Which Frontier Model Will Win the AI-Platform Battle?

Introduction

Dave Steer, CMO of Webflow, brings over two decades of experience leading marketing at category-defining companies like GitLab, Cloudflare, Facebook, and Twitter. His perspective on the AI frontier model race offers valuable insights for marketing leaders navigating the rapidly evolving landscape of AI-powered platforms and their impact on marketing workflows.

The Early I ings of AI Competition

When pressed to pick a wi er among frontier AI models, Steer maintains a pragmatic stance: "I can't make that call because things are changing all the time." His experience using both ChatGPT and Claude in different organizational contexts reinforces that the AI landscape remains fluid. This reluctance to crown a wi er reflects the reality that marketing leaders face - the technology is evolving too rapidly for definitive bets on single platforms.

The conversation reveals an important consideration for marketers evaluating AI tools. While ChatGPT holds first-mover advantage and Claude currently delivers strong performance, the underlying data access may ultimately determine success. Google's Gemini emerges as a potential dark horse precisely because of its co ection to vast data repositories that competitors ca ot match.

Beyond the Commodity Layer

Steer challenges conventional thinking about AI competition with a crucial insight: "The frontier model is the commodity—or it will increasingly become the commodity. It's the context that's added on top of it." This perspective shifts focus from raw AI capabilities to the platforms and workflows built around these models.

Platform Context as Competitive Advantage

For marketing technology leaders, this means evaluating AI tools based on their integration with existing workflows rather than standalone capabilities. The real value emerges when AI platforms understand specific marketing contexts - whether that's website optimization, content creation, or campaign management. Companies that successfully layer contextual understanding on top of frontier models will deliver the most value to marketing teams.

Implications for Marketing Technology Strategy

The discussion highlights three critical considerations for marketing leaders building their AI strategy. First, avoid overcommitting to any single frontier model given the rapid pace of change. Second, focus on platforms that add contextual value to your specific marketing workflows rather than raw AI power. Third, consider how data access and integration capabilities might determine long-term wi ers in the AI platform race.

Marketing teams should evaluate AI tools based on their ability to understand and enhance existing processes. Whether it's GitHub and GitLab competing in developer workflows or Webflow positioning itself for marketing workflows, success will come from deep integration with the tools and processes teams already use.

Conclusion

The AI frontier model battle remains in its early stages, with no clear wi er emerging. For marketing leaders, the key takeaway is to focus less on picking the "wi ing" AI model and more on identifying platforms that add meaningful context to their specific workflows. As frontier models become commoditized, the real competitive advantage will come from platforms that understand and enhance the unique requirements of marketing teams. Rather than betting everything on one model, smart marketers should remain flexible and prioritize solutions that integrate seamlessly with their existing technology stack while delivering tangible value to their workflows.