How do I install the Architect Enterprise AI skill?

Run npx skillmds@latest add hiteshbandhu/architect-enterprise-ai in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Architect Enterprise AI free to use?

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Who published Architect Enterprise AI?

hiteshbandhu (@hiteshbandhu) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Architect Enterprise AI by hiteshbandhu

Name: Architect Enterprise AI
Author: hiteshbandhu

Architect Enterprise AI

Runs enterprise AI architecture playbooks from AI Architects @ AI Engineer — AI architect role, agent platforms, voice agents, agent auth (CIAM), trusted inference, team structure, monetization, and product survival. Use when designing org-wide AI systems, agent platforms, or CIO-ready inference; or when the user says "AI architect", "enterprise agents", "CIAM for agents", "AI that pays", "build-operate divide".

hiteshbandhu Updated Sep 17, 2026

File contents

Architect enterprise AI

Action playbook from nineteen AI Architect track talks. Do not summarize talks — pick a workflow and execute it.

Supporting files:

workflows.md — workflows A–M
source-index.md — src-NNN → learnings

Optional deliverables: {SKILL_OUTPUT_DIR}/architect-enterprise-ai/

Step 0 — Pick workflow

What is the user trying to do?
├─ Define AI architect role & stack choices              → A  [src-015, src-009]
├─ Ship agents that work in production                   → B  [src-003, src-010]
├─ Build agentic platform (Box-style)                  → C  [src-004, src-005]
├─ Voice agents                                          → D  [src-006]
├─ Agent identity / authZ (CIAM)                       → E  [src-007]
├─ CIO-trusted inference & telemetry                     → F  [src-008]
├─ Browser-as-runtime for agents                         → G  [src-019]
├─ Developer experience (AX)                             → H  [src-002]
├─ Revenue / ROI proof (healthcare RCM)                  → I  [src-001]
├─ Feedback loops & learning products                    → J  [src-011, src-013]
├─ Monetization & GTM for AI                             → K  [src-014, src-012]
├─ Modern AI team structure                              → L  [src-016]
├─ Product strategy / knife fight                        → M  [src-017, src-018]

Open workflows.md.

Install

cp -r skills/architect-enterprise-ai ~/.claude/skills/
cp -r skills/architect-enterprise-ai ~/.cursor/skills/

Source: playlists/ai-architects-ai-engineer/.

Cross-cutting rules

Rule	Source
AI architect owns integration, tools, embeddings, vector DB	[src-015 @ 9:41]
Agents need production design patterns, not demos	[src-010]
Feedback loops beat one-shot prompts for quality	[src-011]
AuthN/AuthZ for agents is a first-class concern	[src-007]
Bridge build vs operate for AI product vision	[src-018]

Output to user

Name workflow (A–M) and deliverable
Artifacts under ./skill-outputs/architect-enterprise-ai/ when requested

Invocation examples

@architect-enterprise-ai define our AI architect scope
agent auth model for enterprise SaaS
prove ROI for our AI inference platform

---name: architect-enterprise-aidescription: Runs enterprise AI architecture playbooks from AI Architects @ AI Engineer — AI architect role, agent platforms, voice agents, agent auth (CIAM), trusted inference, team structure, monetization, and product survival. Use when designing org-wide AI systems, agent platforms, or CIO-ready inference; or when the user says "AI architect", "enterprise agents", "CIAM for agents", "AI that pays", "build-operate divide".---# Architect enterprise AIAction playbook from nineteen AI Architect track talks. **Do not summarize talks** — pick a workflow and execute it.**Supporting files:**- [workflows.md](workflows.md) — workflows A–M- [source-index.md](source-index.md) — src-NNN → learningsOptional deliverables: `{SKILL_OUTPUT_DIR}/architect-enterprise-ai/`---## Step 0 — Pick workflow```What is the user trying to do?├─ Define AI architect role & stack choices → A [src-015, src-009]├─ Ship agents that work in production → B [src-003, src-010]├─ Build agentic platform (Box-style) → C [src-004, src-005]├─ Voice agents → D [src-006]├─ Agent identity / authZ (CIAM) → E [src-007]├─ CIO-trusted inference & telemetry → F [src-008]├─ Browser-as-runtime for agents → G [src-019]├─ Developer experience (AX) → H [src-002]├─ Revenue / ROI proof (healthcare RCM) → I [src-001]├─ Feedback loops & learning products → J [src-011, src-013]├─ Monetization & GTM for AI → K [src-014, src-012]├─ Modern AI team structure → L [src-016]├─ Product strategy / knife fight → M [src-017, src-018]```Open [workflows.md](workflows.md).---## Install```bashcp -r skills/architect-enterprise-ai ~/.claude/skills/cp -r skills/architect-enterprise-ai ~/.cursor/skills/```Source: `playlists/ai-architects-ai-engineer/`.---## Cross-cutting rules| Rule | Source ||------|--------|| AI architect owns integration, tools, embeddings, vector DB | [src-015 @ 9:41] || Agents need production design patterns, not demos | [src-010] || Feedback loops beat one-shot prompts for quality | [src-011] || AuthN/AuthZ for agents is a first-class concern | [src-007] || Bridge build vs operate for AI product vision | [src-018] |---## Output to user1. Name workflow (A–M) and deliverable2. Artifacts under `./skill-outputs/architect-enterprise-ai/` when requested---## Invocation examples```@architect-enterprise-ai define our AI architect scopeagent auth model for enterprise SaaSprove ROI for our AI inference platform```

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