AI & RAG
Low-Confidence RFC Question Escalation to Linear
When the answer-bot cannot find a confident grounded answer to an engineering question, it opens a Linear issue routed to the owning team so the knowledge gap gets documented…
How it runs
The automated pipeline, trigger to output.
- TriggerQuestion received via webhookHTTP webhook
- ActionRetrieve top candidate chunksSupabase
- ActionScore grounding confidence + infer ownerOpenAI
- LogicBranch on confidence threshold
- OutputOpen Linear issue for the owning teamLinear
What it does
Closes the loop on questions the RAG bot can't answer. A question arrives via webhook; the flow retrieves candidate sources and scores confidence. If retrieval is weak or the model declines to answer from sources, instead of a dead-end reply it files a Linear issue tagged to the team that owns the relevant area, capturing the question and the closest near-miss sources.
When to use it
When you want unanswered questions to become tracked documentation work rather than vanishing. Pairs with the Slack answer-bot to handle its refusal path.
How it works
- 1An incoming question hits an HTTP webhook from the bot's refusal path.
- 2The flow retrieves the top candidate chunks from the Supabase vector store.
- 3OpenAI scores grounding confidence and identifies the likely owning area.
- 4A logic gate routes high-confidence cases back as an answer and low-confidence cases onward.
- 5For low confidence, the flow creates a Linear issue with the question, near-miss citations, and the inferred owning team as assignee.
Set it up
What you configure once, before turning it on.
- 1Connect HTTP webhookTrigger any URL on agent actions.
- 2Connect SupabaseTables, auth, storage, edge functions.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect LinearIssues, projects, cycles, triage.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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