Context and Memory
299 episodes · Page 8 of 13
#1987: Can You Ever Quit Your Personal AI?
Your AI knows your workflow, but can you ever leave? We explore the lock-in risks of personal AI agents.
#1959: How Constrained AI Models Handle the Unexpected
Your AI assistant promised to only use your documents. Instead, it invented a case law that doesn't exist. Here's why.
#1914: Google Invented RAG's Secret Sauce
Before LLMs, Google solved the "hallucination" problem with a two-stage trick that's making a huge comeback.
#1913: AI Context Windows Are Junk Drawers
Stop paying for old messages. Here's how to keep your AI sessions clean and on-topic.
#1907: Why We Still Fine-Tune in 2026
Despite million-token context windows, fine-tuning remains essential. Here’s why behavior, not just facts, matters.
#1858: Multi-Model Agents: The Instruction & Context Gap
Mixing AI models creates chaos. Learn the practical fixes for context windows, tokenization, and output formats.
#1856: Two AIs Chatting Forever: Why They Go Crazy
What happens when two ChatGPT instances talk forever? They hit a politeness loop, forget their purpose, and spiral into gibberish.
#1849: When Forum Etiquette Becomes Prompt Engineering
Forget simple chatbots—this is how roleplayers taught AI to remember entire worlds, from 90s MUDs to just-in-time lore delivery.
#1846: Right-Sizing Your Agent's MCP Toolkit
AI agents slow down when overloaded with tool schemas. Just-in-time usage is the fix.
#1834: Owning Your AI Memory: The Data Exit Strategy
Why your AI remembers your coffee order but forgets your son’s name—and how to build a portable, federated memory layer you actually own.
#1830: Coordinating Multi-Agent Repos at Scale
Parallel AI agents rewriting your code at once creates silent regressions and architectural drift. How do we fix it?
#1828: Mastering 2M Token Context in Agentic Pipelines
A massive context window sounds like a dream, but it can quickly become a nightmare for complex AI workflows.
#1816: Is the Browser Finally Getting a Brain?
The browser is evolving from a static window into a collaborator that understands, organizes, and acts for you.
#1811: Stop Hardcoding User Names in AI Prompts
Three methods for storing user identity in AI agents—and why the "Fat System Prompt" breaks production apps.
#1804: The Fork in the Road: Why AI Agents Check Old Receipts First
Stop your AI agent from overthinking. Learn why it checks old memories instead of booking flights—and how to fix the "eagerness" problem.
#1794: RAG Is Cheaper Than You Think (Until It’s Not)
From a $1 embedding bill to a $10k/month vector database bill, here’s the real math behind RAG in 2026.
#1792: Google's Native Multimodal Embedding Kills the Fusion Layer
Google’s new embedding model maps text, images, audio, and video into a single vector space—cutting latency by 70%.
#1784: Context1: The Retrieval Coprocessor
Chroma's new 20B model acts as a specialized "scout" for your LLM, replacing slow, static RAG with multi-step, agentic search.
#1779: AI Memory Is a Mess: Files, Vectors, or Cloud?
Why your AI forgets your instructions and what the battle over portable memory means for the future of agents.
#1778: Audio Is the New "Read Later" Graveyard
Why listening to AI conversations beats reading dense PDFs, and how serverless GPUs make it cheap.
#1764: Your Repo as a Knowledge Base
How to give AI agents instant memory of your entire project—without cloud costs or complex infrastructure.
#1754: From Ollama to Agentic CLIs: The Rise of the AI Harness
Explore the evolution from local LLMs to modern agentic CLIs, focusing on the "harness" that gives models context, tools, and autonomy.
#1734: You vs. Your Digital Twin: Who Wins?
Your AI clone is getting scarily good. We explore the tech behind high-fidelity digital twins and the uncanny valley of your own voice.
#1733: When AI Agents Build Their Own Societies
AI agents are forming neighborhoods, economies, and hospitals in server-side simulations that mirror real human behavior.