Tips for getting the most out of AI through prompt engineering

November 7, 2026 Rachel Kim – Technology Editor Technology

Optimizing Prompt Engineering and Memory Settings for Large Language Models

Getting the most out of artificial intelligence platforms requires careful prompt structuring, strict output verification, and deliberate memory management to avoid common cognitive traps.

The Tech TL;DR:

  • Specificity in prompts drastically improves retrieval accuracy, functioning similarly to advanced search operators.
  • AI platforms regularly hallucinate citations, requiring independent verification of all linked sources.
  • Customizing AI memory configurations allows chatbots to prioritize specific sources, such as linking to The New York Times because you already have a subscription.

Engineering Specific Prompts Prevents Generic AI Output

Users often experience frustrating results with large language models because they treat conversational interfaces like omniscient entities rather than statistical research assistants. Effective prompt engineering mirrors advanced search query building, demanding specific parameters, dimensions, and constraints. When shopping or searching for complex assets, supplying a physical boundary or precise context prevents generic output. Instead, taking a picture of the spot where a bookshelf needs to go, providing the AI with the dimensions or range of dimensions looking for, and asking the chatbot to find the best options given those constraints saves a lot of time and allows working smarter.

Input tokens process user prompts and contextual constraints, while output tokens generate responses. Writing overly verbose prompts or requesting exhaustive essays exhausts usage limits quickly. Directing the model to provide concise answers or specific formats preserves tokens and reduces response latency.

curl https://api.anthropic.com/v1/messages \
  --header "x-api-key: $ANTHROPIC_API_KEY" \
  --header "content-type: application/json" \
  --data '{
    "model": "claude-3-5-sonnet-20241022",
    "max_tokens": 150,
    "messages": [{"role": "user", "content": "Provide a concise 3-bullet summary of local memory constraints."}]
  }'

Adjusting Privacy Settings Restricts Stored User Data

While this persistence streamlines routine tasks like drafting correspondence, it introduces privacy considerations regarding stored user data.

Users who prefer complete data isolation can inspect and adjust privacy settings to restrict data retention. Alternatively, explicit instructions can command the chatbot to recall specific behavioral preferences or omit certain sources during information retrieval.

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