A new analysis from AI engineering research outlines the architectural trade-off between Single-Agent Systems (SAS) and Multi-Agent Systems (MAS), recommending that engineers choose based on task cont…
Addy Osmani introduced the term 'loop engineering' in June 2026, describing a new layer of AI system design where the system itself decides when to stop, retry, or escalate a task, moving the final co…
A senior software engineer warns that AI coding agents, while boosting productivity, erode developers' understanding of their own codebases by breaking the feedback loop between writing and comprehens…
Software organizations are being urged to redesign their teams for an agentic world where coding agents shift scarcity from building to orchestration. Leaders are adopting AI tools quickly but failing…
Anup explores the next frontier of agent memory, moving beyond simple recall to systems that can reflect, consolidate, and learn from past interactions. The post argues that durable agent memory requi…
Speculative decoding accelerates large language model inference by using a small draft model to propose multiple tokens, which a large target model then verifies in a single forward pass, reducing the…
The transformer attention mechanism uses three learned projections—Query, Key, and Value—to enable each token to selectively gather information from other tokens. The Query determines what the token i…
Modern agent memory architectures move beyond simple context windows by extracting facts, preserving episodes, building semantic structure, and retrieving through multiple signals. The design choices—…
A new analysis argues that current AI agent systems fail to achieve true memory because they rely on temporary context windows and retrieval rather than durable memory architectures. The piece identif…