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production-agents

Browse 7 articles tagged with “production-agents”.

Articles tagged “production-agents

7 articles

A Traffic Light Showing Amber Beside a Circuit Board Pattern, Representing a Deliberate Pause in an Automated Workflow
Agent Architecture·16 min read

How to Build Agent Interrupt and Approval Checkpoints

How to pause an AI agent before high-stakes actions, persist full state through the approval window, and resume cleanly. Covers interrupt gates, approval queues, checkpointing, and EU AI Act compliance for production CX agents.

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A Control Panel With a Retry Button That Returns the Same Green Checkmark on Every Press, Showing Idempotent Operations
Best Practices·14 min read

How to Build Idempotent Tool Calls for AI Agents

Naive retry logic charges customers twice, sends duplicate emails, and fires double webhooks. Here's how to build idempotent tool calls for AI agents with idempotency keys, deduplication, and safe retries.

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A CX engineer reviewing latency dashboards on a laptop in a warm, naturally lit office
Knowledge & Memory·8 min read

Your Agent's Context Window Is RAM, Not Storage

Most agent failures trace back to one mistake: treating the context window like a database. Here's the RAM model that fixes attention dilution, latency spikes, and ballooning costs.

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Engineering team at a whiteboard mapping how AI agents call tools through a single governance layer
Tools & MCP·10 min read

MCP Without a Gateway Is a Production Liability

Raw MCP is great for prototyping. But production agents need audit trails, per-user identity, tool-level RBAC, and rate limiting, none of which the spec provides. Here's the gateway pattern that fills the gap.

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Developer Building Scoped Credentials for an AI Agent on a Laptop
Security & Compliance·13 min read

How to Build Production-Safe Credentials for AI Agents

After PocketOS lost its production database to a nine-second AI agent error, here's the credential model that would have stopped it: vaults, scoping, RBAC, and boundary tests.

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Circular diagram showing the five phases of the agent development lifecycle with arrows connecting each phase
Operations·14 min read

The Agent Development Lifecycle: Ship, Observe, Improve

Shipping an AI agent is easy. Keeping it reliable after launch is where most teams struggle. The ADLC gives you a structured approach: Intent, Build, Evaluate, Deploy, Observe -- and then do it again.

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JSON code showing an MCP tool description with annotations marking quality issues in red
Tools & MCP·13 min read

How MCP Tool Descriptions Break Your Agent

New research shows 97% of MCP tool descriptions have quality issues that hurt agent accuracy. Here's what the smells look like, why they matter, and how to fix them.

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