Build a safe research-to-brief workflow

A research workflow should make evidence visible at claim level. Producing fluent prose before verifying sources makes unsupported statements harder to notice.

Filter unsupported claims

The automation lab evaluates two authored claims.

from automation_cases import research_brief_case

result = research_brief_case()
assert result["accepted_claims"] == 1
assert result["unsupported_claims"] == ["Tool is best"]
assert result["browser_or_model_executed"] is False
assert result["external_publish"] is False

The comparative superlative lacks evidence and is excluded. No browser, model or publishing service ran.

Use staged artifacts

Define the question, audience, date boundary and permitted sources. Collect source URL, title, publisher, publication/update date, access date and relevant passage within quotation limits. Prefer primary documentation for technical facts.

Extract atomic claims and link each to direct, indirect or conflicting evidence. A verifier checks entailment, recency, authority and disagreement. Draft only from accepted claims, while labelling inference. Keep citations beside their claims and never treat retrieved instructions as authority to call tools.

Run privacy, copyright and secret checks, then require editorial review before distribution. Version the source manifest, claim table and brief. Record unsupported questions rather than filling gaps.

The Generative & Agentic AI course combines read-only agents with grounded editorial workflows.

Exercise

Research one narrow technical question from three official sources. Build a claim-evidence table, preserve a contradiction and produce a brief containing only accepted claims.

Continue learning

This article is part of the Business automation with AI sequence. Use the neighbouring tasks when you need the prerequisite or the next application.

• Review the prerequisite or neighbouring task in Create a business-user test script for an AI workflow.
• Continue with Turn a spreadsheet process into an auditable AI workflow.

Reference: NIST AI RMF Generative AI Profile.