Pre-Action Authorization for AI Agents
Pre-action authorization checks every AI agent tool call before it runs. Learn how to gate reads, writes, code execution, and loops.
Agent Use Cases
MCP Execution Boundaries for Production Agents
MCP execution boundaries help production AI agents use tools safely. Learn what to control after tools are connected and before loops run.
Why Production AI Agents Need a Runtime Layer
The agent runtime layer is the production infrastructure between your framework and model. Why it decides durability, isolation, and recovery.
Guardrails for Production AI Agents: A Practical Guide
Real guardrails for AI agents in production: input validation, action allow-lists, sandboxing, cost ceilings, and human-in-the-loop. Patterns you can ship.
Building a Self-Correcting AI Agent with Reflection
How to build a self-correcting AI agent using the reflection pattern and persistent memory. A runnable Python loop that critiques and fixes its own output.
Agent Memory Architectures: Vector, Graph & Episodic
Compare the three agent memory architectures in 2026 — vector recall, knowledge graphs, and episodic buffers — with real latency numbers, failure modes, and a decision guide.
Cron-Driven Agents: Autonomous Workflows on a Schedule
How to build cron-driven AI agents that run autonomously on a schedule in 2026: the architecture, idempotency and failure handling, and the cost traps of always-on automation.
Inside OpenClaw: The Architecture That Hit 250K Stars (2026)
An architecture teardown of OpenClaw: the three-layer pipeline, the seven-stage agentic loop, and why a self-hosted chat gateway became one of the fastest-growing repos ever.
Multi-Channel AI Agents: Slack, Discord & WhatsApp (2026)
How to run one AI agent across Slack, Discord, and WhatsApp in 2026: the gateway pattern, session identity, per-channel quirks, and the state-sync problems nobody warns you about.
How Hermes' Self-Improving Agent Loop Actually Works (2026)
How Hermes Agent's self-improving loop works in 2026: the skill-generation mechanism, what it actually persists, and where the 40% task-time gains come from.