Pulse assigns templates to users — but we want intelligent conversation, not templated responses

Assessing AI Personalization: Are Templates Replacing Genuine Agency in Conversations?

In recent developments within AI-driven platforms, there’s a growing concern about the shift from authentic, adaptive interaction toward more standardized, template-based responses. This trend raises critical questions about the future of artificial general intelligence (AGI) and the direction in which leading AI companies like OpenAI are heading.

Understanding Pulse’s Approach

Pulse, a notable feature in the AI ecosystem, currently assigns response templates to users based on behavioral data collection. The aim appears to be personalization; however, the implementation results in responses that are pre-programmed and repetitive. From a user’s perspective, this implementation often feels more like weightier customer segmentation rather than an enhancement of conversational intelligence.

Identified Issues with the Current Model

• The response system lacks the flexibility of true understanding, instead relying on static, context-insensitive replies.
• There’s an observable shift from dynamic, context-aware dialogue to reliance on pre-defined templates.
• The platform seems to prioritize categorization—such as user profiles—over genuine comprehension of user intent.
• Such practices suggest a regression in AI development, moving away from the ambitious goal of achieving AGI, and instead fostering a more commodified, superficial interactions model.

The Distinction Between Commodification and True Intelligence

This focus on templated responses can be interpreted as the commodification of AI—reducing complex conversations to simplified scripts or categories—rather than fostering real intelligence. The core promise of GPT-4 and similar models was emergent reasoning: the ability to generate nuanced, contextually appropriate responses, not just responses tailored based on user profiles.

Key Questions for the Future of AI Development

• Strategic Direction: Is OpenAI prioritizing template-based “personalization” over advancing genuine conversational intelligence?
• Response Quality: Are we trending toward AI that provides “your type of answer” instead of “the best possible answer,” thereby limiting the scope of AI’s potential?
• Economic Factors: Could the shift toward categorization and templating be a result of monetization strategies—simplifying models, segmenting users, and serving pre-designed responses to maximize revenue?

For many users, the appeal of AI lies in its capacity for emergent reasoning and authentic understanding. The current pivot toward template-driven responses seems to contrast starkly with this vision and warrants critical examination.

Final Thoughts

As AI developers and consumers, it’s essential to question whether these changes represent meaningful progress toward AG