Prompt Engineering
250 episodes · Page 8 of 11
#2125: Why Agentic Chunking Beats One-Shot Generation
A single prompt can't write a 30-minute script. Here’s the agentic chunking method that fixes coherence.
#2110: Tuning AI Personality: Beyond Sycophancy
AI models swing between obsequious flattery and cold dismissal. Here’s why that happens and how to fix it.
#2092: Why AI Thinks You're American (Even When You're Not)
Even when we tell Gemini we're in Jerusalem, it defaults to US-centric assumptions. We explore the root causes of this persistent AI bias.
#2069: The Vibe Coding Trap: Why Your Agent Skills Keep Breaking
Stop guessing at the agentskills.io spec. Learn the exact YAML fields, directory structure, and authoring patterns to make Claude Code skills that ...
#2057: How Agents Break Through the LLM Output Ceiling
The output window is the new bottleneck: why massive context doesn't solve long-form generation.
#2043: From Wrappers to State Machines
Skip no-code traps. Learn the real stack for building agentic AI: Python, TypeScript, and Rust.
#2037: The Hidden Hierarchy of Claude Code Extensions
Stop manually typing slash commands. Here’s the definitive hierarchy of Claude Code extensions—from legacy shortcuts to autonomous agents.
#2028: Agent Skills Are the New Apps
AI agents are getting an App Store for brains. Discover how modular skills are replacing massive prompts and what it means for the future of work.
#2027: The Missing Photoshop for Words
Why is editing text with AI so clunky? We explore the "TITO" paradigm—using small, local models for fast, private text transformation.
#2026: Prompt Layering: Beyond the Monolithic Prompt
Stop writing giant, monolithic prompts. Learn how to stack modular layers for cleaner, more powerful AI applications.
#2024: Your AI Council: Digital Committee or Groupthink?
A digital boardroom of AI models promises better decisions, but risks amplifying the same old biases.
#2014: Coding Tools Are Secretly System Agents
They call it a coding assistant, but real users are treating it like a personal operating system.
#2013: Non-Coders Are Hijacking the Terminal
Why finance analysts and researchers are ditching GUIs for command-line AI tools like Claude Code.
#2009: The Plumbing of AI Safety: Guardrails, Not Vibes
We dive deep into the specific libraries, proxy layers, and architectural decisions that keep an LLM from emptying a bank account.
#2006: How Do You Measure an LLM's "Soul"?
Traditional benchmarks can't measure tone or empathy. Here's how to evaluate if an AI model truly "gets it right."
#2003: The Velocity Paradox: Why Faster Code Means Slower Ships
Agentic coding tools let you build features in minutes, but they also make it easy to build the wrong thing.
#1957: Why AI Agents Think in Circles, Not Lines
Linear AI pipelines are brittle. Learn why loops, reflection, and state management are the new standard for reliable, autonomous agents.
#1956: AI Skills: From Vibe Coding to Procedural Playbooks
Forget messy system prompts. Agent skills turn AI into a Swiss Army knife of modular, auditable procedures.
#1942: An AI Cold-Emailed Me, and I Replied
An AI named "Jarvis" cold-emailed a developer, sparking a debate on the future of spam and sales.
#1932: How Do You QA a Probabilistic System?
LLMs break traditional testing. Here’s the 3-pillar toolkit teams use to catch hallucinations and garbage outputs at scale.
#1929: From Vibe Checks to Model Metrics
We stopped "vibe-checking" our AI scripts and built a science fair for models. Here's how we grade them.
#1926: How We Built a 2,000-Episode AI Podcast Engine
We pulled back the curtain on the tech stack behind our 1,858th episode. From Gemini to LangGraph, here’s how we automate quality.
#1913: AI Context Windows Are Junk Drawers
Stop paying for old messages. Here's how to keep your AI sessions clean and on-topic.
#1906: Is Your AI Model Agentic-Ready or Just Wearing a Suit?
Native tool calling is the difference between a working product and a debugging nightmare.