Pete Lada

Pretty convinced that multi model is the future of AI platforms Some models are much better at specific tasks than others, whether that is coding with Anthropic, writing with ChatGPT or image generation on Gemini Token costs seem to also vary wildly between models and depending on type of usage The best AI tools will need to optimize giving users the best experiences while also minimizing overall token cost to protect their own gross margins Multi model also ensures you don’t become captive to any one specific model From a relationship leverage perspective, it just makes the most sense in my head Would love to hear perspectives from AI founders or CEOs who are working with these tools on a daily basis > Are you seeing token costs go up across models? > What goes into the decision making behind choosing a model? > If you are not multi model, why?

Linear Interface Refresh A visual update designed to reduce noise and bring structure back into focus as the Linear product continues to evolve. Rolling out today.

If I were a founder in 2026, I'd choose Perplexity Computer. It unifies 19+ frontier models (including Grok for speed), orchestrates sub-agents, and handles end-to-end projects—research, design, code, deployment, even real tasks like booking or forms. One prompt, full execution. Scales a solo founder like nothing else on the list. What are you running with?

POV: You give Perplexity Computer a Kalshi API Key

Introducing Perplexity Computer. Computer unifies every current AI capability into one system. It can research, design, code, deploy, and manage any project end-to-end.

Introducing Model Council in Perplexity. Run three frontier models at once, compare outputs, and get a more accurate, higher‑confidence answer. Available now on web only for Perplexity Max subscribers.