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# The New Agency Stack: How Dev Shops Use Claude, Cursor, and Copilot in Production

**[freeCodeCamp](https://daily.dev/sources/freecodecamp)** · 7 min read · 14 upvotes · 0 comments

## Summary

Dev agencies have shifted AI coding tools from experimental to production-standard. Most now use a three-layer stack: chat assistants (Claude, ChatGPT) for planning and architecture, AI-native editors (Cursor) for building features across codebases, and inline assistants (GitHub Copilot) for boilerplate. The real-world workflow keeps humans in the loop — engineers break work into small tasks, review every AI-generated line, and run code through normal pull request processes. AI has compressed MVP timelines from 4–6 months to 6–12 weeks and improved test coverage, but token costs for heavy agentic use are a new expense. A 'vibecode rescue' niche has emerged for fixing AI-built apps that hit stability walls. The agencies that succeed are those with senior engineers who know when to trust the tools and when to override them.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.freecodecamp.org/news/the-new-agency-stack-how-dev-shops-use-claude-cursor-and-copilot-in-production>

## Questions this post answers

### How much can an agency spend on AI agent token costs per engineer per month?

A team running AI coding agents all day can spend hundreds of dollars per engineer per month on model usage. For agencies this is still cheaper than additional salary costs, but it represents a new recurring expense line that did not exist a couple of years earlier, alongside the shift toward heavier agentic tool use.

_Teams weighing agentic AI costs against hiring can track real-world cost breakdowns like this on daily.dev._

### What questions should I ask to vet an agency that claims to use AI for development?

Ask who specifically reviews the AI's output, expecting named senior engineers and a real pull request process rather than a vague answer about quality checks. Also ask about automated test coverage and for concrete stories about times the AI got something wrong, since a team with no such stories likely hasn't shipped much production work.

_Founders comparing AI-powered dev shops can dig into vetting criteria like these on daily.dev._

### How has AI changed typical MVP development timelines and pricing at software agencies?

Agencies that used to quote four to six months for an MVP now commonly quote six to twelve weeks for the same scope, often starting around $30,000, with fixed-scope fixed-price offers becoming more common again since AI makes timelines for well-defined work more predictable.

_Anyone budgeting or negotiating an MVP build can benchmark these AI-era timelines on daily.dev._

---

Tags: [#github](https://daily.dev/tags/github), [#ai-coding](https://daily.dev/tags/ai-coding), [#claude](https://daily.dev/tags/claude)

[View this post on daily.dev](https://daily.dev/posts/the-new-agency-stack-how-dev-shops-use-claude-cursor-and-copilot-in-production-adj1t36it)

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