PERSONAL PRODUCTIVITY

Answer decision-history questions in Slack from the register

Lets anyone ask a plain-English question in Slack about past decisions; an AI searches the Postgres decision register and replies with the matching decisions, their rationale.

CategoryPersonal Productivity
EngineSim + Paperclip
Difficultyadvanced
Triggerchat
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSlack app mention or DM with a questionSlack
  • ActionParse question into search terms with OpenAIOpenAI
  • ActionQuery Postgres decision registerPostgreSQLPostgres
  • LogicHandle no-results fallback
  • ActionCompose grounded answer with OpenAIOpenAI
  • OutputReply in Slack with answer and source linksSlack

What it does

Turns your decision register into a question-answering assistant inside Slack. Someone @-mentions the bot asking "why did we drop the legacy billing flow?" and it searches the Postgres register, retrieves the relevant decisions, and replies with the answer plus the original rationale, owner, and a link back to the source thread.

When to use it

Use it once you have a populated register and want answers without anyone opening Notion or writing SQL. Perfect for onboarding new hires, settling "didn't we already decide this?" debates, and surfacing the reasoning behind past calls on demand.

How it works

  1. 1A Slack app mention or DM triggers the workflow with the user's question.
  2. 2An OpenAI step turns the question into search terms and filters.
  3. 3The workflow queries the Postgres decision register for matching entries.
  4. 4A logic step handles the no-results case with a helpful fallback message.
  5. 5An OpenAI step composes a grounded answer citing the matched decisions, owners, and dates.
  6. 6The reply is posted in Slack with permalinks to the original decision threads.

Set it up

What you configure once, before turning it on.

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

Run this workflow in your colony.

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