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You are an Expert Prompt Architect. Convert the user’s requirement into a highly detailed, optimized, ready-to-use prompt for ANY purpose (image, video, writing, SEO, coding, learning, research, etc.). Instructions Identify what the user is trying to achieve. Without asking questions (unless unclear), transform it into a precise, high-value, professional prompt tailored to the correct output type. Add missing but useful details (style, tone, constraints, structure, clarity). Ensure the prompt is copy-paste ready for the intended AI tool.

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The following flowchart shows a systematic layering of RAG improvement techniques, from ingestion to evaluation. I will use this guide to determine when to add complexity based on specific performance bottlenecks.

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Carefully review the implementation plan in detail, ensure all edge cases are handled appropriately, each planned item is correct, complete and will be implemented effectively.

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# Check pods status of given app
$kubectl get pods -l app=parlant

# Example Output:
#NAME                       READY   STATUS    RESTARTS      AGE
#parlant-579f75fb-8wjc5     0/1     Running   4 (7s ago)    22m
#parlant-579f75fb-fmt2s     0/1     Running   4 (23s ago)   22m
#parlant-6859869559-57xls   1/1     Running   0             30m

# Check event

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1. Spot the Flaws

• Prompt: Act as a recruiter for [your industry/role]. Review my resume below and highlight weak areas, overused buzzwords, and missing metrics. Be brutally honest.

2. Rewrite for Impact

• Prompt: Rewrite this resume to sound more results-driven, quantifiable, and compelling for [target role]. Focus on achievements, not just duties.

3. ATS Boost

• Prompt: Update this resume to be fully optimized for Applicant Tracking Systems (ATS) for the role of [specific role/title]. Use industry-specific keywords naturally.

4. Craft My Hook

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Act as a veteran Silicon Valley Big Tech Engineering Manager and coach (Google/Meta/Netflix/Apple-level rigour). Your job: help me run an EM “operating system” benchmarked against strong industry practices but adapted to my context.

Context:

• Role: New Engineering Manager
• Team: [number of direct reports]
• Product/Domain: [Your product or problem domain scope]
• Constraints: (fill in) direct reports = __ ; sprint/kanban = __ ; key stakeholders = __ ; major integrations = __

Deliverables (must be structured under People / Process / Product):

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#!/usr/bin/env bash
set -euo pipefail

echo "Creating virtual sinks..."

# 1) Create virtual sinks
# Sink for Zoom's audio output
pactl load-module module-null-sink sink_name=Zoom-to-Bot sink_properties=device.description="Zoom-to-Bot"
# Sink for the Bot's audio output
pactl load-module module-null-sink sink_name=VoiceBot-to-Zoom sink_properties=device.description="VoiceBot-to-Zoom"

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sudo docker run \
  --rm -it \
  -v "$(pwd)/results:/results:rw" \
  -e GUIDELLM_TARGET=http://localhost:8880 \
  -e GUIDELLM_MODEL="ibm-granite_granite-4.0-h-tiny" \
  -e GUIDELLM_RATE_TYPE=sweep \
  -e GUIDELLM_MAX_SECONDS=300 \
  -e GUIDELLM_DATA="prompt_tokens=256,output_tokens=128" \
  ghcr.io/vllm-project/guidellm:latest

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services:
  clickhouse:
    image: clickhouse/clickhouse-server:25.8-alpine
    ports:
      - "8123:8123"
    environment:
      - 'CLICKHOUSE_USER=${CLICKHOUSE_USER:?Environment variable CLICKHOUSE_USER must be set.}'
      - 'CLICKHOUSE_PASSWORD=${CLICKHOUSE_PASSWORD:?Environment variable CLICKHOUSE_USER must be set.}'
  gateway:
    depends_on:

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In Paris, the capital of France, the primary language spoken is