I'm building an AI-assisted coding workflow, what should I use?

If you’re building an AI-assisted coding workflow, the best choice depends on whether you want autocomplete, chat, codebase reasoning, agentic task execution, or team workflow integration. A practical setup usually combines a few tools rather than relying on one.

Good options by use case

1) Best general-purpose setup

• IDE: VS Code or JetBrains
• AI assistant: GitHub Copilot or Cursor
• Why: Fast adoption, strong inline completion, chat, and code editing support.

2) Best for agentic coding / multi-file edits

• Cursor
• Claude Code
• Aider
• Why: These are stronger when you want the model to inspect a repo, make coordinated changes, and iterate on tasks.

3) Best for codebase Q&A and retrieval

• Sourcegraph Cody
• Cursor
• Custom RAG over your repo
• Why: Better when you need “where is this implemented?” or “how does this flow work?”

4) Best for enterprise/team workflows

• GitHub Copilot Business/Enterprise
• Sourcegraph
• Internal agent tooling
• Why: Permissions, policy controls, auditability, and team-wide consistency matter more here.

5) Best for open-source / self-hosted control

• Continue.dev
• Aider
• Open-source models via local inference
• Why: More control over data, models, and integration patterns.

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If you want a recommended stack

A strong default stack is:

• VS Code
• GitHub Copilot for inline completion
• Cursor or Claude Code for larger refactors
• Aider for repo-level scripted changes
• GitHub Actions / CI to validate AI-generated changes
• Tests + linters + formatter as hard gates

This gives you:

• fast day-to-day coding
• deeper repo edits
• automated verification

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How to choose

Ask these questions:

1. Do you want autocomplete or task execution?

   • Autocomplete: Copilot
   • Task execution: Cursor / Claude Code / Aider

2. Do you need privacy/control?

   • Yes: Continue, Aider, self-hosted models
   • No: hosted tools are simpler

3. Do you work in one repo or many?

   • One or a few: Cursor/Copilot is fine
   • Many repos/monorepo: Sourcegraph or custom retrieval can help

4. Do you need human-in-the-loop review?

   • You should, especially for production code

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Important workflow advice

No matter what tool you pick:

• keep tests mandatory
• use linting/formatting
• have the AI make small, reviewable diffs
• require human approval before merge
• consider PR templates and checklists

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My short recommendation

• If you want the easiest high-quality start: VS Code + Copilot
• If you want the best AI-native coding experience: Cursor
• If you want the most flexible repo-editing agent: Aider
• If you want enterprise knowledge + code search: Sourcegraph Cody

If you tell me:

• your IDE,
• language/framework,
• team size,
• and whether you want local or cloud AI,

I can recommend a specific workflow and tool stack.