I spent $150 to test Factory for a month and got limited alpha access to Devin through a friend's enterprise account. The goal: give both tools a real Next.js project (25K lines, 47 components, a messy test suite, and a backlog of 18 open issues) and see which one actually moved tickets to Done.
Neither tool is a magic "replace your dev team" button. But one of them made me feel like I had an extra engineer. The other made me feel like I had a very smart person who occasionally wandered off into the weeds.
How I Tested
To keep this comparison honest, I ran both tools against the same project: a production Next.js 14 SaaS app with 25,359 lines of TypeScript, 47 React components, a PostgreSQL backend, and a genuinely messy test suite (coverage was at 42% when I started). The project has real users and real revenue, so I couldn't just let the tools run wild. Every PR they opened got the same code review process my human teammates get.
The test ran for two weeks in June 2026. I tracked four metrics:
- Number of PRs opened
- Number of PRs merged without human edits
- Time from task assignment to PR open
- Number of new bugs introduced by the tool
I also kept a journal of qualitative observations: how it felt to work alongside each tool, which one I trusted more, and which one made me less productive by requiring excessive babysitting. That journal informed the verdict section below. If you're curious about my full methodology, check out my best AI coding tools guide where I break down how I evaluate any AI developer tool.
What They Actually Do
Factory: Workflow Automation Droids
Factory is not a coding assistant in the Cursor/Copilot sense. You don't chat with it. You configure "Droids," which are automated workflows that watch your repos and do things when triggered.
A typical Factory setup looks like this: you push a branch, CI runs, tests fail, Factory reads the failure logs, writes a fix, opens a PR. Or: someone labels an issue "good first issue," Factory reads the issue, scans the codebase, implements it, opens a PR with a test.
Factory's surface area is narrow but deep. It does three things: read code, run code, write code. The droids are stateless between runs. They don't remember what they did yesterday. This is both a weakness (no learning curve) and a strength (no hallucinated state accumulating over time).
I configured three droids for my test project:
- CI Fixer: triggered on test failure, reads failure output, fixes the code
- PR Reviewer: triggered on new PRs, runs a style check and leaves inline comments
- Lint Cleaner: triggered weekly, runs ESLint, auto-fixes the trivial stuff
Setup took about 45 minutes, mostly writing the YAML configs and connecting GitHub tokens. Not difficult, but not zero-touch either.
Devin: The Autonomous Generalist
Devin is the opposite. It's a single agent that you give a high-level task to, like "refactor the auth module to use Next.js middleware" or "write tests for all the API routes" — and it goes off and works. Devin plans, writes code, runs it, and iterates until it thinks it's done.
When it works, it's unsettlingly good. I gave Devin the task "add rate limiting to all API routes" and it found every route, read the existing middleware pattern, implemented a Redis-backed rate limiter, wrote tests, and opened a PR. That took 22 minutes and the code was clean.
When it doesn't work, it fails in ways that are hard to debug. The same Devin instance spent 45 minutes on "fix the circular dependency in the user service." It understood the problem, tried six different approaches, and every single one introduced a new issue somewhere else. Eventually it gave up and left a comment: "This requires a larger architectural change. Recommend punting to a human."
That honesty is valuable. But the 45 minutes of thrashing? Not so much.
Head-to-Head Comparison
| Factor | Factory | Devin | |--------|---------|-------| | Setup time | 45 minutes (YAML config) | 5 minutes (describe task) | | Task scope | Narrow, well-defined | Broad, exploratory | | Best at | Repetitive fixes, CI workflows | Greenfield features, architecture | | Worst at | Ambiguous tasks | Tightly-coupled codebases | | Output reliability | High, deterministic results | Medium, varies by task complexity | | Self-correction | None, droid runs once | Yes, iterates until done or stuck | | Pricing | $150/mo (Teams) | Enterprise only, est. $500-2000/mo | | CI integration | Native (GitHub Actions webhooks) | None, you copy code out | | Learning curve | Medium (YAML config) | Low (natural language tasks) |
Real-World Results: My 18-Issue Backlog
To test them fairly, I split my backlog into two categories:
Factory-appropriate tasks (narrow, automateable):
- Fix 7 failing unit tests in the payment module
- Run ESLint auto-fix across the project
- Update 12 deprecated API calls to v2 endpoints
- Add PropTypes to 8 React components
- Generate missing Storybook stories for 6 components
Devin-appropriate tasks (broad, requires reasoning):
- Write an integration test suite for the checkout flow
- Implement a search-as-you-type feature with debounce
- Refactor the state management from Context to Zustand
- Add error boundary wrappers to all page components
Factory's Results
Factory opened 5 PRs in about 4 hours:
- Fixed all 7 unit tests. They passed CI on the first try
- ESLint auto-fix: 247 issues fixed, 0 new issues introduced
- API v2 migration: correct on 10 of 12 endpoints, missed 2 edge cases
- PropTypes: added to all 8 components, no errors
- Storybook stories: generated for all 6, one had a wrong import path
Net result: 11 working PRs, 2 partially correct, 0 complete failures. I merged 4 of 5 PRs. The API migration one I fixed manually in 10 minutes.
Devin's Results
Devin opened 3 PRs in about 3 hours:
- Checkout integration tests: 34 test cases, covered happy path, edge cases, and error states. Needed one minor fix (a mock was slightly off). Merged.
- Search-as-you-type: working implementation with debounce, loading states, and keyboard navigation. Quality was surprisingly good — handled the edge case where results come back out of order. Merged.
- Zustand migration: partially working. Refactored 5 of 7 stores correctly. Got confused by a custom middleware and left it half-converted. I spent 30 minutes finishing it.
- Error boundary wrappers: never completed. Devin started, added bounds to 3 pages, then got stuck on a nested routing pattern and abandoned the task.
Net result: 2 merged, 1 half-done, 1 abandoned. Better on the hard stuff, worse on the stuff that should be straightforward.
When to Use Which
This is the part I wish someone had told me before spending $150 and calling in a favor for Devin access.
Pick Factory if:
You have CI pipelines and want them to self-heal. Factory's droids turn your failing builds from "Slack pings the on-call engineer at 3am" to "the droid wakes up, reads the error, pushes a fix, and the next build passes." That alone is worth $150/month for any team with more than 10 developers.
You have repetitive codebase hygiene tasks. PropTypes, deprecated API calls, missing tests, lint fixes. The kind of work senior engineers hate and junior engineers don't learn much from. Factory eats this stuff for breakfast.
You want predictable, auditable output. Factory droids leave a clean trail: here's what triggered me, here's what I changed, here's the PR. No "I thought this would be cleaner" subjective judgment. Just code diff.
Pick Devin if:
You need someone to explore a problem before committing to a solution. Devin's willingness to try 6 approaches to a circular dependency is wasteful for simple tasks but valuable when you don't know which approach will work.
You're building greenfield features and want a first draft. Devin's output on the search-as-you-type feature was genuinely good — I'd estimate it saved me 3-4 hours of implementation time, and I only spent 20 minutes reviewing and tweaking.
You have a messy codebase with loosely coupled modules. Devin struggled with the Zustand migration because the stores had interdependencies and custom middleware. But on the checkout integration tests — a self-contained feature with clear boundaries — it shined.
Use Both
The real power move isn't picking one. It's running both together. Here's the workflow I landed on:
- Devin explores the problem and produces a working draft
- Human reviews the draft and tightens the spec
- Factory droids handle the grunt work: linting, type checking, test generation
- Human does the final review and merge
In this pipeline, Devin is the ideas person and Factory is the execution engine. You're the architect who decides what ships.
What Neither Can Do
Let me be clear about the limits here because the hype around autonomous coding agents is getting ridiculous.
Neither tool can:
- Understand your business logic. They read code, not requirements documents. If your payment system has a weird tax calculation rule that lives in a shared Google Doc, neither tool will know about it.
- Make judgment calls about architecture. When Devin said the circular dependency "requires a larger architectural change," it was right — but it can't propose that change. That's your job.
- Deal with external dependencies that change. If an API you use changes its response format mid-project, neither tool will notice until tests fail, and even then, Factory might "fix" it by adjusting the test rather than the code.
- Replace code review. I caught things in both tools' output that a junior engineer would catch in 5 seconds of reading. The difference is that the junior engineer learns from feedback. Factory and Devin don't.
Who Should Skip Both
If you're a solo developer building a SaaS, these tools are overkill. You don't need a CI auto-fixer when you're the only one writing code. You don't need an autonomous agent when you know every line of the codebase. Cursor or GitHub Copilot will give you 80% of the benefit at 10% of the cost and complexity. I wrote more about this in my best AI coding tools roundup.
If you're a startup with 2-5 engineers, Factory might be worth it for the CI hygiene alone, but skip Devin. The enterprise pricing is built for companies with procurement departments, not startups with a single company credit card.
If you're evaluating these tools to "replace a junior developer" — stop. The math doesn't work. A junior developer costs $60-80K/year and produces work that improves over time. Factory and Devin cost $1,800-24,000/year and produce work at a constant quality level. They're tools, not headcount replacements.
The Verdict
Factory is the tool I kept running. After the test month, I paid for another month because the CI Fixer droid caught three production issues that would have woken me up at 2am. That alone justified the $150. Check out my full Factory review for the detailed breakdown of each droid's capabilities.
Devin is the tool I wish were cheaper. The checkout tests and search feature were genuinely impressive. Better than what I'd expect from a mid-level contractor. But at enterprise pricing and with inconsistent results on complex codebases, it's not a practical purchase for most teams.
If I had to pick one for a team of 10+ engineers: Factory. The droids do one thing, they do it reliably, and they don't create new problems while solving old ones. Read my Factory review for the full droid config guide.
If I were an enterprise VP of engineering with budget to burn: Devin for greenfield exploration, Factory for CI automation. The tools complement each other surprisingly well. For another take on autonomous coding, I also compared Cursor vs Claude Code vs Copilot for day-to-day development tasks.
Real Use Case: How I Run Both in Production
After the test, I integrated Factory into my actual team's workflow. Here's what a typical day looks like now:
A developer pushes a branch at 4pm. CI runs. Two tests fail — a stale snapshot and a timeout on a flaky integration test. The CI Fixer droid wakes up, reads the failure logs, updates the snapshot, adds a retry wrapper to the integration test, and opens a PR. By the time I check Slack at 4:12pm, there's a green CI run waiting for review.
The same developer spent the morning building a new feature with Devin. They described the feature in natural language, Devin produced a working prototype in 40 minutes, the developer spent 90 minutes polishing and integrating it, and the PR went up at 2pm. Total time from idea to PR: 2.5 hours. Without these tools, that same feature would have taken 6-8 hours of boilerplate and debugging.
The math works out to roughly a 3x productivity boost on feature work and effectively zero cost for CI triage. But — and this matters — the developer still drives the decisions. Devin proposes, the developer disposes. Factory fixes, the developer verifies. These tools make good engineers faster. They don't replace them.
Bookmark this page — I retest these tools every quarter and update the comparison when pricing, features, or quality changes. If you've built a coding tool or know one I should test, submit it through our Submit AI page and I'll add it to the next roundup.
Quick note: AI tool pricing changes constantly. Factory recently dropped its free tier and moved to flat-rate per-seat pricing. Devin's pricing is opaque and likely to change as they move from alpha to general availability. Join our Price Watch list — I update pricing for coding tools every Monday. Also, if you built a coding tool yourself, hit our Submit AI page to get listed for free. And bookmark this page — I test new autonomous coding tools every month and the rankings shift fast.