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agentic-development

Provides practical agentic development guidance covering workflows, tools, prompts, and debugging.

49|7|Updated Oct 18, 2025
One-click install
npx skills add https://github.com/Exploration-labs/Nates-Substack-Skills --skill agentic-development-exploration-labs
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agentic-development
Source: https://github.com/Exploration-labs/Nates-Substack-Skills/tree/main/agentic-development
Command: npx skills add https://github.com/Exploration-labs/Nates-Substack-Skills --skill agentic-development-exploration-labs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Traditional software development methodologies often hinder the efficiency of AI agents, leading to over-engineering and frustration. This Skill provides a pragmatic, "just talk to it" approach to agentic development, optimizing for speed, iteration, and developer well-being.

Core Features & Use Cases

  • Efficient Agent Workflows: Guides on parallel agent management, blast radius thinking, and interrupting agents for active steering, maximizing velocity.
  • Optimized Prompting: Advises on model-specific prompt strategies, emphasizing shorter prompts for capable models and the power of screenshots for visual context.
  • Tool & Model Selection: Offers insights into model economics, characteristics (GPT-5-Codex vs. Claude Sonnet), and the benefits of CLIs over complex MCPs.
  • Refactoring & Testing: Recommends using agents for low-focus refactoring tasks and generating tests in the same context to catch immediate bugs.
  • Use Case: You're struggling with managing multiple AI agents on a large codebase. Use this skill to learn how to run parallel agents in one folder, effectively use screenshots for context, and refactor code efficiently without burning out.

Quick Start

I'm starting a new project with AI agents. How should I set up my workflow for maximum efficiency, and which model should I choose for coding tasks?

Frequently Asked Questions about agentic-development

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I manage multiple AI agents working on the same codebase efficiently?▼

Run parallel agents in separate folders with blast radius thinking to isolate changes. Use screenshots for visual context and interrupt agents actively for steering. This maximizes velocity while keeping coordination overhead low.

What's the best way to prompt AI models for coding tasks?▼

Use shorter prompts for capable models like Claude Sonnet, and leverage screenshots to provide visual context. Model-specific strategies matter: GPT-5-Codex and Claude Sonnet have different strengths for code generation.

How should I set up my workflow when starting agentic software development?▼

Agentic workflows prioritize speed and iteration over traditional methodology. Set up agents for parallel execution, use CLI tools over complex MCPs, and optimize prompts for your chosen model to reduce over-engineering.

Can I use AI agents for refactoring and test generation together?▼

Yes. Assign low-focus refactoring tasks to agents and generate tests in the same context to catch bugs immediately. This approach reduces burnout and maintains code quality in large codebases.

What are the limitations of agentic development for large projects?▼

Coordination complexity increases with agent count and codebase size. Careful context management, blast radius planning, and active steering are required to prevent cascading failures and maintain output quality.

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