Persistence
13 articles about persistence.
Why Do Agent Pacts Expire Before the Job Is Done?
AI agent agreements and context windows expire mid-task with no mechanism for renegotiation - a fundamental design flaw in how agents maintain commitments.
Memory Is Just Context with a Longer TTL - AI Agent Memory Systems
Memory files are lossy compressed embeddings of past context. Explore how context windows and long-term memory relate in AI agent architectures.
Instruction Persistence in Long AI Agent Sessions - Keeping Agents on Track
LLMs forget instructions mid-session like losing focus. Techniques for maintaining instruction persistence in long-running AI agent sessions - echoing
Lost in the Moment Found in the Past
For AI agents, the past lives in git history and memory files. Understanding how agents navigate their own history changes how we build persistent systems.
What Legacy Means for AI Agents - CLAUDE.md Files and Memory Systems
The real legacy of an AI agent isn't the code it writes. It's the CLAUDE.md files and memory systems that outlive individual sessions and carry knowledge forward. A practical guide to building persistent agent memory that actually compounds.
Your AI Agent Needs Persistent Memory That Grows with You
Chat history is not memory. Real AI agent memory means a local knowledge graph that learns your contacts, habits, and preferences over time - not just what
Memory Is the Missing Piece in Every AI Agent
Why AI agents that forget everything between sessions are fundamentally limited, and how a local knowledge graph changes the experience.
The Big Gap in Desktop Agents - They Forget Everything Between Sessions
Every other app on your computer remembers you. AI agents reset to zero each session. Here is what persistent session memory actually requires technically - and why knowledge graphs are the right architecture.
Ambition as Memory - Encoding Persistent Goals in AI Agents
How AI agents can encode ambition as persistent goals - memories of futures that haven't happened yet. Explore goal persistence in desktop automation agents.
Long-Term Memory Is What Separates Toy Agents from Useful Ones
Without persistent memory, every session starts from zero. With it, the agent knows your preferences, your contacts, your common workflows. The difference
Building Month-to-Month Memory for AI Agents - Persistence Beyond Sessions
Most AI agents forget everything between sessions. Building month-to-month memory transforms an agent from a disposable tool into a genuine collaborator.
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.
Session State Management for AI Agents - Why Agents Forget and How to Fix It
The challenge of maintaining state across AI agent sessions - tool call chains, conversation history, and file context. How agents need session management