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Agent Framework

Core frameworks for building AI agents

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Agent Canary Deployment and Production Monitoring: From Prompt A/B Testing to Automatic Rollback

How do you know a prompt change is better, not worse? A systematic guide to canary deployment, quality gates, auto-rollback architecture, and continuous behavioral drift monitoring for agents in production.

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Agent Evaluation and Testing: From Vibe Checks to End-to-End Pipelines

Most teams evaluate agents by checking a few examples. Real evaluation needs layered metrics, non-rotting datasets, and judges that push back. This article provides runnable code patterns and a practical decision framework.

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Agent Memory Architecture: Working, Long-term, and Shared Memory Trade-offs

A systematic comparison of the three categories of agent memory -- working, long-term, and shared -- covering storage media, lifecycle, retrieval methods, typical frameworks, and design patterns, fully addressing agent personalization and multi-agent collaboration engineering.

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Agent Small-Model Finetuning and Edge Inference

Exploring how small language models are fine-tuned and deployed for agent workloads at the edge, balancing latency, cost, and accuracy for production AI agents.

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Agent Tool-Call Fault Tolerance: Timeouts, Retries, Fallbacks, Idempotency

A systematic guide to seven tool-call fault tolerance patterns: timeout hierarchy, exponential backoff with jitter, circuit breakers, fallback provider chains, recoverable error classification, structured validation, and idempotency keys -- keeping agents stable in unstable real-world environments.

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Agent Workflow Orchestration in Practice: Production Patterns from DAG to State Machines

Most agent workflows fail at the orchestration layer, not the model. A practical comparison of DAG, state machine, and visual builder approaches with production-ready code for error handling, human approval gates, and conditional branching.