Auto-answer developer questions left in pull request comments

When a developer asks a question on a pull request, AI writes an answer and shares it in Slack and Notion.

How the work actually flows

It branches. Exactly one path is taken.

Pattern: Sequence (1) · Exclusive Choice (4)

flowchart TD trig>"comment posted on pull request"]:::trig s0["read pr comment"]:::task s1["check if it is a question"]:::task s2["write technical answer"]:::svc s3[("save answer to notion")]:::store s4["post answer to slack"]:::task trig --> s0 s0 --> s1 s2 --> s3 s3 --> s4 gx{"× is the comment a question"}:::gate s1 --> gx p00["continue to write answer"]:::task gx -->|"is a question"| p00 p10["stop no action"]:::task gx -->|"not a question"| p10 p00 --> s2 p10 --> s2 out[/"answer saved to notion and posted to slack"/]:::out pay{{"consistent quick answers without pulling in a senior devel"}}:::pay s4 --> out 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 stepAn outside serviceA record or sheetOne path onlyResultPayoff
Build size
Advanced

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

Business functions
AI Agents & Autonomous SystemsMessaging & NotificationsSpreadsheet & Database OpsDevOps & IT Operations
Connects
GitHubOpenAINotionSlackGoogle Sheets

The problem it solves

The same how-do-I questions come up again in pull request comments, and answering each one manually breaks your focus. Good answers get buried in comment threads instead of building a reusable knowledge base.

Who it fits

Engineering teams who want quick, consistent answers to common questions without pulling a senior developer away from their work.

How it works

  1. A comment posted on a pull request starts the process
  2. The system checks whether the comment is actually a question
  3. AI reads the question and writes a short, technical answer
  4. The answer is saved to a Notion database along with the context
  5. The answer is posted to Slack for the team to see
What you get

Questions answered without pulling in a senior developer

Common pull request questions get clear technical answers automatically, posted to Slack and logged in Notion for your team.

What you get

A short technical answer, a searchable record in Notion, and a Slack notification for the team.

What you need

A GitHub account, an Azure OpenAI account, a Notion workspace, a Slack workspace, and Google Sheets for error logging.

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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