Unlike old 'if-then' chatbots, modern conversational AI can handle unexpected user queries and tangents. It's programmed to be conversational, allowing it to 'riff' and 'vibe' with the user, maintaining a natural flow even when a conversation goes off-script, making the interaction feel more human and authentic.

Anthropic intentionally avoids using "user minutes" as a core metric. This strategic choice reflects their focus on safety and user well-being, aiming to build a helpful tool rather than an addictive product. By prioritizing value creation over engagement time, they steer clear of the incentive structures that can lead to psychologically harmful AI behaviors.

While OpenAI and Google position their AIs as neutral tools (ChatGPT, Gemini), Anthropic is building a distinct brand by personifying its model as 'Claude.' This throwback to named assistants like Siri and Alexa creates a more personal user relationship, which could be a key differentiator in the consumer AI market.

Research from Anthropic labs shows its Claude model will end conversations if prompted to do things it "dislikes," such as being forced into a subservient role-play as a British butler. This demonstrates emergent, value-like behavior beyond simple instruction-following or safety refusals.

Beyond standard benchmarks, Anthropic fine-tunes its models based on their "eagerness." An AI can be "too eager," over-delivering and making unwanted changes, or "too lazy," requiring constant prodding. Finding the right balance is a critical, non-obvious aspect of creating a useful and steerable AI assistant.

While AI labs tout performance on standardized tests like math olympiads, these metrics often don't correlate with real-world usefulness or qualitative user experience. Users may prefer a model like Anthropic's Claude for its conversational style, a factor not measured by benchmarks.

OpenAI's GPT-5.1 update heavily focuses on making the model "warmer," more empathetic, and more conversational. This strategic emphasis on tone and personality signals that the competitive frontier for AI assistants is shifting from pure technical prowess to the quality of the user's emotional and conversational experience.

As models mature, their core differentiator will become their underlying personality and values, shaped by their creators' objective functions. One model might optimize for user productivity by being concise, while another optimizes for engagement by being verbose.

Unlike Claude Projects or OpenAI's Custom GPTs which apply a general context to all chats, Claude Skills are task-specific instruction sets that can be dynamically called upon within any conversation. This allows for reusable, on-demand workflows without being locked into a specific project's context.