This position paper proposes the Verification Tree Architecture, a lightweight orchestration framework designed to address the Attention Flooding problem emerging in AI-era software ecosystems. As Large Language Models and Autonomous Coding Agents collapse the marginal cost of bug report generation to near zero, the cost of verification remains fully borne by human maintainers. This structural asymmetry creates a systemic bottleneck that legacy issue-tracking systems — built around isolated documents and manual triage — cannot withstand. The proposed architecture reframes bug reports as probabilistic states within a hierarchical lineage graph rather than independent text entries. Duplicate discoveries are reinterpreted as Confidence Reinforcement Signals. AI is repositioned from a truth verification engine to an Attention Router. Time-based Natural Filtering allows hallucination-driven reports to decay passively without active compute overhead. Key contributions include: the VerificationNode schema, a Confidence Score accumulation formula with environment diversity weighting, Reputation-Based Reporter Tiers resistant to Sybil attacks, Variant Branching Dynamics, and Collapse Mechanics for attention saturation management.This paper is intended as a conceptual framework and system architecture proposal for open-source maintainers, platform engineers, and AI tooling developers navigating the structural challenges of high-volume automated bug reporting.