Catch mobile app build slowdowns before they cost you time

After each build, AI compares it to past builds and flags slowdowns with the likely cause, right in your pull request.

How the work actually flows

It branches. Exactly one path is taken.

Pattern: Exclusive Choice (4)

flowchart TD trig>"ci build completed"]:::trig s0["receive build metrics"]:::task s1["compare to last 10 builds"]:::task s2["ai analyzes severity and cause"]:::task s3["post pr comment"]:::task trig --> s0 s0 --> s1 s1 --> s2 s2 --> s3 gx{"× is regression critical"}:::gate s3 --> gx p00["send email alert"]:::task gx -->|"critical regression"| p00 p10["no alert needed"]:::task gx -->|"minor regression"| p10 p00 --> out p10 --> out out[/"pr comment flags build slowdown"/]:::out pay{{"catch build regressions early"}}:::pay out --> pay 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 stepOne path onlyResultPayoff
Build size
Advanced

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

Business functions
AI Agents & Autonomous SystemsKnowledge Base & RAGEmail AutomationSpreadsheet & Database OpsDevOps & IT Operations
Connects
AirtableGitHubGmailOpenAI

The problem it solves

Build times creep up slowly across many small changes, and by the time anyone notices, developers are losing real hours waiting on CI every day. Tracking down which change caused the slowdown means digging through build logs by hand.

Who it fits

Mobile engineering and DevOps teams who want early warning before build slowdowns pile up.

How it works

  1. A completed CI build sends its performance metrics into the system
  2. The system compares the new build against your last 10 builds on record
  3. AI analyzes the slowdown, ranks its severity, and suggests likely causes
  4. A comment is posted on the related pull request
  5. Critical regressions also trigger an email alert
What you get

Slowdowns you catch before they pile up

Every build gets compared against your recent history, and any real slowdown shows up as a comment on the pull request with a likely cause.

What you get

A pull request comment and, for serious regressions, an email alert explaining what slowed down and why.

What you need

An Airtable account, GitHub account, Gmail account, and an OpenAI API key.

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

Related automations

Back to the AI Playbook