· 7 min read · ai-agents
Agent Glass-Break Patterns: Controlled Escalation for Production
How to implement controlled escalation for AI agents using safeBins and network-level constraints to prevent production catastrophes.
ai-agentssecuritymcp-serverskubernetesorchestration
· 8 min read · ai-agents
When Agents Should Stop: Designing Safety Boundaries That Work
Stop conditions are a feature, not a failure state. Budget caps, progress checks, and exit contracts that make autonomous agents quit cleanly.
ai-agentsagent-safetyautomationagent-orchestrationreliabilitystop-conditions
· 8 min read · ai-agents
Building Agent Skills: A Pattern for Discoverable Capabilities
Moving beyond basic tool-calling to a composable skill pattern that makes agent capabilities discoverable and reusable across different frameworks.
ai-agentsllm-orchestrationsoftware-architecturemcp-serversagent-design
· 8 min read · ai-agents
Privacy-Routed LLM Inference: Keeping Sensitive Data Out of the Cloud
How to build a routing layer for AI agents that ensures sensitive data stays on local hardware while leveraging cloud LLMs for non-private tasks.
ai-agentslocal-llmprivacyollamakubernetessecurity
· 5 min read · ai-agents
Cognitive Memory for Agents: Vector Search vs Activation-Based Recall
Comparing vector databases and activation-based memory for AI agents. Trade-offs in latency, scale, and interpretability.
ai-agentsvector-databasesllm-memorycognitive-architecturepytorchfaiss
· 8 min read · ai-agents
Three-Layer Safety for Autonomous Agents: Stopping the Infinite Loop
Moving beyond prompt engineering to implement token-level schema enforcement, pre-execution gates, and shell-safe execution pipelines for AI agents.
ai-agentsllm-opsmcp-serversollamapydanticaiagent-safety
· 5 min read · ai-agents
Self-Improving AI Infrastructure: How Your Homelab Wiki Updates Itself
How to automate your homelab wiki with self-improving AI infrastructure
ai-agentsself-improving-systemshomelabautomationinfrastructurekuberneteslonghorn
· 6 min read · ai-agents
The 6-Layer Memory Architecture I Run for Claude Code
Open-sourcing the memory system behind my Claude Code setup: CLAUDE.md, path-scoped rules, wiki, vector search, cognitive memory. With the mistakes.
ai-agentsclaude-codememoryragllm-wikimcphomelabkubernetes
· 6 min read · ai-agents
Building Karpathy's LLM Wiki: A Production Homelab Implementation
Implementing Karpathy's LLM Wiki in a homelab with real-world lessons and gotchas
ai-agentsllm-wikihomelabkubernetesproxmoxinfrastructure
· 5 min read · ai-agents
Agent Credential Management: Two-Tier Service Accounts for Secure AI Agent Workflows
Managing agent credentials with two-tier service accounts: a secure approach for AI agent orchestration
ai-agentscredential-managementsecurityservice-accountsmulti-agent-systemskubernetes
· 3 min read · ai-agents
NVIDIA Container Toolkit: Why the Default Runtime Matters
Fixing default runtime misconfigurations in NVIDIA Container Toolkit for GPU workloads
nvidia-runtimecontainerdkubernetesai-agentsgpu-container
· 8 min read · ai-agents
Building MCP Servers with FastMCP: Stop Writing Boilerplate, Start Writing Tools
FastMCP makes building Model Context Protocol servers feel like FastAPI. Here's how to go from zero to a working MCP server in under an hour.
mcp-serversai-agentspythonllm-toolingdeveloper-tools
· 9 min read · ai-agents
Multi-Agent AI Systems: Architecture Patterns That Actually Work
A practical guide to designing multi-agent AI systems — orchestrator patterns, trust boundaries, and the tradeoffs I learned running agents in production.
ai-agentsmulti-agentllmarchitectureorchestrationmcp-servers