AI AGENTS

Weekly Standing-Question Research Briefing

On a weekly schedule, re-researches a list of standing questions you track, compares fresh findings against last week's.

CategoryAI Agents
Enginesim
Difficultyintermediate
Triggerschedule
Steps7
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionRead standing questions and last answersAirtableAirtable
  • ActionRe-search each question for current factsExa
  • ActionCorroborate key facts across a second enginePerplexityPerplexity
  • ActionDiff against prior answers, flag changesOpenAI
  • ActionWrite updated answers and sources backAirtableAirtable
  • OutputEmail changes-only briefingGmailGmail

What it does

Keeps a set of recurring questions perpetually answered. Each week the agent re-runs research on every standing question in your Airtable list, diffs the new sourced findings against the prior run, and produces a briefing that surfaces only material changes, each tagged with a confidence flag and source link.

When to use it

Use it for questions you must keep warm: "What is our top competitor's pricing?", "What's the latest on regulation X?", "Who's hiring aggressively in our space?" Instead of re-searching by hand, you get a Monday-morning email of just the deltas.

How it works

  1. 1A weekly schedule trigger starts the run.
  2. 2The agent reads the standing-question list from Airtable, including each question's last-known answer.
  3. 3For each question it runs a current web search and corroborates the key facts.
  4. 4An LLM diffs new findings against the stored answer and flags changes by confidence.
  5. 5Updated answers and sources are written back to Airtable.
  6. 6A changes-only briefing is emailed to the team.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  2. 2
    Connect ExaNeural search across the web.
  3. 3
    Connect PerplexitySearch-grounded answers with citations.
  4. 4
    Connect OpenAIModels, embeddings, files.
  5. 5
    Connect GmailRead, draft, send, label.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    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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