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Monitoring the Context Window in LLM Applications

Monitoring the Context Window in LLM Applications

A 2025 guide to measuring, managing, and gating LLM context usage—tokens, occupancy, truncation, and drift. Practical patterns: slot-based memory, RAG, summaries, hard caps, and provider-aware telemetry.

Optimizing AI Agentic Workflows: Reducing LLM Calls for Enhanced Efficiency

Optimizing AI Agentic Workflows: Reducing LLM Calls for Enhanced Efficiency

A practical playbook to cut LLM calls—adaptive routing, one-shot multi-head prompts, deterministic tools, precise RAG, and caching—while protecting task success and user experience.

High-Level Design for a Conversational AI Evaluation Framework (Production Implementation)

High-Level Design for a Conversational AI Evaluation Framework (Production Implementation)

A production-ready design for implementing a conversational AI evaluation framework—data models, scoring pipeline, slice dashboards, CI gates, and canary rollout.

A Practical Framework for Evaluating Conversational Agentic AI Workflows

A Practical Framework for Evaluating Conversational Agentic AI Workflows

A production-ready framework to evaluate agentic conversational systems—task outcomes, conversation behaviors, and system reliability—plus datasets, judges, and a CI-friendly harness.