Kimi K2: The Next Big Thing in AI?

In this episode of The Build, Cameron Rohn and Tom Spencer dissect Kimi K2's potential and trace its implications for AI development and product strategy. They begin by assessing Kimi K2 as an AI agent platform, comparing local inference trade-offs and state-of-the-art model performance while referencing Langsmith for observability and MCP tools for model control and routing. The conversation then shifts to developer tooling and workflows, where Vercel deployment patterns, Supabase as an edge-friendly backend, and continuous integration practices are evaluated for low-latency agent orchestration. They explore architecture decisions next, debating monolithic versus microservice approaches for agent stacks, strategies for state management, and how to integrate Langsmith traces into debugging and monitoring. The hosts move on to building in public and entrepreneurship insights, sharing practical tactics for community-driven roadmaps, open source contributions, and monetization options such as hosted tiers or API quotas. They also touch on developer experience, demonstrating how MCP tools and frameworks can simplify model updates and safe rollouts. Throughout, the episode balances technical detail—agent design, latency mitigation, observability—with startup-level choices about product-market fit and growth. The conversation closes by urging builders to iterate publicly, instrument thoroughly, and prioritize architecture that enables rapid experimentation and sustainable scaling.