Explore seven essential practices for effective AI prompt engineering in 2025, enhancing response accuracy and relevance across industries.

In the world of artificial intelligence, privacy and control over data are becoming increasingly important. Cloud-based AI services, while convenient, can raise concerns about data security and privacy. Fortunately, there are tools available that allow you to run AI models locally on your machine, giving you full control over your data while still harnessing the power of advanced language models.

Artificial intelligence (AI) systems like large language models are highly sensitive to how prompts are phrased. Even small tweaks to a prompt can produce very different results. When reading new AI research papers, it's often useful to test out the prompts yourself on your own models. This allows you to reproduce the paper's results and compare differences due to your model architecture, training data, etc.

Testing your AI systems against malicious prompt injections is an important part of responsible AI development. PromptMixer provides some useful tools to help with testing prompt injections.