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Replace residual em-dashes, arrow-notation shorthand, and a handful of filler intensifiers; fix two small typos. Add .gitignore to keep the working CHANGES.md audit out of the repo. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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| 02-errors-and-logs | ||
| 03-autocomplete | ||
| 04-conversations | ||
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| 07-local-models | ||
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| LICENSE | ||
| README.md | ||
Coding with AI
This is a practical guide to working effectively with AI coding assistants: web chat interfaces (ChatGPT, Claude, Gemini, Microsoft Copilot), in-project chat panels and CLIs (Claude Code, Cursor), autocomplete, and agentic tools. Our focus is on workflow and judgment: which tool to choose, what to paste, how to prompt, how to verify, and what to cite.
AI tools change quickly, but the patterns change more slowly. This guide aims at the patterns and uses current tools as examples.
A note on scope. This guide is about coding: writing, editing, refactoring, and debugging software. Students and engineers also use AI tools heavily for learning tasks: explaining concepts, summarizing literature, generating practice problems, study quizzes, mnemonics, working through homework, finding the right vocabulary for a half-remembered idea. The web-chat-vs-in-project framing here applies broadly, but the tools, examples, and tradeoffs for learning use cases are different enough to deserve their own guide.
Sections
| # | Topic | Description |
|---|---|---|
| 01 | Two worlds | Web chat versus tools that live with your code. Why the second is where coding work belongs, and the autocomplete/chat/agent spectrum within it. |
| 02 | Errors and logs | The canonical copy-paste case. How to frame what you paste so the assistant can actually help. |
| 03 | Autocomplete | Ghost-text suggestions as you type. What it's good for, the traps (especially in verification code), and when to escalate. Less central than chat or agents; skim or skip if you don't use it. |
| 04 | Conversations | Multi-turn design discussions in the in-project chat or a web chat, managing context, and when to start a fresh chat. |
| 05 | Agentic workflow | What agentic tools (Claude Code, Cursor agent, Microsoft Copilot agent mode) actually do, and how to supervise them. |
| 06 | Verifying and citing | Reviewing AI output for hallucinations and silent errors. Privacy and IP of what you paste. Attribution in academic and professional work. |
| 07 | Using local models | Local models as a cross-cutting alternative (privacy, cost, offline operation). Which tools support local across the autocomplete/chat/agent spectrum, and where the capability gap to cloud still matters. |
Who this is for
Students and practicing engineers who are already using AI assistants but want to use them more deliberately, including those whose default workflow is "ask ChatGPT, copy the answer back." There is nothing wrong with copy-paste, but our goal is to know when it is the right tool and when to use something else.
Prerequisites
- A working development setup (editor, terminal, version control). See computing-setup and cli-walkthrough for the underlying skills.
- Access to at least one AI tool. The examples use Claude and ChatGPT in web chat form, Claude Code or Cursor as in-project chat / agentic tools, and GitHub Copilot / Codeium / Microsoft Copilot interchangeably for autocomplete. University-provided access (e.g., Microsoft Copilot or Gemini through institutional agreements) works equally well for nearly everything covered here.
A note on tools and dates
Tool capabilities, pricing, and policies change frequently. Where this guide names a specific feature ("Cursor's agent mode," "Claude Code"), the description reflects what those tools did as of the first half of 2026. The underlying patterns (web chat versus tools that live with your code, and the autocomplete/chat/agent spectrum within the latter) are durable. Treat any tool-specific advice as illustrative.
License
MIT
Author
Eric M. Furst, University of Delaware