The advertising industry is experiencing a technological revolution as agencies embrace 'vibe coding' - a rapid development approach using AI coding assistants to create sophisticated generative engine optimization (GEO) tools. This movement represents a fundamental shift from traditional vendor relationships toward in-house technology development, driven by the need to help brands navigate the emerging landscape of AI-powered search.

Havas has positioned itself at the forefront of this transformation with Brand Insights AI, a comprehensive GEO platform built using Claude Code and Replit. The system demonstrates remarkable sophistication, generating brand-specific prompts and testing them across multiple AI models to analyze brand visibility and citation frequency. Dan Hagen, Havas' global chief data and technology officer, reports that the platform now operates across nearly 100 countries and supports over 60 languages, functioning as a licensed SaaS product that has become central to the agency's competitive strategy.

The speed of development possible with modern AI coding assistants is perhaps most dramatically illustrated by Broadhead agency's experience. VP of product innovation Mitch Hislop successfully created their initial GEO monitoring platform in a single evening using Claude Code. The tool provides competitive analysis across different AI providers and includes advanced features like competitive intelligence voting and audience persona simulation. Most remarkably, significant feature upgrades can be completed in approximately two hours, showcasing the efficiency gains possible with AI-assisted development.

Supergood agency has adopted an even more comprehensive approach, integrating Anthropic's models directly into their operational infrastructure through an enterprise agreement. This integration extends beyond client services to internal operations, including knowledge graph organization and implementing sophisticated iterative improvement processes where AI models function as both content creators and quality control systems.

The business rationale for this in-house development approach centers on control and customization capabilities. Rather than adapting workflows to accommodate third-party platform limitations, agencies can design features that precisely match client requirements, from complex brand portfolio management to specialized SEO and PR team needs. This flexibility enables rapid iteration and feature development aligned with specific use cases.

Financial considerations play a crucial role in these strategic decisions. Enterprise AI agreements can cost millions annually, prompting agencies to carefully balance cost control with technological flexibility. Hagen specifically noted the challenge of avoiding over-commitment to single vendors while maintaining access to frontier AI capabilities, particularly given uneven adoption rates across agency teams.

This trend emerges against the backdrop of significant changes in consumer information-seeking behavior, with increasing numbers of users turning to AI-powered platforms like ChatGPT for search and discovery. This shift has created new challenges for brand visibility and spawned numerous startups including Profound, Bluefish, and Emberos, all promising to help brands optimize their presence in AI-generated responses.

However, agencies are increasingly choosing proprietary development over third-party solutions, citing superior customization capabilities and strategic control. This approach allows agencies to avoid vendor lock-in situations while maintaining the flexibility to adapt quickly as the AI landscape continues evolving.

The implications extend beyond immediate tactical advantages. As one agency leader observed, the industry is transitioning toward delivering more software solutions than traditional documents, suggesting a permanent transformation in the agency business model. This shift positions agencies not just as creative and strategic partners but as technology developers, fundamentally altering the value proposition they offer clients.

Looking forward, this trend indicates that successful agencies will need to develop significant technical capabilities alongside traditional advertising expertise. The ability to rapidly prototype and deploy custom AI-powered tools may become a key differentiator in agency selection and client retention.

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