AI Systems Are Software Systems
Why production AI requires the same engineering discipline as any distributed system, and how this wiki covers the full stack of AI …
Software-Engineering
GitHub Actions Security: Risks, Exploits, and Hardening
A comprehensive guide to GitHub Actions security vulnerabilities, common exploit patterns, and how to audit and harden your CI/CD pipelines …
.gitignore Patterns and Best Practices
Build a Code-Based Video: Programmatic Video Production with Remotion
A step-by-step guide to creating professional demo and explainer videos entirely in code using Remotion, React, and AI-assisted development. …
Everything as Code: Treating All Artifacts as Software
The principle of defining infrastructure, configuration, documentation, policy, video, and design as version-controlled code artifacts - and …
Version Control Fundamentals and Git
KISS Principle - Keep It Simple
A design principle stating that systems work best when they are kept simple rather than made complex, favoring straightforward solutions …
Requirements Analysis
The process of eliciting, analyzing, documenting, and validating the needs and constraints that a software system must satisfy.
Software Configuration Management
The discipline of tracking and controlling changes to software artifacts, rooted in military standards and formalized by IEEE 828, …
Software Development Lifecycle (SDLC)
The structured process of planning, creating, testing, and deploying software systems through defined phases.
SWEBOK V4 Knowledge Areas Overview
Overview of the IEEE Software Engineering Body of Knowledge Version 4, covering its knowledge areas and relevance to AI/ML engineering.
Technical Debt
The accumulated cost of shortcuts, compromises, and deferred improvements in a software system that increase future maintenance effort.
UML Overview
The Unified Modeling Language, a standardized visual notation for specifying, constructing, and documenting software systems through 14 …
API - Application Programming Interface
What an API is, REST vs GraphQL vs gRPC, authentication patterns, rate limiting, and how AI services are accessed through standardized API …
Extreme Programming (XP)
Kanban for Software Development
Programming Languages for AI - Python, TypeScript, HCL
A practical guide to the three languages used across a modern AI stack: Python for agents and models, TypeScript for frontends and video …
Retry and Backoff Patterns for AI Services
Exponential backoff with jitter, retry budgets, and idempotency patterns for production AI systems. Why AI services require different retry …
The Agile Manifesto
The Scrum Framework
Waterfall Methodology
Event Sourcing
What event sourcing is, why it matters for AI audit trails and pipeline replay, its relationship to CQRS, and when to apply it in AI …
Feature Flags
What feature flags are, how they enable safe AI model rollouts, A/B testing, and instant rollback - and the tools available for implementing …
Feature Flags for AI Model Deployment
Using feature flags to safely roll out AI model changes: A/B testing models, canary deployments, gradual traffic shifting, and instant …
Property-Based Testing
What property-based testing is, why it is ideal for AI systems that cannot be tested with exact-output assertions, and the tools available …
Testing AI Systems - Unit Tests to Production Monitoring
A practical testing strategy for AI systems: property-based testing, integration testing with mocked models, evaluation frameworks, and …
AWS Amplify - Full-Stack App Development
Using AWS Amplify to deploy front-end applications, host static sites, and connect to AWS AI backends.
Event-Driven Architecture for AI
What event-driven architecture is, how S3 triggers, EventBridge, and Step Functions patterns enable scalable AI pipelines.
Hugo - Static Site Generator
Using Hugo to build fast, maintainable documentation sites and AI solution landing pages, with GitHub Pages and Amplify deployment.
Using Notion as an AI Backend - Databases, APIs, and Automation
Notion API for structured data, MCP integration, and using Notion databases as knowledge stores for AI agents. When it works and when to …