·Artificial Intelligence
Module 7 Lesson 1: What Hallucinations Are
Why does an AI sometimes lie with total confidence? In this lesson, we define 'Hallucinations' and learn to identify the difference between a creative slip and a factual failure.
reliability
16 articles
·Software Development
Vibe Coding vs. Formal Verification: Bridging the Gap
Why 'It feels right' is not a unit test. Learn how to combine the speed of LLM 'Vibe Coding' with the safety of formal verification for mission-critical agents.
·DevOps
Module 6 Lesson 1: Service Dependencies and Startup Order
Master the timing of your stack. Learn how 'depends_on' works and how to use 'wait-for-it' scripts to ensure your app only starts after the database is truly ready.
·DevOps
Module 6 Lesson 3: Healthchecks and Restart Policies
Build a self-healing stack. Learn how to configure advanced healthchecks and restart policies directly in your Compose file to automate recovery from crashes.
·DevOps
Module 6 Lesson 4: Docker Healthchecks
Is your app actually alive? Learn how to define HEALTHCHECK instructions in your Dockerfile so your orchestrator can detect and fix 'Zombie' containers.
·DevOps
Module 10 Lesson 4: Designing for Resilience
The 'Anti-Fragile' pipeline. Learn how to write CI/CD scripts that can handle network failures, registry timeouts, and flaky tests without completely stopping your company's delivery engine.
·Automation
Module 9 Lesson 1: Wait & Backoff Strategies
Patience pays off. Learn how to use the 'Wait' node for more than just pauses, including how to implement custom backoff strategies to handle intermittent API failures.
·AWS Bedrock
Module 13 Lesson 1: The Planner-Executor Pattern
Division of Labor. How to split 'Thinking' and 'Doing' between two different agents for higher reliability.
·Agentic AI
Module 12 Lesson 1: Why Agents Hallucinate
Understanding the glitch. The psychological and technical causes of AI hallucinations in agentic systems.
·Agentic AI
Module 12 Lesson 4: Self-Correction Loops
The double-check. Implementing internal loops where one agent reviews and corrects the errors of another.
·Agentic AI
Module 14 Lesson 1: The Reliability Gap
Why LLMs aren't enough. Understanding the limit of probabilistic reasoning in deterministic business systems.
·Agentic AI
Module 6 Lesson 4: Deterministic Execution
Stability in the graph. Using edges and state counters to prevent infinite loops and ensure predictable behavior.
·Agentic AI
Module 7 Lesson 2: Loop Guards
Setting boundaries. How to implement hard limits on cycles and token usage within your agent graphs.
·Agentic AI
Module 7 Lesson 3: Retry and Fallback Nodes
Resilience by design. How to handle tool failures and rate limits within the agent graph.
·Artificial Intelligence
Architecting Resilient Autonomous Agents for Production
A deep dive into building reliable, production-ready autonomous agent systems, focusing on error handling, state management, and observability.
·Artificial Intelligence
Self-Healing AI Agents: How to Build Resilient AI Systems
Why most AI agents fail in production and how to build systems that detect, correct, and learn from their own errors.