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Run Docker Compose as a reliable Linux service with systemd. Type=oneshot units, restart policies, logs, updates, health checks, backups, and safe cleanup.

Compare Docker install methods on Ubuntu: official APT repo, docker.io, Snap, rootless mode, Compose plugin, and post-install security. Decision table and migration paths included.

Practical Ubuntu APT troubleshooting guide: fix held packages, broken dependencies, bad PPAs, and NO_PUBKEY GPG errors with a clear step-by-step workflow

Six proven multi-agent orchestration patterns for production AI systems: orchestrator-worker, sequential pipeline, fan-out, hierarchical, swarm, and mesh. Decision framework, failure modes, cost analysis, and observability.

Speculative decoding speeds up LLM inference 20-50% with zero quality loss. Draft-verify mechanics, EAGLE-3, P-EAGLE, n-gram, MTP, and setup for llama.cpp, vLLM, SGLang, TensorRT-LLM.

Master Go context for cancellation, timeouts, and request-scoped values. Covers HTTP handlers, database calls, background workers, goroutine leaks, and graceful shutdown.

Stop losing events between your database and message broker. Learn the transactional outbox pattern in Go with PostgreSQL, FOR UPDATE SKIP LOCKED, and a polling relay.

Vibe coding drifts, SDD promises structure -- but is it just waterfall with markdown? Learn when specs help, when they hurt, and how to find the useful middle ground.

SDD makes the specification the source of truth for AI coding. Learn the core workflow, how it differs from TDD and BDD, and the real costs and benefits.

Learn how ADRs, PDRs, and DDRs preserve intent, guide AI coding agents, and keep architecture, product, and design decisions close to code.

Learn how Go testing/synctest makes concurrent tests faster and more reliable with fake time, isolated bubbles, Wait, and deterministic async behavior.

Learn Go error handling architecture with wrapping, sentinel errors, custom types, errors.Is, errors.As, API boundaries, logging, and production patterns.

Is Google's A2A protocol actually useful in 2026? A practical review of A2A adoption, MCP overlap, security concerns, and when to use agent-to-agent protocols in production.

A practical guide to polling agent patterns in AI assistants — schedulers, queues, webhooks, durable workflows, state management, and tradeoffs for production systems.

A practical guide to the A2A Protocol for AI agents, explaining Agent Cards, tasks, messages, parts, artifacts, discovery, and architecture tradeoffs.

A practical comparison of A2A and MCP for AI agent systems, covering tools, agents, architecture patterns, overlap, security, and when to use both.

Learn how to implement the CQRS pattern in Go. This guide covers design principles, practical code examples, library recommendations (Watermill, Event Horizon), and architectural tradeoffs for building scalable, maintainable systems.