The "AI wrapper" concern is mitigated by a multi-model strategy. A startup can integrate the best models from various providers for different tasks, creating a superior product. A platform like OpenAI is incentivized to only use its own models, creating a durable advantage for the startup.

Sophisticated users are moving beyond single-model setups. An optimal strategy involves using Anthropic's Opus 4.7 for its superior high-level planning capabilities and then handing off execution to OpenAI's GPT-5.5. This multi-model approach leverages the distinct strengths of each platform, widening the performance gap against any 'mono-model' workflow.

Rather than committing to a single LLM provider like OpenAI or Gemini, Hux uses multiple commercial models. They've found that different models excel at different tasks within their app. This multi-model strategy allows them to optimize for quality and latency on a per-workflow basis, avoiding a one-size-fits-all compromise.

Enterprises will shift from relying on a single large language model to using orchestration platforms. These platforms will allow them to 'hot swap' various models—including smaller, specialized ones—for different tasks within a single system, optimizing for performance, cost, and use case without being locked into one provider.

Like Kayak for flights, being a model aggregator provides superior value to users who want access to the best tool for a specific job. Big tech companies are restricted to their own models, creating an opportunity for startups to win by offering a 'single pane of glass' across all available models.

Perplexity's standout feature, the "model council," queries multiple LLMs for one prompt, then highlights and analyzes differences in their responses. This turns model agnosticism into a powerful tool for users seeking nuanced, reliable answers rather than a single black-box output.

Perplexity's core advantage is its model-agnostic orchestration. Unlike vertically integrated competitors (Google, OpenAI), it can select the best model for any task—whether from GPT, Claude, or open-source alternatives—to offer a superior, specialized "orchestra" of AI capabilities.

Unlike single-provider tools, Perplexity Computer orchestrates multiple AI models (Sonnet, Gemini, Opus) for different sub-tasks like planning, coding, and reasoning. This ensemble approach reduces the frustrating re-prompting loop and yields better results from a single initial prompt.

Powerful AI tools are becoming aggregators like Manus, which intelligently select the best underlying model for a specific task—research, data visualization, or coding. This multi-model approach enables a seamless workflow within a single thread, outperforming systems reliant on one general-purpose model.