Cognitive Overload on LLM call

Great question. Even when your prompt fits within the token limit, asking an LLM to handle many diverse and layered instructions in one call creates what we refer to as:

🧠 Cognitive Overload in LLMs

This is the most common term. It refers to situations where:

• The number of simultaneous tasks overwhelms the model's internal attention mechanisms.
• The model fails to prioritize, leading to skipped or incorrect sub-tasks.
• Outputs may be incomplete, inconsistent, or ignore formatting rules.

🔍 Other Terms and Concepts That Apply:

1. Instruction Dilution

When many instructions are packed into one prompt, each instruction gets less "weight", and the model is less likely to follow all of them accurately.

2. Semantic Interference

The meaning of one instruction interferes with another. E.g., asking for both raw and formatted output might confuse the model into mixing both.

3. Task Multiplexing / Prompt Overloading

Describes a prompt that tries to combine data retrieval, computation, formatting, reasoning, and narrative writing all at once — leading to model confusion or shallow responses.

4. Contextual Drift

The LLM “forgets” or deprioritizes earlier parts of the prompt as it processes later instructions. This is especially common when multiple tables + tasks are described before the final instruction.

✅ Example of Too Much in One Prompt:

“From table1, get unit sales. From table2, get revenue. From table3, get average revenue per customer. From table4, get sales by product family. Then format revenue in K/M, compare it with target revenue, state whether it's above or below, and write a narrative for each product family.”

Even if it fits token-wise, this places excessive cognitive demands on the LLM:

• It must mentally join four tables
• Understand what to compare
• Apply formatting rules
• Write an insight summary

That’s equivalent to giving a human analyst a multi-tab spreadsheet and asking them to do reporting, charting, and analysis in their head without notes.

✅ Best Practice Summary