AI Ops
Running AI systems in production
AI Agent Memory: Sessions, Long-Term State, and Retrieval
Tutorials AI OpsDesign AI agent memory without a data swamp: session state, durable facts, retrieval, provenance, conflicts, privacy, deletion, and production evaluation.
MCP Security: OAuth, Tool Permissions, and Prompt Injection
Tutorials AI OpsSecure remote and local MCP servers with OAuth audience binding, least-privilege tools, prompt injection defenses, sandboxing, audit logs, and tests.
Production LLM Stack: Routing, Evals, Cost, Reliability
Tutorials AI OpsA practical production LLM stack: request contracts, model routing, tools, validation, observability, evals, cost controls, fallbacks, and safe rollouts.
Testing AI Agents: How to Know Your Agent Actually Works
AI OpsA practical guide to testing AI agents: unit/integration/e2e tests, eval frameworks (DeepEval 4.0, RAGAS, Promptfoo, Braintrust), metrics, CI/CD pipeline. With code examples.
Context Engineering vs RAG: When to Use Which
AI OpsA deep comparison of context engineering and RAG: when long context replaces retrieval, when you actually need RAG, a decision framework, and the modern 2026 stack.
AI Agents: The Complete Guide - What They Are, How to Build Them, Where to Use Them
AI OpsA complete guide to AI agents: architecture, frameworks (LangGraph, CrewAI, OpenAI Agents SDK, Google ADK, Pydantic AI, MCP), practical use cases, and a hands-on tutorial.
Prompt Library Template: A 5-Part Framework
Tutorials AI OpsA 5-component prompt template for building a reusable library. Structure, examples for different tasks, plus organization and versioning of a prompt library.
LLM Cost Optimization: Measure Cost per Successful Task
Cases & Practice AI OpsReduce LLM spend without hiding quality loss: attribute costs by task, remove waste, set output budgets, test smaller models, use caching safely, and control retries.
Kronos Agent OS: a self-hosted runtime for durable AI agents
Engineering AI OpsAn evidence-based tour of KAOS v0.3.0: durable turns, layered memory, MCP tools, governance, behavior evals, portable agent state, and safe defaults.
Human-in-the-Loop for AI: Approval Gates That Work
Tutorials AI OpsDesign human oversight for AI actions with risk tiers, approval state machines, calibrated routing signals, reviewer UX, queue SLAs, audit logs, and release metrics.
Langfuse Prompt A/B Testing: Offline First, Then Canary
Tutorials AI OpsRun prompt experiments on a fixed dataset first, then canary two labeled versions in production. Includes sticky assignment, guardrails, and tested code.
Langfuse Prompt Management in Python: Versions, Evals, Rollbacks
Tutorials AI OpsBuild a Langfuse prompt workflow in Python: get_prompt(), compile(), version labels, dataset evals, trace linking, canaries, and safe rollback.
Multi-Agent Architecture Patterns: When One AI Isn't Enough
Tutorials AI OpsMulti-agent system architecture patterns for production: Sequential Pipeline, Parallel Fan-Out, Classifier+Router orchestration, task routing, agent specialization with code examples.
LLM-as-Judge: Build a Calibrated Quality Gate
Tutorials AI OpsDesign an LLM judge with narrow rubrics, human calibration, deterministic checks, bias tests, CI gates, production sampling, and safe handling of untrusted outputs.