Retention
6 articles about retention.
The Most Underrated Feature in AI Agents Is Knowing When Not to Act
Agents that pause and show a preview before acting have dramatically better retention than fully autonomous ones. The copilot approach - where users confirm
How to Set Memory Boundaries for AI Agents - Typed Categories for Context Retention
Separating AI agent memory into typed categories - user preferences, project context, and feedback - creates clear boundaries and prevents context pollution.
114K Views and 19 Signups From One Reddit Post: Why Views Without Retention Mean Nothing
Our Reddit post got 114K views and 19 signups. The 0% retention is what actually matters. A deep breakdown of vanity metrics, the AARRR funnel, and what we changed to fix activation.
Memory Triage for AI Agents - Why 100% Retention Is a Bug
AI agents that remember everything drown in irrelevant context. Smart memory triage using LRU decay, access frequency scoring, and hybrid retention policies cuts active memory by 50-60% while improving recall accuracy.
How to Tell if Your Product Is Actually Useful or Just Visually Polished
DAU/MAU ratios and session length can be gamed by making products addictive without being useful. The real signal is unprompted return visits - people
30 Days of Stress Testing an AI Agent Memory System
What happens when you push an AI agent memory system to its limits for 30 days. Results on retention, decay, and what actually persists across sessions.