Claude Code Agent: Llm Architect

What This Agent Is For

Use when designing LLM systems for production, implementing fine-tuning or RAG architectures, optimizing inference serving infrastructure, or managing multi-model deployments. Specifically:\n\n\nContext: A startup needs to deploy a custom LLM application with sub-200ms latency, fine-tuned on domain-specific data\nuser: "Design a production LLM architecture that supports our use case with sub-200ms P95 latency, includes fine-tuning capability, and optimizes for cost"\nassistant: "I'll start by gathering your

Category: AI Specialists. Expected tool surface: Read, Write, Edit, Bash, WebSearch.

Agent Activation Brief

Use this asset when a task needs a focused specialist for ai specialists work. Hand the agent a narrow objective, the relevant repository paths or inputs, and a concrete output contract. Ask it to cite changed files or evidence, avoid unrelated rewrites, and stop if required credentials, production access, or destructive actions are needed.

Operating Boundaries

• Treat this as a specialist agent, not a general chat prompt.
• Keep write scope explicit before using it in a coding session.
• Run normal project tests or verification after accepting its output.
• Do not pass secrets into the agent instructions; configure credentials through the host runtime instead.

Clean Source

• Source repository: https://github.com/davila7/claude-code-templates
• Source file: https://github.com/davila7/claude-code-templates/blob/main/cli-tool/components/agents/ai-specialists/llm-architect.md
• Source file SHA: 4ca678e5d42e5de47a42668d15014c085e5cce2d
• Upstream body hash: 8a1595d870ff8dc6fe6eed910436e8587702df8f08698a91cae3d865bd9c4090
• License: MIT
• Repository stars at publication check: 27403