Scaling Trusted GLP-1 Guidance with Agentic AI Delivery

The company is a global leader in weight management, offering a physician-recommended program that blends clinical science with human connection. Through a worldwide network of coaches and community support, it provides a personalized, evidence-based path to lasting results. In a market crowded with quick fixes and conflicting advice, the company stands apart—grounded in empathy and focused on helping people live longer, healthier lives.

The client partnered with OpenAI to launch an app within ChatGPT that would surface their trusted content—recipes, nutrition guidance, and expert recommendations—directly to users. The opportunity was extremely time-sensitive: as adoption of GLP-1 (Glucagon-Like Peptide-1) medications accelerated, millions of users were actively searching for guidance on what to eat while taking drugs such as Ozempic. The project’s urgency was heightened by OpenAI’s timeline to launch their new ChatGPT Health experience, providing a narrow window to become one of the platform’s initial partners.

The client needed to meet users in the moment of intent inside ChatGPT while maintaining medical credibility and brand trust. Delivering a compliant, high-quality experience quickly was critical to capturing demand before competitors.

The team delivered the solution using an agentic, AI-native delivery model designed to move work in parallel while remaining tightly governed. Rather than relying on a linear, human-only workflow, senior engineers orchestrated a set of specialized AI agents responsible for discrete tasks such as schema design, tool definition, UX component scaffolding, and analytics instrumentation.

Shared, real-time context ensured all agents operated from a single source of truth, while human reviewers remained in the loop—directing priorities, validating outputs, and approving changes before integration. This parallel, agent-assisted model allowed the team to compress timelines significantly without compromising medical accuracy, security, or platform compliance.

By aligning delivery to ChatGPT’s agentic and tool-calling architecture from the start, the team was able to iterate quickly, minimize rework, and ship a production-ready experience within an aggressive launch window.

Together with the client’s engineering team, we used an agent-assisted delivery model to build a GLP-1–aware recipe discovery experience natively inside ChatGPT—designed to respond intelligently to natural-language questions while driving measurable business outcomes.

When users ask questions like “What should I eat when I’m taking Ozempic?”, ChatGPT surfaces the client’s app and invokes a server-side tool that searches a curated set of GLP-1-friendly recipes. 

Results are returned in an inline carousel:

This approach balanced user value with business impact—meeting users where they are, while creating a clear path to deeper engagement.

Implementation included: