- Three Sources of Truth: Where Your AI Project Actually LivesWhy Checkpointing AI Work Means More Than Committing CodeLearn why AI-assisted projects need three sources of truth aligned: the codebase, the agent context, and the repository that preserves prompts, plans, and project guidance.AI Elixir Development Tools Workflows
- Prompts That Write Prompts: Meta Workflow GenerationTurn Repeatable AI Development Workflows into Versioned Project InfrastructureLearn how meta workflow generation turns prompts into reusable project commands, making AI development workflows durable, repeatable, and reviewable.AI Elixir Development Tools Best Practices Workflows
- Your AI Tooling Has a Home: Project vs. Global InfrastructureWhy Team-Ready AI Workflows Belong with the Code They GovernLearn when AI tooling should live globally versus in the project so shared workflows stay versioned, visible, and aligned with the codebase.AI Elixir Development Tools Best Practices Workflows
- Building Your AI Toolchain: Rules, Skills, Sub-Agents, and Slash CommandsHow to Layer AI Execution with Reusable Workflows Instead of Repeating PromptsLearn when to use rules, skills, sub-agents, and slash commands so your AI workflow scales with structured oversight instead of context-heavy repetition.AI Elixir Development Tools Best Practices Workflows
- Stop Repeating Yourself: How to Architect AI Workflows Like CodeApply DRY Thinking to AI Instructions with Axioms, Roles, and TasksIf you keep retyping the same AI instructions, you do not have a workflow. Learn a practical three-layer structure to keep coding agents consistent.AI Elixir Development Tools Best Practices Workflows
- The Editor Is the AgentWhy Checkpoint-Based AI Workflows Create ControlLearn the Ask → Plan → Agent workflow, a two-level safety net, and context discipline for checkpoint-based AI coding in Elixir.AI Elixir Development Tools Best Practices Workflows