Agents

AI Agent Memory: Architecting Persistence Beyond Context Windows

AI agents are revolutionizing how we interact with technology, but their ability to perform complex, multi-step tasks is often limited by a fundamental...

Architecting Dev Environments for AI Coding Agents: A Guide

Software development is shifting from simple code generation to AI agents that plan, execute, and iterate on complex tasks. Empowering these agents...

Build Resilient AI Agents Against Opaque LLM Provider Behavior

Building robust AI agents requires more than just powerful LLMs; it demands foresight against the inherent unpredictability of proprietary LLM...

Auditing AI Agents: Security, Cost, and Compliance in Production

The deployment of AI agents in production environments marks a significant leap in automation, offering unparalleled capabilities for complex,...

Operational Safety: Resource Limits & Circuit Breakers for AI Agents

Autonomous AI agents offer transformative potential, but their ability to act independently also introduces significant operational risks, including...

Controlling AI Agents: Guardrails for Safe, Cost-Effective Deployment

Autonomous AI agents promise to revolutionize workflows by intelligently planning and executing multi-step tasks across diverse tools and data sources....

Observability for AI Agents: Prevent Costs, Boost Security

Autonomous AI agents represent a significant leap in automation, capable of planning and executing multi-step tasks. However, this power introduces...

Defending AI Agents: Mitigating Action-Oriented Data Injection

The rise of AI agents marks a significant shift in automation, empowering systems to autonomously plan and execute multi-step tasks using a suite of...

Architecting Durable AI Agents: Mastering Context & State with Model Context Protocol

The promise of AI agents—software that uses large language models LLMs to plan and execute multi-step tasks with tools—hinges on their ability to...

AI Coding Agents: Boost Productivity & Understand Limitations

AI coding agents are transforming the developer workflow, moving beyond simple autocomplete to provide autonomous, multi-step assistance across the...

Timeless Security for AI Agents: Applying Proven Principles

The rapid evolution of AI agents is transforming how developers build applications, moving beyond simple chatbots to autonomous systems capable of...

Essential Credential Security for AI Agents: A Developer Guide

As AI agents become increasingly sophisticated and integrated into complex workflows, their ability to interact with external systems – from databases...

Building MCP-Compliant AI Agents: A Developer's Handbook

The rise of AI agents has ushered in a new era of autonomous software, capable of planning and executing multi-step tasks. However, the true power of...

Architecting Resilient AI Agents for Production Safety

As AI agents move from experimental prototypes to critical production systems, ensuring their safety and resilience becomes paramount. Unlike...

Least-Privilege Setup for AI Coding Agents

AI coding agents can save hours, but they can also turn a bad prompt, poisoned repo, or overpowered tool call into a real incident. The safest pattern...

Prevent Prompt Injection in AI Coding Agents

AI coding agents are vulnerable to prompt injection because they read and act on untrusted text from repos, docs, issues, search results, RAG stores,...

How to Sandbox AI Coding Agents Safely

AI coding agents are safest when you assume they will eventually run the wrong command, install the wrong package, or follow a malicious instruction...

Safe AI Coding Agents in Production: Practical Guardrails

AI coding agents can be used in production safely, but only when you treat them like powerful junior operators with fast hands and incomplete judgment....