Topic / T SALON
Agent
T Salon's collection on AI agents — architectural flaws and rebuilds in multi-agent collaboration, long-term memory update and expiry, memory security controls for enterprise agents, and engineering lessons from shipping AI-native applications.
5 stories
- 2026.09.19
How to Keep Bad Assumptions Out of Agent Memory
Retrieval quality cannot repair a memory that was wrong when written. How enterprise agents use environment-probing curation, source verification, and lifecycle controls in MemOS to prevent flawed assumptions from becoming durable memory.
- 2026.09.11
Dreaming Update: AI Memory Requires Annual Management
In April 2025, OpenAI introduced an early version of Dreaming to ChatGPT, allowing it to reference chat logs. In June, OpenAI upgraded the Dreaming architecture.
- 2026.09.01
Memory Poisoning: Long-Term Memory Controls for Agents
If a system records a fake contact as a trusted supplier, the impact extends beyond the current conversation. Memory Poisoning is a critical risk for AI Agents.
- 2026.08.03
Event Recap: From AI Demo to Production｜Engineering Practices for Agent and AI Native Applications
A recap of the 'From AI Demo to Production' offline event held in Shanghai on August 1st, featuring four guests sharing engineering practices on persistent Agent memory, multi-model collaboration, Vibe Coding, and Agent execution environments.
- 2026.07.21
Agent Swarm Rewrites SQLite: Deep Dive into 5 Fatal Flaws and Architectural Reorganization
An in-depth analysis of the latest Agent Swarm experiment. By leveraging tree decomposition, a custom high-speed VCS, neutral merge agents, and a stigmergic Field Guide, the swarm reached an 80% SQLite (Rust) test pass rate in four hours and eventually achieved 100%.