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ai-lead-ops

Provide structured playbooks for AI platform operations, incident reviews, and rollout governance.

7|1|Updated May 19, 2026
Search Tags:#sre#incident-management#ai-ops#release-governance#cost-capacity#vendor-eval
One-click install
npx skills add https://github.com/daemon-blockint-tech/Agentic-Enteprises-Skill --skill ai-lead-ops
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-lead-ops
Source: https://github.com/daemon-blockint-tech/Agentic-Enteprises-Skill/tree/main/ai-lead-ops
Command: npx skills add https://github.com/daemon-blockint-tech/Agentic-Enteprises-Skill --skill ai-lead-ops

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Guides AI ops leadership—LLM SRE, model/prompt releases, eval/incidents, cost/capacity, vendors, and cross-functional cadence. Use for AI platform ops, LLM SLAs, incidents, rollout governance, unit economics, red-team/eval gates, and team rituals—not memory (ai-memory-developer), context code (ai-context-engineer), security programs (cybersecurity), token roadmaps (ai-token-improvement-plan-engineer), solution architecture (applied-ai-architect-commercial-enterprise), skills portfolio (ai-skill-manager), or vertical AI product eng management (engineering-manager-vertical-ai-products). Prompt/eval team management and golden-set release policy: engineering-manager-agent-prompts-evals. Safeguard inference platform: ml-infrastructure-engineer-safeguards. Safeguard model research: ml-research-engineer-safeguards.

Core Features & Use Cases

  • AI platform operations governance and release planning
  • Incident reviews, post-mortems, and cross-team cadences
  • SLOs, SLAs, and reliability governance for LLM features
  • Vendor evaluation, bake-offs, contracts, and risk management
  • Unit economics tracking, capacity planning, and cross-functional rituals

Quick Start

Create an AI ops cadence plan and template for the last release incident.

Frequently Asked Questions about ai-lead-ops

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up SLO tracking and reliability governance for LLM features?▼

AI platform ops governance provides structured playbooks for establishing SLOs, SLAs, and reliability tracking specifically for LLM features, ensuring consistent rollout control and cross-team accountability.

What is the best way to run incident reviews and post-mortems for AI platform operations?▼

Incident reviews for AI platform operations use structured post-incident templates to analyze LLM failures, document findings, and drive cross-functional cadences across engineering, research, and risk teams.

How do I manage release governance for model and prompt rollouts?▼

Release governance for model and prompt rollouts applies structured playbooks to control feature releases, enforce red-team and evaluation gates, and maintain operating model documentation.

Can I use this for AI vendor evaluations and unit economics tracking?▼

Yes, AI vendor evaluations and unit economics tracking are supported through structured templates for bake-offs, contract risk management, cost planning, and capacity optimization.

Does this handle AI platform capacity planning and cross-functional rituals?▼

AI platform capacity planning and cross-functional rituals are handled by providing cadence structures that align engineering, research, risk, and product teams on cost tracking and operational governance.

When should I not use this Skill for AI operations management?▼

Avoid using this Skill for context engineering, security programs, token roadmaps, solution architecture, skills portfolio management, or vertical AI product engineering, as it focuses strictly on platform ops governance.

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