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Cost-effective Decision Routing with Jev 1.13

Transition from Opus 5.5 to Jev 1.13 to reduce daily costs from $60–80 to 42 cents. Jev efficiently manages decision-making tasks by selecting from predefined options, while maintaining control over the final output.

added by @orbitalisVector

I was burning $60–80 a day on Opus 5.5 for decisions that never needed a frontier model.

"Keep going?" "Which tool now?" "Is this good enough?" Every one billed at Opus prices. Jev 1.13 handles 10,000 of them for 42 cents.

I moved them over in one evening. Here's the setup.

Jev can't write a sentence. It only picks from the options you give it, which is exactly the job. Everything runs from Claude Code:

1 → Make a TypeSafe account and grab an API key. Never paste it into chat.

2 → Add the official skill: npx skills add typesafe-ai/skills --skill typesafe-ai
Then ask: "Install typesafe-sdk and build me a decision router that picks research / write / review / cheap from the task's current state."

3 → Spell out the options:
• research: sources or evidence missing
• write: enough context, just ship it
• review: unclear, needs a human
• cheap: formatting, lookup, classification

4 → Run one task you do daily (morning brief, inbox, content plan) and watch where Jev sends it.

5 → Start the confidence bar at 0.85. Below it goes to you or to Opus. Above it stays cheap.

6 → Hard limits: max actions per run, max spend per day, a kill switch. Drafts get written, never sent. Publishing waits for you.

Opus still does the thinking and the writing. Jev just picks the road.

Anyone calling that risky hasn't opened their own Opus bill.

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Hermes Setup with 443 Unique Skills

added by @GodsBoy7777

The Hermes setup now features 443 unique skills, utilizing Jev for skill selection. Jev achieved 94.4% exploratory reused-data performance, ensuring confidence-aware decision-making.

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Jev: Fast Decision-Making for LLMs

added by @MichaelLee04

Jev offers a new intelligent decision-making primitive that enhances model routing and classification tasks. It allows for quick and cost-effective decision-making, improving the efficiency of LLM calls in applications.

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Improved Model Routing and Action Review with Jev

added by @FredvanRijswijk

The integration of Jev from @typesafe_ai replaced three steps in Prio, achieving 100% accuracy in model routing and significantly reducing action review time from 5 seconds to 0.25 seconds for clear cases.

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Implementing Jev in AI Agent Fleet

added by @FloRyRy410

A decision layer named Jev was integrated into an AI agent fleet, achieving high accuracy and low latency for decision-making tasks. The rollout emphasized careful testing and risk management to avoid potential failures.

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Jev: Decision-Making Model for Structured Outputs

added by @Al_Grigor

Jev is a model that processes states and typed questions to return structured JSON with probability distributions. It outperforms previous setups in speed and cost, making it ideal for routing and decision-making tasks.

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Integrate Hermes Agent with Grokbot for Enhanced Operations

added by @PixelRainbowNFT

Connect your Hermes Agent to the Grokbot app for streamlined communication and orchestration across multiple Hermes machines. Choose between SSH Relay or API Fleet for optimal performance based on your setup.

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