The 2026 Guide to AI-Assisted Development
Published by Self-published · Tech
Covers prompt engineering, AI coding assistants, and agent-driven development workflows for modern software engineers.
Who this book is for
Working developers who want to go well beyond autocomplete, junior developers and career changers who get a structured path plus appendices on programming basics, and team leads or engineering managers who need decision frameworks for AI tooling, evaluation, security, and staffing.
Table of contents
- The New Developer Workflow
- How LLMs Work (What Developers Need to Know)
- Prompt Engineering for Code
- Tool Calling and Function Use
- AGENTS.md and Project-Level Instructions
- IDE Configuration and Editor-Specific Features
- MCP (Model Context Protocol)
- WebMCP and the Agent-Ready Web
- Agent Skills and Reusable Workflows
- Context Management and Long-Context Strategies
- Managing Multiple Agents
- Agentic CI/CD and PR Automation
- Evaluation and Testing for AI-Generated Code
- Security, Guardrails, and Safe Tool Use
- Observability, Tracing, and Reproducibility
- From Demo to Production
- Building Your Portfolio
- Career Paths in AI-Augmented Development
Excerpt
This book is not about AI replacing developers. It is about developers becoming more effective by using AI as a tool. Think of AI coding agents the way you think about any powerful tool: a database, a testing framework, a CI/CD pipeline. The tool does not make decisions. You make decisions. The tool executes them faster, catches some mistakes, and handles repetitive work so you can focus on the parts that require judgment.
