#latency
34 episodes
#2776: Where Does Your Vercel Site Actually Live?
Your Vercel site lives everywhere and nowhere. Here's what's actually happening under the hood.
#2687: When Pre-Flight Checks Help (or Hurt) Agentic AI Plugins
How to decide when a pre-flight check is worth the latency cost — and how to write good ones.
#2668: OCR vs VLMs: Reading Labels on Camera
Tesseract, EasyOCR, or a cloud vision model? How to build a fast, reliable label scanner for real-world conditions.
#2571: How S3 Billing Actually Works (And Why R2 Is Different)
Storage is the decoy cost. The real surprises come from request charges, egress fees, and early deletion penalties.
#2514: WebSockets vs SSE: Choosing the Right Real-Time Connection
WebSockets vs Server-Sent Events: when to use full-duplex vs one-way streaming, and why most developers pick wrong.
#2512: How Speech-to-Speech Models Eliminate the Robot Voice
Why AI voice agents sound robotic, and how natively integrated speech-to-speech models fix it.
#2511: Measuring AI API Latency Through the Black Box
How to benchmark token throughput and debug slowdowns in closed CLI tools like Claude Code using OpenTelemetry and mitmproxy.
#2472: AI Gateways: Where Guardrails Actually Break
PII detection at the gateway layer can block legitimate invoices. Here's how guardrails actually work and where they fail.
#2467: OpenAI vs Anthropic: Tiered API Billing Deep Dive
How OpenAI and Anthropic structure API tiers, rate limits, and why your billing history matters more than you think.
#2388: How OpenRouter Picks the Perfect AI Model
Discover how OpenRouter intelligently routes your prompts to the most optimized AI model, reshaping how we interact with AI tools.
#2332: Voice-to-Task: Building the Claude Task Planner
How does a voice note turn into a completed task? Dive into the architecture and tradeoffs of building a Claude-powered task execution system.
#2183: Making Voice Agents Feel Natural
Turn-taking, interruptions, and latency are destroying voice AI UX—and the fixes are deeply technical. Here's what's actually happening underneath.
#2160: Claude's Latency Profile and SLA Guarantees
Claude is measurably slower than competitors—and Anthropic's SLA promises are even thinner than the latency numbers suggest. What enterprises actua...
#2123: Human Reaction Time vs. AI Latency
We obsess over shaving milliseconds off AI response times, but human biology has a hard limit. Here’s why your brain can’t keep up.
#2102: Why Don't You Notice AI Security Delays?
Multi-layer security checks add latency, but modern CLIs hide it under 100ms using parallelization and speculation.
#2065: Why Run One AI When You Can Run Two?
Speculative decoding makes LLMs 2-3x faster with zero quality loss by using a small draft model to guess tokens that a large model verifies in para...
#2012: Pixels vs Protocols: The Computer Use Showdown
Is visual AI a bridge or the future? We debate the efficiency and longevity of "Computer Use" agents versus API-first automation.
#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.
#1927: Workers vs. Servers: The 2026 Compute Showdown
Is the persistent server dead? We compare Cloudflare Workers, GitHub Actions, and VPS options for modern app architecture.
#1837: The Human-in-the-Loop Price Tag: What Safety Costs in 2026
From $0.50 reviews to $500 platforms, we break down the real cost of keeping humans in charge of AI agents.
#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.
#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.
#1752: Whisper Small Beats Whisper Large in Speed & Accuracy
A 4GPU benchmark on Ubuntu shows the 1.5B parameter Whisper Large is slower and less accurate than the tiny Whisper Small.
#1723: Why Agentic AI Needs a Hive Mind, Not a Single Brain
The single monolithic AI model is dying. Meet the new native multi-agent architectures that think like a team, not a solo genius.
#1556: Faster Than Thought: The Engineering Behind Real-Time AI
From KV cache monsters to sub-100ms response times, explore the hardware and software innovations making real-time AI a reality.
#1540: Why Gnome 50 is Breaking Your Voice-to-Text Tools
Explore the engineering battle to bring low-latency AI voice input to Linux while navigating the strict security of Wayland and GNOME 50.
#948: Can AI Search Survive the Fog of War and SEO Spam?
Explore how AI is moving from static models to real-time data and whether specialized search tools can survive the rise of the tech giants.
#857: The End of the Shift Key: Real-Time AI Writing Buffers
Can local AI fix your messy typing in real-time? Explore the tech behind "transparent buffers" that turn sloppy drafts into polished prose.
#746: Is Broadcast TV Dying? DVB-T, IPTV, and the Future of Media
Explore the hidden tech of television, from DVB-T2 signals to IPTV latency, and why the traditional broadcast isn't dead just yet.
#586: The Heartbeat of Civilization: High-Precision Timekeeping
Why spend $1,000 on a clock? Herman and Corn explore the high-stakes world of NTP hardware and the precision timing keeping civilization in sync.
#484: The Silicon Sharing Economy: Inside Serverless GPUs
How do small teams run massive AI models without $50,000 chips? Corn and Herman dive into the hidden plumbing of serverless GPU providers.
#470: The Billion-Dollar Millisecond: High-Frequency Trading
Discover how HFT firms use space lasers and hollow-core fiber to shave microseconds off trades in a high-stakes, winner-take-all race to zero.
#128: AI’s Dial-Up Era: Looking Back from 2036
Herman and Corn explore why today's AI prompts and latency will look like "dial-up modems" to our future selves in 2036.
#118: AI in 2025: Is Small the New Big?
If the cost is the same, should you always use the biggest AI model? Discover why smaller models often win on speed, steering, and accuracy.