Metaview Candidate Sourcing Agents

Overview & Result

Metaview's CTO says the company shipped Jev into its agents and decomposed their work into small semantic questions with team-defined thresholds. He reports that candidate searches in the sourcing product now take seconds instead of minutes, with similar accuracy and lower cost per search.

How Jev fits in the loop

1. Break an agent workflow into smaller semantic questions, as described by Metaview's CTO.
2. Ask Jev those bounded questions inside the sourcing workflow.
3. Set application thresholds for the responses.
4. Use the reported questions and thresholds as a way to revise agent behavior without relying only on a system prompt.

How to reproduce

1. Read the Metaview CTO's original post and watch its before/after candidate-search video.
2. Inspect the TypeSafe CEO's quote post for the original source attribution.
3. To evaluate the reported change, compare the same candidate-search tasks before and after Jev using disclosed timing, accuracy criteria, and per-search cost.

Why this build matters

It is a first-hand report of Jev being used in a production recruiting product, with an original comparison video and a TypeSafe CEO quote post.

Reported performance

Latency: About 10x faster candidate searches, reported by Metaview's CTO

Limitations

• The production integration is not open source, so JevForAgents cannot inspect each agent's implementation or thresholds.
• The reported speed, accuracy, and cost comparison has no published task set or measurement method in the cited post.
• The before/after video and TypeSafe CEO's quote post support that this is a real first-hand account; they do not independently verify the performance figures.

Patterns