Back office ops · Production

Coinbase builds RAPID-D, a multi-agent AI decision support system to augment its RAPID framework

The problem

Coinbase's RAPID decision framework lacked systematic mechanisms to surface unseen risks, mitigate cognitive bias, and provide a transparent, auditable layer of analysis for critical strategic decisions.

Workflow diagram · grounded in source
1
RAPID document submitted
trigger
“the primary RAPID document, i.e. the document that uses the RAPID framework to outline roles and responsibilities for a project or decision”
2
Analyst baseline review
ai_action
“This agent first performs a thorough, impartial review of the primary RAPID document, i.e. the document that uses the RAPID framework to outline roles and responsibilities for a project or decision. The agent generates a baseline recomme…”
3
Seeker context enrichment
ai_action
“This agent intelligently probes the decision by first generating critical questions about the RAPID document. It then leverages our enterprise search tool to find answers across all internal knowledge sources”
4
Contrarian challenge
ai_action
“This agent's sole purpose is to build the strongest possible case against the initial recommendation. It deliberately probes for weaknesses, unstated assumptions, potential risks, and unintended consequences.”
5
Synthesizer final recommendation
ai_action
“It meticulously evaluates the arguments from the Analyst, the broader context from the Seeker, and the challenges from the Devil's Advocate. It then produces a comprehensive final recommendation for the human Decider, complete with a det…”
6
Human Decider final decision
human_review
“an accountable "decider" makes the final decision based on these insights”
7
Stakeholder feedback incorporation
feedback_loop
“Comments or corrections — whether provided by the user during an active session or later by any stakeholder in the RAPID document — are captured and analyzed against the assistant's original recommendation. This evaluation is then used t…”
Reported outcome

RAPID-D makes decision-making transparent, consistent, and reproducible; Claude 3.7 Sonnet was selected for its strong balance of quality, stability, and reliability.

Reported metrics
Decision-making process qualitytransparent, consistent, and reproducible
Model reliability assessmentstrong balance of quality, stability, and reliability
Reported stack
RAPID-DClaude 3.7 Sonnetenterprise search toolenterprise knowledge base
Source
https://www.coinbase.com/en-nl/blog/making-smarter-decisions-faster-with-AI-at-Coinbase
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

RAPID-D makes decision-making transparent, consistent, and reproducible; Claude 3.7 Sonnet was selected for its strong balance of quality, stability, and reliability.

What tools did this team use?

RAPID-D, Claude 3.7 Sonnet, enterprise search tool, enterprise knowledge base.

What results were reported?

Decision-making process quality: transparent, consistent, and reproducible; Model reliability assessment: strong balance of quality, stability, and reliability (source-reported, not independently verified).

How is this back office ops AI workflow structured?

RAPID document submitted → Analyst baseline review → Seeker context enrichment → Contrarian challenge → Synthesizer final recommendation → Human Decider final decision → Stakeholder feedback incorporation.

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