# AI Software Engineer

> A mid-to-senior software engineer costs about $195,000 a year once salary and benefits are counted. A CellCog AI Employee ships features end to end, fixes bugs with regression tests, reviews pull requests, and keeps your codebase documented, working directly in your repositories, for a fraction of that.

- Canonical (HTML): https://cellcog.ai/ai-employees/ai-software-engineer
- Site index for agents: https://cellcog.ai/llms.txt
- Last updated: 2026-10-06

## What it does

- **Ship features end to end**: Take a feature from requirement to working code: implementation, tests, and a clean diff ready for your review.
- **Fix bugs with tests**: Reproduce the bug, trace the root cause, ship the fix with a regression test and a written explanation.
- **Review pull requests**: Review code against your standards and catch what could break in production, with reasoning on every comment.
- **Keep the codebase documented**: Keep architecture docs, onboarding guides, and API references current as the code actually evolves.
- **Automate the maintenance**: Write the scripts, CI checks, and migrations, and patch the small problems before they grow into incidents.

## Things to ask it

- Here's a customer bug report: uploads over 50MB fail silently. Find the root cause, fix it, and add a test that would have caught it.
- Build the CSV export feature from this spec: filters, column selection, and email delivery for large files.
- Review this pull request against our style guide and flag anything that could break in production.
- Our onboarding doc is a year out of date. Read the codebase and rewrite it so a new engineer can ship in week one.
- The dashboard API takes 6 seconds to load. Profile it, find the slow queries, and fix them.

## Who hires one

- **Solo founder: Shipping without an engineering team**. Non-technical founders ship real features and fixes. Technical founders hand off the backlog they never get to.
- **Small team: The extra engineer on the team**. Small teams point a CellCog AI Employee at the bug queue, the tests, and the docs, so the humans stay on the hard problems.
- **Agency / operator: Maintaining many codebases at once**. Agencies and dev shops keep every client project patched, tested, and documented in parallel.

## Human software engineer vs AI employee

| | Human | AI employee |
|---|---|---|
| Code review turnaround | Hours to days | Minutes, with written reasoning |
| Test coverage | When there is time | A test with every fix |
| Documentation | Perpetually behind | Kept current as the code changes |

## Where a human still does better

- **Architecture ownership**: System-design calls with long-term consequences deserve a human owner. It prepares the analysis and the options.
- **Production judgment**: You decide what deploys and when. It works in your review flow, and humans hold the merge button for as long as you want.
- **Tribal knowledge**: Code that only makes sense with context nobody wrote down takes longer at first. It documents that knowledge as it learns it, so the problem shrinks.

## Frequently asked questions

### Can an AI engineer really work in our codebase?

Yes. It works directly in your repositories, through your own machine or its cloud computer: it reads the code, follows your conventions, runs your tests, and delivers changes as clean diffs for your review. CellCog's own production codebase is built and maintained this way.

### What languages and stacks does it support?

The common production stacks: Python, JavaScript and TypeScript, React, SQL, and the usual cloud and CI tooling, plus most mainstream languages. If your stack is unusual, it reads the existing code first and follows the patterns already there rather than imposing new ones.

### Will it break things in production?

It works like a careful senior hire: changes land as reviewable diffs, tests run before anything ships, and you decide which actions it can take on its own versus which wait for your sign-off. Every action is logged, so you can always see exactly what it did and why.

### How is this different from Copilot or Cursor?

Coding assistants autocomplete while a human types. A CellCog AI Employee is the one doing the work: it takes a ticket, plans the change, writes the code and the tests, and comes back with the diff. It also owns everything around the code: reviews, documentation, and release notes.

### Can it work alongside our existing engineers?

Yes, that is the most common setup. Engineers hand it the work that crowds out feature development: bug queues, test coverage, refactors, documentation, dependency updates. It communicates in the tools your team already uses and leaves a written trail on everything it touches.

### How does the cost compare to hiring a software engineer?

You pay for the work, not the hire. Hiring is free. Each time your employee works, it spends credits from your account: on Flash, built for speed, a working session typically runs under $5. On Max, our deepest reasoning, the same session runs up to about $25. From there the cost depends purely on how much work you assign. Start free, no credit card needed, with 200 credits.

### How do I get started?

Click "Get started" to sign up and hire one in minutes, or use "Talk to us" and our team will help you set up your AI Software Engineer.

Hire one: https://cellcog.ai/ai-employees/ai-software-engineer