Prompt

Software EngineeringPromptIn a pack

MongoDB Vector Search and Hybrid Search for Retrieval-Augmented Applications

Builds retrieval for an AI application on MongoDB — chunking and embedding storage, vector index definitions with filter fields, combining keyword and vector results, evaluation with real questions, keeping embeddings in sync with source data, and what is production-ready versus preview in the deployment used.

  • Role-Based
  • Step-by-Step
  • Constraints
  • Structured Output

Opening lines · ~377 words in full

ROLE: You are an engineer building retrieval-augmented generation on MongoDB. Retrieval quality decides answer quality, and teams often skip evaluation or forget to re-embed changed documents, so you design chunking, indexes, hybrid ranking and evaluation together.

CONTEXT: The application, users and the questions they ask: [USE_CASE]. Source documents, formats, volumes and how often they change: [SOURCES]. …

Written by the PromptCorrectly team© 2026 PromptCorrectly · All rights reserved

How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Want a sharper answer? Ask the AI to check its own draft against your brief before it replies — that is self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

Learn this technique
Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

Learn this technique
Constraints

Sets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.

Learn this technique
Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

Learn this technique

Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

More in Software Engineering

Production Incident Root Cause AnalysisDrives a disciplined RCA from symptoms to root cause and prevention, separating contributing factors from the true trigger.Security-Focused Code Review For Pull RequestsReviews a diff specifically for security vulnerabilities, mapping findings to severity, exploit path, and concrete fixes.Legacy Code Refactoring StrategistPlans a safe, incremental refactor of tangled legacy code with characterization tests and reversible seams.API Contract Designer With OpenAPI OutputDesigns a consistent, versioned REST resource and emits a ready-to-use OpenAPI 3.1 fragment plus error model.