start measuring with evals. The remaining ~65 skills (other buckets, deliverables planning, governance, analytics) come in Phase 2.

8. The 5-file deliverable per skill

A skill is not "one markdown file." It's FIVE files. If any are missing, the skill can't graduate past experimental. This is the governance lock that prevents rot.
  1. The skill markdownskills/<skill-name>.md
  2. The eval rubricevals/<skill-name>_rubric.md
  3. The golden set seedevals/golden/<skill-name>/seed.json (start with 5 items; 20 for beta; 50 for GA)
  4. The judge prompt — entry in agent_prompts registry with agent_id="evals_judge_<skill>"
  5. The example invocationsskills/<skill-name>.examples.md with 3 realistic user prompts and expected outputs
Remember this
A skill's job is to make the model do the right procedure consistently. The skill does NOT contain knowledge — it references knowledge that lives in context. If your skill markdown is mostly facts, you've written a context document. If it's mostly an output template, you've written a prompt template. A skill is a procedure that references context and produces a specified output.

Do's & Don'ts — Guardrails

The rules of the road. Read this before you start. CRAFT's leverage depends on these holding — for our clients, for our employees, and for Cardinality's IP.

If you read one line on this tab: AIDLC is governed by six guardrail domains — Security, Data, Intellectual Property, Skill Governance, People, and Incident Response. Each has a do-list and a don't-list. Violations of the don'ts are reported to the CoE within 24 hours.

The six guardrail domains

1. Security
Enterprise tier, SSO, audit logs, BAA, prompt-injection defense, no autonomous destructive actions.
2. Data
Synthetic-only scope. No PHI, FTI, CJI, or client production data ever enters Claude.
3. Intellectual Property
Empower platform code, client deliverables, and Cardy AIDLC skills are Cardinality IP. AIDLC outputs are work-for-hire under client contracts.
4. Skill Governance
Versioned in git, eval-gated to GA, signed CoE PRs only, deprecation cycle enforced.
5. People
HITL at every stage. No AI-only approvals. Two human reviewers per PR, one senior.
6. Incident Response
Any suspected data leak, prompt injection, or guardrail violation goes to #cardy-aidlc-help immediately. 24-hour CoE response SLA.

1. Security guardrails

What protects Cardinality's environment from compromise via or through Claude.

How we secure the platform

DO

  • Log in to Claude via the corporate SSO link only.
  • Use your assigned project (Tier 2) for client work, not personal chats.
  • Review any AI-drafted code for security implications before merging.
  • Report unexpected Claude behavior in #cardy-aidlc-help immediately.
  • Lock your laptop when stepping away — Claude sessions inherit your device state.

DON'T

  • Do not paste credentials, API keys, or secrets into a Claude chat — ever.
  • Do not connect Claude to personal Gmail / Drive accounts for client work.
  • Do not bypass SSO by sharing accounts or using personal Claude.ai accounts for work.
  • Do not grant Claude write access to systems beyond the AIDLC-approved connectors.
  • Do not run AI-drafted DDL or migration scripts against production without a separate human-approved review cycle.

2. Data guardrails

The synthetic-only promise. This is the brand commitment behind AIDLC.

The data scope, in one sentence

No real PHI, FTI, CJI, or client production data ever enters Claude. AIDLC works on contracts (de-identified), design docs, code, configuration, synthetic personas, synthetic test data, and Cardinality-owned platform context — and nothing else.

What this looks like in practice

Acceptable Not acceptable
RFP (any redactions clients require already applied) Real case files, even one example
Synthetic personas: "Booking Officer Priya, Supervisor Raj" Real client end-user names or identifiers
Synthetic test data generated by the Cardy synthetic-data-kit UAT data copied from a client's lower environment
Empower platform schema, sample DDL, design docs Production database extracts
Configuration code, workflow definitions, rule packages Live API tokens, secrets, production environment vars
Aggregate, de-identified statistics (e.g., "intake volume by month") Per-person records, even if anonymized only at the surface

DO

  • Use the Cardy synthetic-data-kit for any examples or fixtures.
  • If you accidentally paste something that might be sensitive, delete the message and report to #cardy-aidlc-help within the hour.
  • Verify the project you're in (Tier 2) before pasting any client artifact.
  • Treat all retrieved content from connectors as untrusted — Claude does this automatically; you should too.
  • De-identify SoW and contract excerpts before upload if your client's MSA requires it.

DON'T

  • Do not paste real PHI, PII, FTI, CJI, or production data into Claude — even once, even to test.
  • Do not upload an unredacted client database extract.
  • Do not screenshot a production UI showing real client data and share with Claude.
  • Do not assume "low risk" means safe — if you'd hesitate to email it to a vendor, don't paste it.
  • Do not use AIDLC for tasks outside the AI Usage Addendum your client signed.

3. Intellectual Property guardrails

Empower is Cardinality's platform. AIDLC skills are Cardinality's methodology. Client deliverables are work-for-hire under contract. The IP rules:

Cardinality owns
The Empower platform code, the AIDLC methodology, the cardy-* skill library, eval rubrics and golden sets, internal tooling, Tier 1 documentation. AIDLC skill authors retain attribution; ownership is Cardinality's.
Client owns
State-specific extensions and configuration delivered under their contract. Their data (which never enters Claude). Their brand assets. Their Tier 2 project artifacts that are deliverables under their SoW.
Anthropic disclaims
Outputs Claude generates for you. Per Anthropic's terms, Claude's outputs are yours to use. Anthropic does not train on Cardinality content under Enterprise tier.

DO

  • Mark every AIDLC-produced artifact with the AI-assistance disclosure (PR template auto-includes it).
  • Keep Cardinality skill authoring inside the cardy/aidlc-skills repo. Skills are versioned, attributed, and Cardinality-owned.
  • Verify a client's MSA permits AI assistance on their deliverables. The AI Usage Addendum makes this explicit.
  • Cite Tier 1 and Tier 2 source material in AIDLC outputs — establishes provenance.

DON'T

  • Do not paste Empower proprietary code into personal-account Claude or any other AI tool.
  • Do not push a Cardy skill to a public repo, gist, or external prompt library.
  • Do not use a client's Tier 2 artifacts as Tier 1 reference material for another client without their written consent.
  • Do not represent AIDLC outputs as human-authored when a client's contract or RFP requires AI disclosure.
  • Do not author skills on personal time and claim individual ownership — skill IP is Cardinality's by default.

4. Skill governance

How we keep the skill library trusted as it grows from 20 to 85+ skills.

DO

  • Propose new skills via PR to cardy/aidlc-skills.
  • Include golden-set examples and rubric updates with substantive skill changes.
  • Cite Tier 1 standards by name in skill outputs — it's a rubric dimension.
  • Report a skill regression in #cardy-aidlc-help with reproduction steps.

DON'T

  • Do not edit your local copy of a skill and ship a one-off to a client — your edit is invisible to evals.
  • Do not change the default model on a skill without a passing head-to-head eval.
  • Do not use a deprecated skill past its sunset date — replacements are named in the deprecation notice.
  • Do not bypass the two-human PR rule by claiming "Claude reviewed it."

5. People & HITL guardrails

AIDLC is human-supervised by design. The HITL gates are non-negotiable.

Gate Approver Encoded in
PRS → Fit-Gap BA Lead Jira workflow transition
Fit-Gap → Story Decomposition Solution Architect Drive doc approval comment
HLD → LLD Implementation Architect (+ Empower Product Architect for Platform / Product Feature) Drive doc approval comment
Stories → Development BA Lead + PM Jira workflow transition
LLD → Code Tech Lead (bucket-specific) Drive doc approval comment
Test Cases → Master Suite QA Lead Xray/Zephyr promotion
Code → Merge Two human reviewers, one senior; Claude may be one, never both Bitbucket branch protection
Release DevOps Engineer + Implementation Manager Functional implementation project team's Slack channel + Jira release transition

DO

  • Be the human in the loop. Read every AI-drafted artifact before approving.
  • Use the AI-assistance checklist in the PR template — it forces explicit disclosure.
  • Edit AIDLC outputs visibly. The point isn't to accept whole; it's to make them right.
  • Escalate to the CoE if a skill produces consistently wrong artifacts — that's a rubric signal.

DON'T

  • Do not approve an artifact you haven't read.
  • Do not bypass the second human reviewer on a PR.
  • Do not auto-transition Jira tickets with AI based on AI output — humans transition.
  • Do not let "Claude said so" justify a decision. Claude proposes; you decide.

6. Incident response

Things will go wrong. Here's the playbook.

Severity levels

Severity Example Response SLA
SEV-1 Real PHI/FTI/CJI suspected pasted into Claude CoE acknowledges in 1 hour; Security loop in same day
SEV-2 Prompt injection succeeded; client data leak suspected; IP exposure CoE acknowledges in 4 hours
SEV-3 Skill quality regression; eval drift >0.3; consistent false PR review positives CoE acknowledges in 24 hours
SEV-4 Workflow friction; usability complaint; minor skill bug Champion or CoE in next business day

What to do if you suspect a violation

  1. Don't try to clean it up alone. Reporting an honest mistake is welcomed; covering one up is not.
  2. Capture evidence. Screenshot the chat, note the project, note the skill if applicable.
  3. Post to #cardy-aidlc-help with the severity tag (SEV-1 etc.) and the evidence. CoE on-call is paged automatically for SEV-1/2.
  4. Stop the relevant work until CoE clears it.
  5. Cooperate with the post-mortem. Every SEV-1/2 gets a written post-mortem; we focus on the system, not the person.
Blameless reporting. Cardinality's policy is blameless reporting for honest mistakes with AIDLC. The disciplinary path is reserved for deliberate violations (deliberate exfiltration, knowing PHI exposure for personal use, etc.). Report fast; we'll work the problem together.

Quick reference card

If you're about to… First ask yourself
Paste a document into Claude Is this real client data? If yes, stop.
Run code Claude wrote in production Has a second human reviewed and tests passed? If no, stop.
Send a Claude-drafted email to a client Have I read it end-to-end? Has my manager seen it if it's sensitive? If no, stop.
Author a new skill Is this in the cardy/aidlc-skills repo? Does it have golden examples? If no, open a PR.
Use Claude on personal/side projects Use a personal Claude account on personal time. Don't mix with the Cardinality SSO tenant.
Share a Claude transcript externally Does it contain Tier 2 client material or Empower IP? If unsure, ask the CoE before sharing.

Your Role — What Changes

Pick your role to personalize. We'll surface your skill pack, your daily flow, your access date, and where to go next. Your selection persists across visits and across tabs.

Personalize this portal

I am a…

Your skill pack
Your daily flow
When you get access
See the Timeline tab.
Where to learn more
See full details below, or jump to the Pilot: San Diego walkthrough.

All roles

The full reference. Your selected role above gets highlighted; the rest are visible for context.

Business Analyst / Product Manager
Your skill pack
cardy-pmo-pack + cardy-platform-base.
Your daily flow
Open Claude.ai → switch to your implementation Project. Run /prs-generator on a new RFP section. Edit, accept. Run /epic-to-stories, then /story-ac-gherkin. Paste into Jira (or do it directly in Jira via @claude). Approve own AC; mark "Ready for Dev".
When you get access
See the Timeline tab.
Where to learn more
Pilot tab → Stages 1, 2, 3, 5. Workshop calendar invite arrives ahead of your access date.
Solution Architect / Tech Lead
Your skill pack
cardy-arch-pack + cardy-pmo-pack + cardy-platform-base.
Your daily flow
Open Cowork mode. Run /fit-gap-classifier against the PRS. Then /hld-functional + /er-diagram + /data-model. Save to Drive, link to Jira. Approve own designs only after second-pair review.
When you get access
See the Timeline tab.
Where to learn more
Pilot tab → Stages 3, 4, 7. Architecture office hours twice weekly.
Developer
Your skill pack
cardy-dev-pack + cardy-platform-base. Skills are bucket-aware/code-empower-workflow for OOTB, /code-extension for client extensions, etc.
Your daily flow
Open Claude Code in your repo. Pick up a story from Jira. Run /code-empower-workflow SD-7 (or whichever bucket skill matches). Review the diff. Edit. Run /unit-tests. Run tests locally. Push branch, open PR — Claude posts a review automatically. Second human reviewer approves. Merge.
When you get access
See the Timeline tab.
Where to learn more
Pilot tab → Stage 9 (the developer's day). Pair sessions with your champion in the first week of access.
QA / Performance Engineer
Your skill pack
cardy-qa-pack + cardy-platform-base.
Your daily flow
From a story + tech design, invoke /tc-system, /tc-sit, /tc-uat, /tc-perf, /tc-security. Review, edit, import to Xray/Zephyr. Approve. During execution, use /defect-triage and /regression-pack-update.
When you get access
See the Timeline tab.
Where to learn more
Pilot tab → Stages 8, 11. QA workshop scheduled around your access date.
DevOps Engineer
Your skill pack
cardy-release-pack + cardy-platform-base.
Your daily flow
Before release, run /runbook-drafter and /rollback-plan. At ship time, /release-notes. Post-release, /hypercare-digest daily during hypercare window.
When you get access
See the Timeline tab.
Where to learn more
Pilot tab → Stage 12.
Delivery Manager
Your skill pack
cardy-pmo-pack + cardy-platform-base. Plus the deliverables-planning skills: /ssp-plan, /infra-plan, /ocm-plan, /training-plan, /transition-plan.
Your daily flow
At kickoff: run /estimation-methodology and per-bucket /estimate-*. For each contract deliverable, run the matching planning skill to produce a contributor brief + outline. Hand to contributors. Track via your normal PM tooling.
When you get access
See the Timeline tab. You can pick up cardy-pmo-pack earlier if you sit alongside BAs.
Where to learn more
Pilot tab → Deliverables Track + Stage 6. PMO huddle scheduled around your access date.
Configuration Specialist
Your skill pack
cardy-dev-pack (OOTB skills subset) + cardy-platform-base.
Your daily flow
For OOTB stories, invoke /code-empower-config, /code-empower-workflow, /code-empower-page, /code-empower-rule. Apply in Empower workflow designer / page builder / rules engine. PR-style review with Empower Config Lead.
When you get access
See the Timeline tab.
Where to learn more
Pilot tab → Stage 9 (OOTB lane).
Data Migration Engineer
Your skill pack
cardy-dev-pack (migration skills) + cardy-platform-base. Plus migration-specific test skills from cardy-qa-pack.
Your daily flow
Invoke /lld-migration for the mapping design. Then /code-migration-pipeline for the actual ETL. Then /tc-migration-validation for row-count, integrity, business-rule validation cases. All grounded against the legacy source schema doc and the Empower target ER from Tier 2.
When you get access
See the Timeline tab.
Where to learn more
Pilot tab → Stage 7 (LLD-migration) + Stage 9 (migration pipeline). Migration office hours scheduled around your access date.
Report Developer
Your skill pack
cardy-dev-pack (analytics skills) + cardy-platform-base.
Your daily flow
Invoke /lld-migration (analytics variant — same skill, different bucket context) for the dashboard / data mart design. Then /code-analytics-dashboard for the BI artifacts. Outputs grounded against operational schema and reporting requirements from Tier 2.
When you get access
See the Timeline tab.
Where to learn more
Pilot tab → Stage 9 (analytics lane). BA Lead approves before publishing.
Empower Platform Engineer
Your skill pack
Same as Developer pack, plus you co-own cardy-platform-base — the Tier 1 standards.
Your daily flow
Same as Developer for Platform/Product Feature work. Plus: quarterly Tier 1 refresh ceremony where you and the CoE update platform standards documents.
When you get access
See the Timeline tab.
Where to learn more
Pilot tab → Stage 9 (Platform/Product Feature lane). Empower Product Architect briefing in the first week of access.
You stay senior on every artifact. AIDLC shortens the path from blank page to first draft. Your judgment is still what makes the artifact correct.

Pilot: San Diego implementation

Our real pilot engagement — a San Diego county HHS implementation kicking off now. Follow this end-to-end and you'll see exactly what your role does at each stage. The engagement is real; the working artifacts in CRAFT (extracts, examples, fixtures) are de-identified per our data-scope policy.

Setup — the Tier 1 and Tier 2 documents

Tier 1 Org-level documents (set by Empower Product + CoE — once for the whole org)

T1
Empower Architecture OverviewHigh-level architecture, modules, integration points.
T1
Coding Guidelines (Frontend, Backend, DB, Rules)Per-language conventions and Empower-specific patterns.
T1
RBAC Model (v4)Subjects → Roles → Capabilities. Facility-scoped.
T1
Workflow Designer PatternsStandard motifs for case-management workflows.
T1
Rules Engine PatternsDecision tables vs DRL; rule organization.
T1
HHS Domain PrimerChild welfare, child support, juvenile justice basics for engineers new to the domain.
T1
NFR Baselines & SecurityP95 targets, audit events, accessibility.
T1
Estimation MethodologyPer-bucket story-point definitions.

Tier 2 San Diego documents (set by the implementation squad lead + PM at kickoff)

T2
RFP — San Diego HHSThe client's request for proposal.
T2
Cardinality ResponseOur winning proposal with proposed tech stack and approach.
T2
Signed SOWStatement of Work with named deliverables and milestones.
T2
AI Usage Addendum (De-Identified Working Artifacts)Signed by squad lead + Legal. The data-scope guardrail in writing.

All 12 docs live in Google Drive folders that are wired to the Tier 1 and Tier 2 Claude Projects. Once they're in, every skill in the workflow grounds against them automatically.

Artifact formats. CRAFT generates business-ready outputs in the format that fits each stage: .docx for PRS / HLD / LLD / release notes, .xlsx for fit-gap matrices and estimation models, .pptx for client decks, .pdf for signed deliverables, and code in the repo. Markdown drafts are an internal authoring step only — the artifact you review and ship is in the business format.

Now the flow — stage by stage

Stage 11

Pre-Sales Ingest

BA · PM · Solution Architect

Squad lead drops the RFP, response, SOW into the Tier 2 Drive folder. BA opens Claude.ai → "San Diego Implementation" project → runs /rfp-outcome-extraction to pull the named outcomes the client contracted for, and /sow-deliverables-extractor to extract the named contract deliverables (SSP, IP, OCM, etc.) — separated for the PMO.

You click
Open Claude.ai → San Diego project → /rfp-outcome-extraction
You see
A structured list of outcomes, requirements, and contract deliverables, each citing RFP page numbers.
Output
"San Diego — Outcomes & Deliverables Brief" saved to Drive; linked from Jira project description.
Stage 22

Detailed PRS

BA · Product Owner

BA invokes /prs-generator in Cowork mode. Claude reads the San Diego RFP, response, and outcomes brief; produces a long-form PRS (100–200 pages) with flows, UML sketches, and acceptance criteria. If the PRS is genuinely too big to be one document, BA invokes /prs-splitter — splits into Core PRS, Integration PRS, Data Migration PRS, Extensions PRS.

You click
/prs-generator in Cowork; then /prs-section-deepener for any thin sections.
You see
Streamed PRS with cited references back to RFP. Each section has cleanly numbered AC.
Output
PRS_SanDiego_v0.1.docx in Drive. BA Lead reviews, edits, marks "Approved v1.0", and a more traditional word document or PDF can be generated.
Stage 33

Fit-Gap & Classification

Solution Architect

SA invokes /fit-gap-classifier. Claude reads the PRS and the Tier 1 Empower platform docs; classifies every requirement into one of the 6 buckets. Output: a classification matrix.

You click
/fit-gap-classifier in Cowork.
You see
Matrix: requirement → bucket → rationale → confidence. Items with confidence < 3 flagged for SA attention.
Output
FitGap_Matrix_v0.1.xlsx in Drive. SA edits, approves. Jira epics auto-tagged with bucket.
Requirement Bucket Rationale
Intake & eligibility workflow with referral capture OOTB Configuration Empower workflow designer + page builder, no new platform features needed.
San Diego's safety & risk assessment protocol Client Extension Client-specific rule package; doesn't belong in core platform.
Courts SFTP nightly feed (juvenile dependency dockets) Integration External system contract.
Migrate 50K legacy case records from CWS/CMS Data Migration One-time data migration with mapping, transformation, validation.
Caseload & outcomes dashboard for supervisors Analytics & BA Operational BI on top of the operational data.
"Multi-county placement coordination" capability Platform / Product Feature Generally useful capability — belongs in Empower core.
Stage 44

High-Level Design

Solution Architect · Data Architect · Security Architect

SA invokes /hld-functional, /hld-architecture-diagram. Data Architect invokes /er-diagram and /data-model. Security Architect invokes /security-model. Each lands in Drive; each is approved before story decomposition.

You click
/hld-functional, /er-diagram, /security-model
You see
HLD with options-considered, recommendation, NFR specifics. ER diagram with delta from existing Empower model.
Output
HLD_SanDiego.docx, ER_SanDiego.svg, SecurityModel.docx — all in Drive, linked to Jira epics.
Stage 55

Story Decomposition

BA · Product Owner

BA invokes /epic-to-stories on each epic, then /story-ac-gherkin on each story. Outputs land directly in Jira via the connector.

You click
/epic-to-stories CARDY-EPIC-1, then per-story /story-ac-gherkin
You see
Stories with Gherkin AC covering happy / sad / edge / NFR scenarios. Each cites SoW page and parent epic.
Output
Stories created in Jira: SD-1 through SD-30+. Status "Ready for Estimation".
Stage 66

Estimation

Tech Lead · PM

Per bucket, tech leads invoke the matching estimation skill: /estimate-ootb, /estimate-extension, /estimate-integration-migration. Each uses the per-bucket story-point methodology from Tier 1.

You click
Per bucket: /estimate-ootb etc.
You see
Story points per story with rationale. Confidence flags for outliers.
Output
Estimates back into Jira. Sprint plan formed.
Stage 77

Low-Level Design

Architect · Tech Lead (bucket-specific)

For each significant story, the bucket-matching LLD skill runs: /lld-ootb-config for OOTB, /lld-extension for extensions, /lld-integration for integrations, etc. Each LLD includes contracts, sequence diagrams, and decision points.

You click
Pick LLD skill matching the bucket; pass story key.
You see
Bucket-appropriate LLD. For Extension: sequence + Empower extension hooks + RBAC capability names. For Integration: contract diagram + error handling.
Output
LLD_SD-NN.docx in Drive. Tech Lead approves.
Stage 88

Test Case Generation

QA · Developer (for unit)

QA runs /tc-system, /tc-sit, /tc-uat, /tc-perf, /tc-security per story. Developer runs /tc-unit alongside code generation in Stage 9.

You click
Per layer: /tc-system, etc.
You see
Test cases mapped to AC, with setup, steps, expected results.
Output
Cases imported into Xray/Zephyr by one click.
Stage 99

Development — the developer's day

Developer (bucket-aware)

This is the most-asked-about step, so let's walk a real one. Story SD-7: "Implement San Diego's safety & risk assessment protocol as a client extension." Bucket: Client Extension. Developer Anil opens VS Code, opens Claude Code in the project, types:

$ claude
> /code-extension SD-7

Claude reads the story from Jira, the LLD from Drive, the Empower rules-extension patterns from Tier 1. Generates: a Drools rule package for the safety/risk protocol, a Nest service to invoke it, an Angular component to display the assessment, and an RBAC binding so only Supervisors can override. Then runs /unit-tests automatically alongside. Anil reviews the diff inline, fixes one edge case, pushes:

$ git push origin feature/SD-7-safety-risk-assessment

Opens a PR. Claude posts a review against Empower standards (Stage 10).

You click
Inside Claude Code: /code-extension SD-7, then /unit-tests.
You see
Diff across rule package, service, component, and tests. Bucket-aware — uses your client extension scaffolding, not platform-core patterns.
Output
Branch + PR + green tests + Claude PR review comment.
Stage 1010

Code Review

Senior Developer (human) + Claude (one of two reviewers)

Claude posts inline comments against Empower standards (RBAC, audit events, NFR baselines). Senior Dev reviews; can dismiss Claude comments. Second human reviewer approves. Merge.

You click
Open PR; read Claude comments; mark resolved / fix; second human reviewer approves.
You see
Inline annotations citing Tier 1 standards. Severity-labeled. Sometimes 1-2 false positives — human judgment is the gate.
Output
Merged PR. Story moves to "Ready for QA".
Stage 1111

Test Execution

QA

QA runs test suites. For failing cases, invokes /defect-triage — Claude classifies and proposes likely root cause, links to relevant code. QA confirms, files defect.

You click
Run tests; for failures /defect-triage.
You see
Triage suggestions with code links and a confidence score.
Output
Defect tickets in Jira, mapped to root-cause hypotheses.
Stage 1212

Ship & Hypercare

DevOps Engineer · Delivery Manager

DevOps Engineer invokes /release-notes, /runbook-drafter, /rollback-plan. Posts in the implementation team's own release Slack channel for approval (e.g. #sd-implementation-releases). After ship, /hypercare-digest runs daily for 2 weeks.

You click
/release-notes SD-7, then /runbook-drafter, /rollback-plan.
You see
Release notes citing tickets. Runbook with verification steps. Rollback plan with named owners.
Output
Release notes in Drive + Slack post; runbook in Confluence; rollback plan in PR description.

The parallel Deliverables Track

Running alongside Stages 1–12 is the Contract Deliverables Track. PMO invokes planning skills for each contract deliverable. AIDLC does NOT generate the SSP itself; it generates a planning artifact that names contributors, sections, data sources, prior reference materials, and a draft outline. Humans author the final docs.

Deliverable Skill When Contributors
System Security Plan (SSP) /ssp-plan Week 2 of implementation Security + DevOps + Compliance
Infrastructure Plan (IP) /infra-plan Week 2 DevOps + Solution Architect
OCM Plan /ocm-plan Week 3 OCM Lead + PM
Training Plan /training-plan Week 4 Training Lead + PM
Transition Plan /transition-plan Before go-live PM + Hypercare Lead
That was the whole loop. Same shape repeats per sprint. The skills get sharper with eval feedback. Your judgment is still the gate at every stage.
File Formats. This process mentions markdown files (.md extension) as the input and output files for any text heavy document or artifact. This is because markdown files are pure text, and are useful to quickly review and make changes. Once the content is reviewed and approved, better known formats such as word documents or PDFs can be generated using the same content.

Timeline — PLACEHOLDER

All dates and day-counts below are PLACEHOLDER. Final dates will be confirmed and replaced once kickoff is signed off.

Customize me. Replace [KICKOFF], [+10d], [+25d], [+35d], [+50d], [+60d], [+120d] with real calendar dates before circulating.
Day 0[KICKOFF]
Phase 1 — Kickoff
All-hands announcement. Strategy doc circulated. CoE introduced.
Everyone
Day 0–10[KICKOFF] → [+10d]
Phase 2 — Foundations
Procurement, BAA, SSO, audit log routing complete. CoE seated. Pilot squad named (12). Tier 1 ingested. Tier 2 San Diego provisioned. Skill packs v0.1 in repo.
CoE · IT · Legal · Squad Lead
Day 10–25[+10d] → [+25d]
Phase 3 — Pilot (San Diego implementation)
12-person squad runs end-to-end through AIDLC on the live San Diego engagement. cardy-pmo-pack + cardy-platform-base live. Top-5 evals running (PRS, Fit-Gap, HLD, Story+AC, Code Review). Day-25 leadership review with go/no-go on the next phase.
Pilot squad (BA, Architect, Dev, QA, DevOps)
Day 25–35[+25d] → [+35d]
Phase 4 — BAs & Architects (~50)
cardy-arch-pack ships. PRS, fit-gap, HLD, LLD, estimation skills live across active engagements. Workshops twice weekly. Office hours open.
All BAs + Architects (onsite + offshore)
Day 35–50[+35d] → [+50d]
Phase 5 — Developers (~200)
cardy-dev-pack ships. Claude Code installed across the developer fleet. Bucket-aware code skills live. Code review skills live. Two-human PR rule enforced via branch protection.
All Developers · Configuration Specialists · Empower Platform Engineers
Day 50–60[+50d] → [+60d]
Phase 6 — QA · DevOps · PM (~40)
cardy-qa-pack and cardy-release-pack ship. Test generation + execution + ship readiness live. Deliverables planning skills live for PMO.
All QA · DevOps Engineers · Delivery Managers
Day 60[+60d]
Phase 7 — Org-wide access complete · CRAFT v1 declared
All 300+ employees have access to their skill packs. Leadership review #2. Portal updated with retros and metrics.
Everyone
Day 60–120[+60d] → [+120d]
Phase 8 — Hardening & GA
Full skill library matures to ~85 skills. All skills promoted to GA where eval thresholds are met. Production sampling at 5% wired across surfaces. Drift dashboard live. Next implementation kicks off the AIDLC way.
CoE · all squads

What you should do before your access date

FAQ

The questions people are actually asking. If yours isn't here, post in #cardy-aidlc-help.

Is real client data going into Claude?

No. AIDLC works on contracts (de-identified), design docs, code, configuration, synthetic personas, and synthetic test data only. No PHI, no CJI, no FTI, no real client production data — ever. This is a contractual posture, enforced in every project addendum and every skill preamble.

Will this change my job?

The shape of your day shifts. Less blank-page drafting, more reviewing AI-drafted artifacts and making them right. The system of record (Jira, Bitbucket, Drive) doesn't change. Your approver role doesn't change. What changes is the speed from "we have a story" to "we have a tested PR" — that's the whole point.

Will AI replace any of us?

Not in this plan. Cardinality's growth plan is to win more state implementations and ship them faster — that requires more senior people, not fewer. AIDLC is leverage for the people we already have. The CoE is +5 hires; no role is being eliminated.

What if Claude writes bad code?

Two human reviewers required on every PR, one of them senior. Claude can be one of the two, never both. Plus the Code Review skill flags low-confidence sections and Empower-standards violations before a human reviewer opens the PR. Plus tests must be green. Plus the eval framework catches systematic quality regressions before they reach prod.

Will offshore and onsite teams be on the same skills?

Yes. The skill library is shared. Bucket ownership reflects natural team focus — Platform / Product Feature work typically sits with the Empower product team, Client Extension and Integration buckets typically sit with implementation teams — but every skill is available to anyone with the role.

How do we know the skills are working?

Every AIDLC skill has an evaluation rubric and a golden set (20–50 examples). Quality is scored weekly, drift is monitored, and skills can only graduate to GA after hitting thresholds. The dashboard is in the CoE Settings and reviewed monthly with leadership.

What about the contract deliverables — SSP, IP, OCM?

For this rollout, AIDLC produces a planning artifact for each: contributors, sections, source data, prior reference materials (de-identified), and a draft outline. Humans author the final document. AIDLC removes the blank-page tax; humans keep ownership of regulatory artifacts.

What if a client objects to AI being involved?

Show them the AI Usage Addendum (de-identified working artifacts; no real PHI/FTI/CJI/production data) and the HITL gate matrix. If they want eval evidence, the CoE can share scores. To date, every state client briefed on CRAFT has been supportive once they see the controls.

I have an idea for a new skill — what do I do?

Open a PR against cardy/aidlc-skills. Squad champions can fast-track squad-specific skills. Cross-cutting skills go through CoE review. Every skill is versioned; nothing is final.

What if a skill produces a wrong artifact?

Reject it. Edit it. The HITL gates exist exactly for this. Then flag it in #cardy-aidlc-help with the skill name and what went wrong. The CoE uses these reports to tighten rubrics and grow golden sets.

What's the cost? Who pays?

Claude Enterprise license is centrally funded by Innovations & AI. No per-seat charge to delivery budgets. Per-skill usage is tracked and visible to the CoE; expensive Opus-heavy skills are monitored and may be model-routed to Sonnet if a cost/quality crossover allows.

Who do I ask?

Slack #cardy-aidlc-help is the front door for help and guidance — open to everyone. CoE on-call rotation publishes there. #cardy-aidlc-announce is read-only for broadcasts. #cardy-aidlc-coe is CoE folks only. Release approvals and project-stage approvals happen inside each implementation team's own channels and Jira workflow, not in the CRAFT channels.

Resources

Links, channels, and the CoE.

Customize me. Replace the # in each href="#" below with the real Google Drive link before circulating. The top "Drive home" link drops people into the AIDLC folder; the rest are direct deep-links to each document.

Documents (Google Drive)

→ Open the CRAFT Drive folder

Slack channels — keep it simple

Three channels. That's it. Everything else (skill PRs, eval digest, pilot updates) is threaded inside these.

Claude resources

The CoE — Office of Innovations & AI (placeholder)

Office hours (placeholder)

What to do right now

  1. Join #cardy-aidlc-announce. You'll get every phase launch and milestone here.
  2. Read the Pilot tab. It's the single highest-leverage 10 minutes you'll spend on CRAFT.
  3. Mark your access date. Block 30% of your calendar for the week your role's pack ships (Timeline tab).
  4. Ask one question. In #cardy-aidlc-help. We want every question now, not on your access date.

Why CRAFT

Sometimes a picture says it faster than the strategy doc. Share these in Slack, drop them in a deck, pin them above your monitor.

AI-Native SDLC vs Traditional SDLC

TRADITIONAL SDLC "Let's manually..." write requirements, create user stories, code everything, test everything, review everything, document everything ourselves, …and stay late again." AI-NATIVE SDLC (CRAFT) "AI generates..." requirements, stories, code, tests, documentation, traceability, reviews. Humans guide, validate, govern. Ship faster. Sleep better. Win more. "Competing in software delivery without AI today is like bringing sticks and stones to a drone war."

AI does the heavy lifting. Humans provide the judgment.

Print it. Pin it. Paste it in a deck. Share it in Slack. If anyone asks why we're investing in CRAFT, this picture is the 5-second answer.

More memes welcome. Got a visual that captures CRAFT, HITL, or the bucket model in one image? Drop it in #cardy-aidlc-help and we'll add it here.