Security hardening for Claude Code agentic workflows
Sandbox agents, enforce least privilege, protect secrets, and defend against prompt injection in production Claude Code agentic workflows.
Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Sandbox agents, enforce least privilege, protect secrets, and defend against prompt injection in production Claude Code agentic workflows.
Keep dynamic Claude Code workflows cheap and fast with prompt caching, batching, tight context scoping, and deliberate multi-agent use.
Diagnose and fix the common failure modes of dynamic Claude Code workflows: runaway loops, wrong tool calls, and hallucinated arguments.
What to put in Claude Code context and what to leave out: durable vs disposable facts, just-in-time loading, fighting context rot, and subagent isolation.
Integrate MCP servers with Claude Code the right way: scoped auth, clear schemas, structured errors, retryable flags, and idempotency for safe agent actions.
Code-level patterns for Claude Code: progressive disclosure, narrow typed tools, context budgeting, verification loops, and idempotency — applied directly.
A hands-on walkthrough: project memory, a custom skill, an MCP server, an enforcement hook, and a subagent — wire a real Claude Code workflow today.
How Claude Code builds a fresh harness per task: the agent loop, skill discovery, MCP routing, context budget, and subagents, explained end to end.
How 2026 computer-use AI agents handle plumbing back-office work — updating CRM, filing job details, and paperwork after the call. Agentic AI explained.
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