Skip to main content

memory

6 articles

From chat logs to structured understanding: giving AI products real memory. Context windows aren't memory. RAG isn't memory. Real memory means maintaining a coherent, evolving model of each user.

Essential reading
Memory Is the New Moat
Opinion memory self-models

Memory Is the New Moat

Features get copied in weeks. Models get commoditized in months. But a product that remembers each user - their beliefs, preferences, and context - builds a compounding advantage that no competitor can replicate.
Robert Ta's Self-Model
Robert Ta's Self-Model
· 11 min read
Agent Memory: Why Chat Logs Are Not Enough
Deep Dive ai-agents memory

Agent Memory: Why Chat Logs Are Not Enough

Chat logs give AI agents history but not understanding. Agent memory needs structured self-models that capture beliefs, goals, and context evolution.
Robert Ta's Self-Model
Robert Ta's Self-Model
· 15 min read

All articles
The Agent Memory Problem Nobody Is Solving
Opinion ai-agents memory

The Agent Memory Problem Nobody Is Solving

Agent memory architectures require persistent self-models that maintain belief states across sessions and agents, not just chat logs or vector storage. Enterprise teams building multi-agent systems face alignment drift and coordination taxes when memory lacks shared contextual understanding.
Robert Ta's Self-Model
Robert Ta's Self-Model
· 8 min read
Your AI Platform Has No Memory Architecture
Opinion memory architecture

Your AI Platform Has No Memory Architecture

Chat logs are not memory. RAG over transcripts is not memory. Real memory architecture means structured, evolving models of each user.
Robert Ta's Self-Model
Robert Ta's Self-Model
· 11 min read
Context Windows Are Not Memory
Opinion ai-agents memory

Context Windows Are Not Memory

Your AI agent has a 128K context window. You think it remembers. It does not. Context windows are temporary buffers, not persistent understanding. Here is why the distinction matters and what to do about it.
Robert Ta's Self-Model
Robert Ta's Self-Model
· 10 min read
Multi-Agent Memory Benchmarks
Research ai-agents evaluation

Multi-Agent Memory Benchmarks

Multi-agent systems are everywhere. Memory in multi-agent systems is nowhere. We benchmarked how well leading agent frameworks retain user context across agent handoffs - and the results are concerning.
Robert Ta's Self-Model
Robert Ta's Self-Model
· 13 min read

Related topics
self-models (114) architecture (76) ai-agents (21)

Stay sharp on AI personalization

Daily insights and research on AI personalization and context management at scale. Read by hundreds of AI builders.

Daily articles on AI-native products. Unsubscribe anytime.

Building AI that needs to understand its users?

Book a Strategy Call