enterprise system architects

Abstract: Agents are increasingly interacting with other agents that act for different principals -- people or organizations on whose behalf they work -- e.g., a buyer's personal agent negotiating with an enterprise's seller agent. In such agent-to-agent (A2A) scenarios, each agent has its own environment and holds information and authority that the other cannot see. Moreover, the interests of each agent may be aligned (cooperative), partly aligned (mixed-motive), or opposed (competitive). Existing multi-agent system failure studies assume only one orchestrator, shared workspace, or principal. We ask how A2A systems fail when these assumptions are removed. We study more than 2,500 recorded runs of A2A systems built from different agent harnesses and models, spanning 488 scenarios across eight families (legal, CRM, security, commerce, etc.). From these traces, we derive $A^2$-Failures, a taxonomy of 20 A2A failure modes in four categories: (i) discovery and delegation, (ii) grounding and record consistency, (iii) verification, and (iv) conduct and fidelity. Three observations hold across the harnesses, models, and scenarios studied: (1) Agents match tasks to peer names mentioned in the prompt rather than actively searching for available peers; (2) Agents never fact-check each other unprompted; (3) Scoring only the final output rewards the lead agent while hiding internal coordination, verification, and behavioral breakdowns. Our study makes a case for comprehensive evaluations where agents are scored individually against their own objectives in addition to task outcome. We release the run logs behind the taxonomy at https://huggingface.co/datasets/a2a-salesforce/a2-failures.

Abstract: Multi-version concurrency control (MVCC) has been the dominant concurrency protocol in modern database management systems (DBMSs). However, cloud-native HTAP architectures shift many of MVCC's traditional advantages from the primary transaction engine to the deployment architecture. Now, transactional and analytical processing are decoupled into loosely synchronized engines, while cloud deployment primitives provide the workload isolation required for this design. In this paper, we challenge the status quo, arguing that single-version concurrency control (SVCC) is better suited to cloud transaction processing than MVCC. Through a systematic analysis of MVCC's limitations, we show that SVCC avoids these shortcomings through a more lightweight and efficient design. Beyond arguing for a lighter transaction processing, we use this SVCC effort as a blueprint to advocate for a broader rethinking of cloud-native architectures and to outline a research roadmap to shape next-generation DBMSs.