Article: LLM Reliability Layers Under Test: Accuracy, Yield, and the Limits of Verification

Pushpdeep Mishra, Wejdan Bagais — Tue, 10 Nov 2026 09:00:00 GMT

Verification layers sort outputs by trust rather than fixing errors. In a benchmark of six reliability layers, voting and self-correction failed to recover accuracy - they only withheld doubtful records. Production systems gain more reliability by replacing generation with deterministic lookups, tracking yield over raw accuracy, and resolving extraction bottlenecks before stacking checks.

By Pushpdeep Mishra, Wejdan Bagais

Article: Systemic Approach to Memory, Knowledge, and Context in Agentic AI Architectures

Adi Polak — Mon, 02 Nov 2026 11:00:00 GMT

The article argues that reliable agentic AI architecture depends on a context engine that selects, injects, compresses, and expires information before it reaches the model. It separates context, memory, and knowledge, and recommends tiered memory, curated knowledge, and token budgeting. It also covers common anti-patterns, such as context stuffing and stale data loops, with mitigations.

By Adi Polak

InfoQ - AI, ML & Data Engineering - Articles

Article: LLM Reliability Layers Under Test: Accuracy, Yield, and the Limits of Verification

Article: Systemic Approach to Memory, Knowledge, and Context in Agentic AI Architectures