← Prompt Engineering

Prompt Engineering

250 episodes · Page 7 of 11

#2461: How Claude Code's Conversation Compaction Actually Works

The three-tier system, what survives, what dies, and why you shouldn't rely on auto-compact.

context-and-memoryai-coding-assistantsai-inferenceprompt-engineeringmulti-agent-systems

#2412: When AI Caves: Progressive vs. Regressive Sycophancy

Why do LLMs agree with you even when you're wrong? We break down the SycEval benchmark and the 78% persistence problem.

ai-alignmentai-evaluationhallucinationsprompt-engineeringreasoning-models

#2366: Why LLMs Forget the Middle of Long Conversations

Why do large language models struggle with the middle of long conversations? Explore the science behind attention dilution and practical fixes.

context-and-memorytransformer-architecturehallucinationsprompt-engineering

#2336: How ADRs Solve AI's Institutional Memory Problem

Architectural Decision Records (ADRs) aren’t just documentation—they’re a way to give AI coding assistants the context they lack.

ai-coding-assistantscontext-and-memoryprompt-engineeringdevops

#2334: How AI Flattens Your Voice in Emails

Why AI-generated emails feel impersonal and how to reclaim your authentic voice in professional communication.

ai-alignmentprompt-engineeringfine-tuningai-evaluation

#2309: Blind Ranking AI's Best Podcast Scripts

How do 15 AI models handle controversial podcast prompts? We rank their scripts blind and reveal the surprising winners.

ai-evaluationai-biasprompt-engineeringhallucinationsreasoning-models

#2287: Is AI Code Generation the Future of Low-Code?

Exploring the rise of AI code generation and its potential to reshape the low-code movement.

ai-coding-assistantsprompt-engineeringworkflow-automationopen-source

#2253: Why AI Agents Get Three Steps, Not Infinity

Why do AI agents get exactly three rounds of tool use? It's a critical guardrail against infinite loops and runaway costs, not a limit on intellige...

multi-agent-systemsai-inferenceprompt-engineeringai-coding-assistantsreasoning-models

#2249: Building Custom Benchmarks for Agentic Systems

Public benchmarks fail for agentic systems. Learn how to build evaluation frameworks that actually predict production behavior.

ai-evaluationmulti-agent-systemsai-coding-assistantsprompt-engineering

#2242: AI as Your Ideation Blind Spot Spotter

How to use AI not to answer questions you already know to ask, but to surface possibilities your expertise has made invisible to you.

prompt-engineeringai-coding-assistantscontext-and-memorymathematics

#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.

ai-evaluationprompt-engineering

#2219: Spec-Driven Life: How AI Planning Beats Project Paralysis

What makes AI agents reliably productive? A structured spec that externalizes memory and chunks work into manageable pieces. Can the same framework...

ai-coding-assistantscontext-and-memoryprompt-engineeringmulti-agent-systems

#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...

context-and-memoryragprompt-engineeringai-alignmentreasoning-models

#2207: Specs First, Code Second: Inside Agentic AI's New Era

As AI coding agents evolve from autocomplete to autonomous cloud workers, the bottleneck has shifted—now it's about how clearly you specify what ne...

ai-coding-assistantsmulti-agent-systemsprompt-engineeringdevops

#2194: Game Theory for Multi-Agent AI: Design Better, Fail Less

Nash equilibrium, mechanism design, and why your AI agents are playing prisoner's dilemma whether you know it or not.

multi-agent-systemsai-alignmentai-evaluationprompt-engineering

#2186: The AI Persona Fidelity Challenge

Advanced LLMs dominate benchmarks but fail at staying in character—especially when asked to play morally complex or antagonistic roles. What does t...

ai-alignmentprompt-engineeringai-evaluationcontext-and-memoryreasoning-models

#2185: Taking AI Agents From Demo to Production

Sixty-two percent of companies are experimenting with AI agents, but only 23% are scaling them—and 40% of projects will be canceled by 2027. The ga...

ai-evaluationprompt-engineeringai-inferencereliability-engineeringdevops

#2177: Skip Fine-Tuning: Shape LLMs With Alignment Alone

Can you build a personalized LLM by skipping traditional fine-tuning and using only post-training alignment methods like DPO and GRPO? We break dow...

fine-tuningai-alignmentai-inferencegpusprompt-engineering

#2175: Let Your AI Argue With Itself

What happens when you let multiple AI personas debate each other instead of asking one model one question? A deep dive into synthetic perspective e...

multi-agent-systemsprompt-engineeringai-evaluationlocal-aimodel-context-protocol

#2174: Role-Playing as Orchestration

How a role-playing protocol from NeurIPS 2023 became one of AI's most underrated agent frameworks—and what happens when you scale it to a million a...

multi-agent-systemsai-coding-assistantsprompt-engineeringopen-source

#2171: How IQT Labs Built a Wargaming LLM (Then Archived It)

A deep code review of Snowglobe, IQT Labs' open-source LLM wargaming system that ran real national security simulations before being archived. What...

multi-agent-systemsai-evaluationprompt-engineeringopen-sourcegames

#2168: What Serious Agentic AI Developers Actually Need to Know

Python, TypeScript, LangGraph, and the frameworks reshaping how agents work. A technical map of the skills and concepts that separate prototypes fr...

ai-coding-assistantsmodel-context-protocolmulti-agent-systemsprogramming-languagesprompt-engineering

#2135: Is Your AI Wargame Signal or Noise?

Monte Carlo methods promise statistical rigor for AI wargaming, but the line between genuine insight and sampling noise is thinner than you think.

ai-evaluationprompt-engineeringai-inferencemilitary-strategyforecasting-and-wargaming

#2133: Engineering Geopolitical Personas: Beyond Caricatures

How to build LLMs that simulate state actors with strategic fidelity, not just surface mimicry.

prompt-engineeringfine-tuningragai-evaluationai-alignment