Tooling 7 min
Test-Driven AI Coding: Closing the Red-Green Loop
How to feed failing tests directly to your AI coding assistant and use TDD as a feedback loop that keeps AI-generated code correct from the first run.
Josh
[ Tag ]
#workflow
16 articles
Tooling 7 min
Multi-Model AI Coding Workflows: Routing Tasks to the Right Model
Most developers default to one model for everything. Here's a practical framework for matching each coding task to the right model — cutting costs without sacrificing quality.
0degrees Team
Agents 6 min
Parallel AI Agent Workflows: Fanning Out Tasks to Multiple Agents
How to identify independent workstreams, fan them out to multiple AI agent sessions simultaneously, and merge results without conflicts.
0degrees Team
Production 6 min
Keeping Secrets Out of Your AI Coding Sessions
A practical guide to sharing the right context with AI assistants without exposing API keys, credentials, and sensitive data that creates security risk.
0degrees Team
Tooling 7 min
Writing a CLAUDE.md That Actually Changes How Your AI Codes
How to write a project instruction file that reliably steers AI coding assistants toward your conventions — what to include, what to leave out, and how to test it works.
0degrees Team
Tooling 7 min
Prompting AI for CI/CD: Writing Pipelines That Actually Deploy
How to give AI coding assistants the context they need to write GitHub Actions, Dockerfiles, and CI pipelines that work — not just pipelines that look like they work.
Josh
Tooling 7 min
Documenting Code with AI: Keeping Docs Honest
How to get AI coding assistants to write documentation that accurately reflects your code — not plausible-sounding summaries that drift from reality.
0degrees Team
Tooling 7 min
AI-Assisted Git: Writing Better Commits and PR Descriptions
How to use AI to write commit messages, pull request descriptions, and changelogs that actually communicate intent — and where the workflow breaks down.
Josh
Tooling 7 min
Using AI to Review Your Own Code Before It Ships
How to use AI coding assistants as a first-pass code reviewer — prompting for real feedback on code you wrote, interpreting what it finds, and fitting it into your workflow.
0degrees Team
Tooling 7 min
Briefing AI on Your Codebase: The Architecture Context That Actually Matters
How to give an AI coding assistant exactly the architectural context it needs to write code that fits your project — without overwhelming it with noise.
0degrees Team
Agents 6 min
Task Decomposition for AI Coding Agents: How to Break Down Complex Features
How to split a complex feature into agent-sized sub-tasks that execute reliably — with concrete patterns and scope rules that prevent drift and rework.
Josh
Tooling 7 min
Upgrading Dependencies with AI: A Systematic Migration Workflow
How to use AI coding assistants to navigate major library upgrades — feeding changelogs, mapping the breaking change surface, and validating the result.
Josh
Agents 7 min
Steering a Drifting AI Agent: How to Correct Course Mid-Task
Practical techniques for recognizing when an AI coding agent has gone off track and redirecting it effectively — before it digs you deeper into the wrong solution.
Josh
Tooling 7 min
Using AI to Explore Unfamiliar Codebases
How to use AI coding assistants as a guide when navigating code you didn't write — from getting an architectural overview to tracing execution paths.
Josh
Tooling 6 min
Refactoring with AI: A Step-by-Step Strategy for Modernizing Legacy Code
How to use AI coding assistants for safe, incremental refactoring — scoping the work, writing safety tests, reviewing generated diffs, and avoiding common pitfalls.
Josh
Tooling 7 min
Managing Context in Long AI Coding Sessions
How to keep AI coding assistants accurate across a long feature branch — when to trim, reset, and summarize context so the model stays focused.
Josh