Automatically generate, review, and improve code with AI

Takes a plain-English coding task, writes the code, reviews it, and saves the reviewed result.

How the work actually flows

It repeats. Repeats code fails quality bar; it retries when a step fails.

Pattern: Structured Loop (21)

flowchart TD trig(["coding task scheduled or submitted"]):::trigtime s0["ai writes code"]:::task s1["ai reviews and scores code"]:::task s2["commit code to github"]:::svc s3["notify team with review report"]:::task trig --> s0 s0 --> s1 s2 --> s3 lp{"passing quality score threshold"}:::gate s1 --> lp lp -. "code fails quality bar" .-> s0 lp -->|"finished"| s2 out[/"reviewed code committed to github"/]:::out pay{{"faster releases with consistent quality"}}:::pay s3 --> out out --> pay s2 -. "retries on failure" .-> s2 classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
Starts itA stepAn outside serviceRepeat or finishResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
Knowledge Base & RAGMessaging & NotificationsSpreadsheet & Database OpsFile & Cloud Storage
Connects
CursorGitHubGoogle DriveGoogle SheetsSlack

The problem it solves

Your dev team spends real hours writing boilerplate code and doing manual code reviews before anything gets merged. Inconsistent reviews and refactoring slow releases down, especially when the same routine fixes come up over and over.

Who it fits

Small engineering teams or technical founders who want AI to handle first-pass coding and review work.

How it works

  1. A coding task is submitted on a schedule or with a description of the work needed
  2. AI writes the code for that task
  3. A second AI pass reviews and scores the code for quality
  4. Code that passes the bar is committed to GitHub; code that doesn't gets optimized and reviewed again
  5. The final code, review notes, and a Slack notification are sent to the team
What you get

Code that's already had a first review

You describe a coding task and get back code that's been written, reviewed, scored, and committed once it clears the bar.

What you get

Reviewed, committed code in GitHub along with a saved review report and a team notification.

What you need

A Cursor AI account, a GitHub account, a Google Workspace account, and a Slack workspace.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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