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Jev full tutorial: 3 prototypes built live

Scores relevance and routes between local voice input and browser execution.

▶ Watch on YouTube ↗
FULL VIDEO
VIDEO KEY TAKEAWAYS18 mins · @Moritz Kremb (Prompt Warrior)

Core takeaway

Starting from getting an API key, Moritz hand-writes three complete prototypes live: voice-controlled browser automation, relevance triage for vector-memory retrieval, and an extension that auto-skips YouTube sponsor segments. It is one of the most complete hands-on introductory videos in the community.

Key chapters

  • 00:00Tutorial overview: the three prototypes built today
  • 02:15Environment setup and TypeSafe API key configuration
  • 04:50Prototype 1: voice-controlled real-time browser navigation
  • 09:30Prototype 2: fast relevance triage for RAG vector retrieval
  • 14:10Prototype 3: detecting sponsor segments in a video caption stream
  • 16:40Summary and outlook for future agent architectures

Key insights

  • Shows Jev's very low latency when interacting with real-time multimodal input (voice) and external systems (browser, video stream);
  • In RAG, using Jev first to check whether the top-K retrieved documents are actually relevant greatly reduces LLM hallucination;
  • All code is written in concise TypeScript and works out of the box.
Gotchas
  • Watch the upstream speech-to-text latency; local Whisper or fast streaming ASR is recommended;
  • Sponsor detection depends on clean, timestamped caption text.

Overview & result

Moritz starts from getting the API key, then builds three prototypes live: a voice-controlled browser, vector memory retrieval triage, and a YouTube topic scorer.

How Jev fits in the loop

  1. The surrounding agent or application prepares a bounded state and candidate actions.
  2. Jev performs the candidate selection & scoring decision described by the source.
  3. Application code executes the selected action and handles low-confidence or exceptional cases.

How to reproduce

  1. Open the linked source and verify the author, workflow, and claimed Jev role.
  2. Recreate the smallest bounded decision with your own inputs and credentials.
  3. Measure accuracy, latency, cost, and fallback behavior before production use.

Why this build matters

Scores relevance and routes between local voice input and browser execution.

Limitations

  • This directory entry summarizes the linked source and is not an independent benchmark.
  • Reported results may not generalize to a different dataset, policy, or runtime.

Patterns

Browser AgentsAgent Evaluation