Messaging in the Age of AI
The article discusses the impact of AI on messaging infrastructure, highlighting the shift from traditional deterministic messaging to a more complex model. AI agents introduce new challenges such as unpredictable message sizes and the need to manage reasoning context at scale. The author emphasizes the importance of adapting existing messaging systems to accommodate these changes rather than replacing them entirely.
- ▪AI-originated messages can carry large contexts, breaking traditional assumptions about message size and predictability.
- ▪The messaging layer must now manage reasoning context, token budgets, and model latency variance.
- ▪New workloads generated by agents stress different parts of the messaging system, requiring adaptations to handle varying message sizes and traffic patterns.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3910974) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Pravin Khandke Posted on May 25 Messaging in the Age of AI #ai #eventdriven #kafka #agents Messaging infrastructure has been boring for a decade. Queues, topics, exchanges — the primitives settled. Then AI agents arrived, and suddenly the assumptions that made messaging boring stopped holding. Messages are no longer just data. They are context.
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