How To Get Better Responses From AI

Do you ever find yourself disappointed with the responses from AI tools like ChatGPT, Gemini, or Claude? Whether you’re an avid enthusiast or AI-curious, you’ve likely experienced an underwhelming output from one of these platforms.

Yes, AI is getting better every day, but there are some limitations that may be hampering your efforts. Let’s breakdown what they are and how to overcome them.

Common Issues With AI

Context Window Saturation

You’ll notice that the AI starts forgetting earlier details or answers inconsistently. Every model has a fixed token limit. Once that limit is breached, older tokens drop off (“truncated”), so the model literally no longer “sees” the earlier part of the conversation.

When an AI reads or writes text, it doesn’t see whole words or characters. Instead, it chops everything into small, consistent-sized pieces called tokens and processes those. Think of tokens as Lego bricks the model snaps together (or pulls apart) to build language.

Hallucination

When you see factual errors, numbers that don’t add up, or wild guesses in the responses you receive, it’s clear the AI is “hallucinating” or fabricating answers. It’s not not doing this on purpose, it’s just trying to be helpful when it doesn’t have enough context from the prompt.

Remember that AI is still a computer and it’s using probabilities learned from its training to predict the next word or number to fill in the blank. Anyone who has been in a casino knows that probabilities don’t always work in our favor.

Prompt Decay

Sometimes the AI will “forget” an instruction that you provided it earlier in the chat and you’ll find yourself reminding it of a specific requirement or parameter. As your chat session with the AI lengthens, some relevant instructions may get buried or diluted.

How To Overcome These Issues

When you encounter these common challenges with AI tools, it’s important that you re work your prompts with these tips:

• Chunking – To avoid having the AI over saturating its context window, break your tasks into smaller, more carefully worded prompts. At each stage you can summarize intermediate results before moving on.
• Anchoring – Repeat or reference critical constraints in each new prompt (“Reminder: maintain a neutral tone and cite sources”).
• Structuring – Giving the AI a clear format like “Give me three bullet points, each under 20 words” it can refocus its output.

Conclusion

Improving your prompt-writing skills is an ongoing process, but the results are worth it. By understanding AI's limitations and applying these techniques, you'll see a significant improvement in the quality and accuracy of responses. Remember, the best AI outputs almost always come from the best inputs—your prompts.