When AI fails to deliver what we expect, we often blame it for being "buggy" or "unreliable." But perhaps the problem isn't with AI - it's with our mental model. We keep trying to use AI like software, when it behaves much more like a human colleague.

The "AI is not software" argument correctly identifies what AI isn't - but stops short of recognizing what it is. AI doesn't just lack the properties of software; it actively exhibits human-like behaviors. This isn't anthropomorphism. It's a practical observation with immediate implications for how we work with these systems.

Non-Determinism as Feature

The same prompt produces different outputs. This variability isn't a failure of engineering - it's what enables creativity. Temperature settings function like energy levels. Context windows create attention limits. Previous exchanges influence future responses. These aren't metaphors; they're functional parallels to human cognition.

Software bugs are deterministic - reproduce the conditions, reproduce the bug. AI "errors" are stochastic - the same prompt that produced brilliance might next produce nonsense. This isn't broken software; it's tired human. The fix isn't debugging but understanding conditions for optimal performance.

The Instruction Paradox

Over-constrained prompts degrade output quality. Add twenty requirements to a prompt and watch coherence collapse - precisely how humans respond to micromanagement. The optimal instruction level follows human management principles: clear intent with execution freedom.

Consider this progression:

"Write about dogs" - too vague
"Write 500 words about golden retrievers including history, temperament, care requirements, health issues, training tips, and famous examples, using formal tone but accessible language, with three citations" - over-constrained
"Write a comprehensive guide about golden retrievers for potential owners" - optimal

Software improves with more specifications; AI, like humans, improves with better context and clearer goals.

Personality Without Source Code

Claude differs from GPT differs from Gemini in consistent, learnable ways. These aren't different programs but different personalities. We develop working relationships with specific models just as we adapt to colleagues' work styles.

Claude might refuse tasks with ethical concerns while GPT eagerly attempts them. Gemini might excel at technical explanations while...

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