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AI & RAG

On-Call Spec Answerer from Dropbox Engineering Corpus

Answers on-call questions posted in a Slack channel by retrieving the most relevant Dropbox engineering specs and replying with a grounded, source-cited answer in the thread.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew question in #oncall Slack channelSlack
  • ActionEmbed question and vector-search spec chunks in PostgresPostgreSQLPostgres
  • ActionFetch top source passages with Dropbox file pathsDropboxDropbox
  • ActionGenerate grounded answer from retrieved contextOpenAI
  • OutputReply in Slack thread with answer and cited sourcesSlack

What it does

Turns your team's Dropbox spec folder into an on-call answer assistant. When an engineer asks a question in the on-call Slack channel, this workflow finds the relevant spec passages and replies in-thread with a concise, citation-backed answer.

When to use it

Run this when on-call engineers waste time hunting through design docs at 2am. Point it at the Dropbox folder holding your service specs and runbooks, and the bot becomes the first responder for "how does X work / what's the rollback for Y" questions.

How it works

  1. 1A new message in the #oncall Slack channel triggers the flow.
  2. 2The question is embedded and matched against pre-indexed spec chunks stored in Postgres (pgvector).
  3. 3The top passages are pulled, with their source Dropbox file paths retained.
  4. 4OpenAI composes an answer constrained to the retrieved context, refusing to guess when coverage is thin.
  5. 5The answer plus linked source files is posted back as a Slack thread reply.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SlackChannels, DMs, threads, mentions.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect DropboxFiles and folders.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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