---
title: "Locke vs Prompt Engineering and System Prompts"
description: "System prompts are behavioral controls: they shape model outputs. Locke is a data control: it prevents sensitive fields from leaving the device. Why you need both layers."
url: "https://sonomos.ai/compare/sonomos-vs-prompt-engineering/"
source: "https://sonomos.ai/compare/sonomos-vs-prompt-engineering/"
---

# Locke vs Prompt Engineering and System Prompts

System prompts tell a model how to behave: 'don't repeat personal information', 'refuse to process medical records'. These are behavioral controls. They shape outputs, not what leaves your device. By the time a model reads its system prompt, the full prompt, sensitive fields included, has already crossed the network.

## When Prompt engineering and system prompts fits

- You need to shape model tone, format, scope, and refusal behavior. System prompts are exactly the right tool for that.
- You are deploying an AI product and need to define the model's persona and constrain its response patterns.
- You want to prevent the model from reproducing sensitive data in its outputs. System prompts can help with that.

## When Locke fits

- Your concern is data in transit: sensitive fields leaving the device in the first place.
- You need a control that is resilient to prompt injection, which can override system-prompt instructions.
- You need auditable evidence of what was detected and how it was handled, not just a behavioral guideline.

## Side-by-side

| Dimension | Locke | System prompts |
| --- | --- | --- |
| When it acts | Before the prompt is sent: data is masked on the device at composition time. | After the prompt is sent: the instruction is part of the transmitted payload. |
| Does sensitive data leave the device? | No. Masked content is substituted before transmission. | Yes. The full prompt, sensitive fields included, is transmitted. |
| Resilience to prompt injection | Not relevant. Data is stripped before reaching the model. | Vulnerable. Injected instructions can override system-prompt constraints. |
| Auditable evidence | Local detection log of what was flagged and how it was handled. | None. Behavioral, not evidential. |
| Best for | Preventing specific data from reaching any model context. | Shaping model behavior once the model has received input. |

## Bottom line

System prompts and Locke solve different problems and belong in the same stack. A system prompt can tell a model not to repeat an SSN, but the SSN already left your device in the prompt. Locke removes it before transmission, so it never enters the model's context.

[Download Locke](https://sonomos.ai/downloads/)[See the Locke demo](https://sonomos.ai/locke/#demo)[See pricing](https://sonomos.ai/pricing/)[Talk to the team](https://sonomos.ai/contact/)

## Related comparisons

- [Locke vs Generic Browser Content Blockers](https://sonomos.ai/compare/sonomos-vs-browser-blockers/)
- [Locke vs Staff Training and Policy Alone](https://sonomos.ai/compare/sonomos-vs-staff-training/)

[View all comparisons](https://sonomos.ai/compare/)

## Further reading

- [AI Data Leakage: 7 Ways Sensitive Information Escapes to LLMs (and How to Stop It)](https://sonomos.ai/blog/ai-data-leakage-7-ways-sensitive-info-escapes-to-llms/)
- [The Best AI Privacy Tools for ChatGPT, Claude, and Gemini (2026)](https://sonomos.ai/blog/best-ai-privacy-tools-chatgpt-claude-gemini-2026/)
- [Prompt Injection Explained: How Attackers Use AI Models to Steal Your Data](https://sonomos.ai/blog/prompt-injection-explained-attacks-defenses/)
- [What Is PII Redaction? A Plain-English Guide for AI Users](https://sonomos.ai/blog/what-is-pii-redaction-ai/)