Build Real-Time Voice Apps Without Pause Latency
John Lindquist explains how streaming token classification cuts voice latency and triggers actions without user pauses.
Jev: 8 real use cases this fast, cheap model
With Claire Vo, John Lindquist · Sunday, October 4, 2026
Claire Vo and John Lindquist discuss Jev, an ultra-fast, low-cost decision and classification model from Typesafe AI. They explore architectural patterns and real-world product demos, including real-time voice task management, pairwise data deduplication, multi-step application routing, multi-agent collision avoidance, and game reasoning.
Key takeaways
- Most voice apps stall because they wait for silence detection or an enter key before sending transcripts to a slow LLM. Read more →
- Typesafe AI's decision model, Jev, executed moves 10x faster and 4x cheaper than a low-reasoning LLM in live blitz chess benchmarks. Read more →
- Generative models process unstructured text to produce unstructured text, introducing latency and hallucination risks when applications only need deterministic routing. Read more →
- Heavy AI workloads are hitting physical hardware ceilings, forcing engineers to buy extra storage drives and distribute execution across dedicated Mac minis. Read more →
- Running full LLM prompts across every row in a messy database quickly destroys engineering budgets and causes severe latency bottlenecks. Read more →
- Asking large generative models to predict complex multi-agent execution plans up front creates fragile pipelines that break when agents touch shared resources. Read more →
6 articles from this episode
Why Constrained State Spaces Beat Large Reasoning Models
How Typesafe AI's Jev cuts latency by 10x and cost by 4x over LLMs by treating web actions and games as discrete decision spaces.
Why Fast Decision Models Beat Generative LLMs for Routing
Claire Vo and John Lindquist explain why 4-cent decision models replace bloated LLMs for deterministic classification and routing.
Why Claire Vo Runs 40 Grok Bots on Stacks of Mac Minis
AI engineering is shifting from file trees to agent org design. Here is why top builders are buying extra hardware and running swarms of bots.
How to Deduplicate Massive Datasets Without LLM API Bills
Claire Vo and John Lindquist explain how to use fast decision models and tiered LLM validation to deduplicate messy databases cheaply.
Stop Asking Massive LLMs to Plan Multi-Agent Workspaces
Claire Vo and John Lindquist explain how fast classification models like Jev solve agent collision avoidance through step-by-step state checks.
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