Mastering AI Agent Architectures: Shared Memory: Blackboards, Tuple Spaces, CRDTs, and Consensus (Mastering AI Agent Architectures — The Styles Series)

By VU TRI CONG MOBILUCK - CODE247.AI

Agents that build on each other's work need a place to put it - and that place can fail, go stale, or conflict.

This book measures eighteen shared-memory styles on the Gauntlet benchmark. It starts from the classic blackboard - knowledge sources, partial entries, an agenda written as code - and then asks what it costs to keep a shared board alive and true.

The classic blackboard: 96 % on research at 0.79 the cost of a voting boardTuple spaces - a hierarchy without a masterThe consistency menu - why stale reads are cheap and strong reads cost the deadlineCRDTs - convergent is not correct: a merge that applies an adjustment twiceConsensus only where invariants demand itContext coherence - typed views per agent instead of the whole boardContention and hot spots - one lock, shards, or optimistic writesShared memory versus messages, measured pair by pair

The decision card is written as seven conditions, each delivered by a chapter, with a production checklist beside it.

Runnable code, frozen results and a lock at tag gauntlet-b5. Book 5 of 7 in Mastering AI Agent Architectures - The Styles Series.

• Format: Paperback
• Language: English
• ISBN: B0HKH6GQ4Y
• ISBN13: 9798175731942
• Release Date: September 2026
• Publisher: Independently published
• Length: 233 Pages
• Weight: 0.71 lbs.
• Dimensions: 9.0" x 0.5" x 6.0"