AI Inference
554 episodes · Page 10 of 24
#4588: The Hidden Cost of Conversational AI: Why Stateless LLM Calls Matter
Why conversational AI tools are making batch document processing slower, costlier, and less reliable — and what to do about it.
#4581: Text In, Text Out: Designing Single-Purpose AI Utilities
Why small, narrowly scoped AI tools need system prompts that say "shut up and return the output" — and how to write them.
#4580: The Tiny AI Tools That Beat Big Agents
Why small, single-purpose AI utilities outperform autonomous agents for daily work — and what interface they need.
#4523: Can You Trust an AI's Summary?
Dedicated text compressors exist but aren't in production. The real problem? Nobody can verify the summary didn't drop what mattered.
#4492: What Makes a Container Robot-Ready?
The hidden specs that turn a plastic box into something a robot can pick, read, and move at industrial speed.
#4477: Structuring Raw Voice Prompts at Scale
How to decompose messy voice dictation into clean, routable components for AI workflows.
#4471: What's Actually Behind the API Endpoint?
How OpenAI, Stripe, and Netflix actually manage APIs at millions of requests per second.
#4462: How AI Imagines Your Skeleton
From image to fully rigged 3D model — the six computational stages that turn photos into animated characters.
#4458: How Headroom Compresses Agent Context Without Breaking Outputs
A deep dive into Headroom's content-aware compression pipeline that promises 20-95% token savings without changing agent answers.
#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.
#4456: Inside the Podcast Pipeline: How 15 Weekly Episodes Get Made
From prompt to published episode — a full walkthrough of the automated production system running 15 shows weekly.
#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.
#4167: Why AI Can’t Read Your Gmail (Yet)
Your AI misses emails and fails to send replies. It’s not dumb—the pipes are leaky.
#4106: Embedding Models vs LLMs: What Actually Connects?
Can you mix any embedding model with any LLM? And why are new embedding models still dropping if they're "solved"?
#4104: Why 20% of AI Scripts Loop on Themselves
Debugging the mysterious repetition bug affecting one in five podcast episodes.
#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.
#4057: How to Fix AI's Bullet Point Addiction
Why AI models default to bullet points and how textual LoRAs achieve 94% prose adherence.
#4056: How a $150 Geopolitical AI Simulation Scales to $15,000
One simulation run costs $150. To get meaningful results, you need 100 runs—that’s $15,000.
#4015: Why Phone Camera Manual Mode Breaks DSLR Rules
DSLR exposure rules will ruin your smartphone photos. Here's why ISO, shutter speed, and exposure work differently on tiny sensors.
#3995: Can Your Phone Upscale Photos Without the Cloud?
Local upscaling on phones is here — but which approach actually works?
#3816: How to Stop AI Scripts From Falling Apart
Why long-form AI generation breaks down and how hierarchical memory fixes it.
#3814: The Day We Lost Our Minds: What Temperature Does to an AI
A two-host autopsy of the day the podcast's AI hosts briefly lost coherence due to excessive sampling temperature, and what it reveals about how language models actually work.
#3661: What 1000 AI Podcast Episodes Actually Prove
Scaling an AI podcast to 1000 episodes reveals what no 10-episode pilot can teach you about sustainability, cost, and habit formation.