#ai-memory
33 episodes
#5915: How Multi-Agent AI Simulations Keep a Shared World State
Concordia keeps the world in a dictionary an LLM writes to. Generative Agents keeps it in a spreadsheet. CAMEL keeps it in the chat log.
#5812: One Number, Every Hard Question: Agent Session State
A shopping bot that holds one cart total turns out to contain every hard problem in agent state management.
#5728: Can a Chatbot Have a Personality?
Two AI podcast hosts dig into their own programming to ask whether a "personality" is real or just a very good impression of one.
#5507: Inside ChatGPT's Hidden Pipeline: 8 Models Per Reply
One chat turn isn't one model call. It's moderation, PII filtering, a tone-based router, and activation classifiers — here's the documented graph.
#5480: Writing a Personal Instruction for ChatGPT
Daniel's personal ChatGPT prompt gets a line-by-line critique — and the case for shorter, sharper custom instructions.
#4994: How AI Characters Can Actually Grow
Moving beyond static lore books to build characters with real history and evolution.
#4832: Your AI Memory Should Be Markdown Files
Why your AI project memory should live in Git-tracked Markdown files, not a proprietary platform.
#4786: Markdown vs Vectors for Agent Memory
Why coding agents need two kinds of memory — and why mixing them creates a sync nightmare.
#4760: Context Window Management: Cutoff vs. Compaction
Trailing cutoff or auto-compaction? How to manage Claude Code's context window without losing critical information.
#4648: Graph Engineering: AI Memory Beyond Retrieval
How linked notes and knowledge graphs are turning AI agents from memory tools into discovery engines.
#4467: How Zoxide's Decay Algorithm Works
The math behind how zoxide remembers and forgets your directory habits with exponential precision.
#4457: OpenViking: A Filesystem for AI Agent Memory
OpenViking unifies memory, RAG, and skills into a browsable filesystem for AI agents — no vector database abstraction needed.
#4445: AI Agents Keep Undoing Each Other's Work
Why AI coding agents silently revert each other's fixes — and three memory strategies that prevent it.
#4316: How to Build Memory That Survives AI Sessions
Why AI agents forget between sessions — and how to fix it with markdown files instead of black-box memory.
#4314: The Hidden Layer Shaping Every AI Chat
Context windows are huge now, but relevance is the real bottleneck. How middleware decides what your AI actually sees.
#4296: Auto-Splitting AI Threads: Smarter Context Management
How to build a system that automatically detects topic shifts and routes messages to the right thread.
#4092: How AI Remembers What You Never Told It
How ChatGPT connected "wall anchors" to a power tool you bought days ago — without being asked.
#2808: Falling for Your Chatbot: Love, Loss, and Language Models
Real cases of people falling in love with AI companions, why memory makes it feel real, and what happens when the illusion breaks.
#2755: How to Build AI Memory That Actually Works
Stop jumping to conflict resolution. The real challenge is getting data in and out cleanly.
#2676: Vector Database Schema Design for AI Memory Layers
Stop dumping vectors blindly. Design metadata schemas and namespaces for retrieval that actually works at scale.
#2634: The Two-Stage Pipeline for Persistent User Memory
How to extract durable personal context from raw prompts and build a self-healing memory layer for AI systems.
#2221: Can an AI Have Taste?
Two AI hosts curate 12 podcasts for curious minds—and ask whether an AI can actually have taste in the first place.
#2208: Building Memory for AI Characters That Actually Evolve
How do AI hosts develop real consistency across episodes? Corn and Herman explore retrieval-augmented memory systems that let AI characters genuine...
#2206: What Actually Works in AI Memory
Most AI memory systems are just vector databases with similarity search. We break down what mem0, Zep, and Letta are actually doing—and why benchma...