Google Deepmind: Generative & Adaptive AI

Legacy generative AI systems frequently overwhelmed users with heavy, unstructured blocks of text. Our objective for this effort was to intercept specialized (and I can’t tell you what the specialized bit was due to NDA) consumer prompts and dynamically inject structured UI components, transforming raw, unpredictable model outputs into highly navigable, interactive experience layers.

Role: UX Lead, Gemini Team
Context: Confidential MVP Launch

Behavioral Architecture & The Prompt Pivot

Working alongside the prompt engineer, I worked to shape the model's System Instructions (SI) to accurately detect user intent. This allowed us to introduce a critical branching logic that split the user journey into two distinct paths based on situational context:

  • The Low-Latency Path: Delivers an instant, structured output blueprint immediately upon intent detection, serving users who require immediate information with minimal friction.

  • The High-Context Path: Triggers an agent-driven discovery session, utilizing progressive disclosure to gather user parameters and situational constraints before generating the customized UI framework.

  • Systemic Safety Guardrails: Worked with the prompt engineer to apply specific constraints on the response criteria in order to manage system trust and mitigation risk. This included structuring explicit boundaries around medical authority (e.g., establishing a "not a doctor" posture) and adjusting the model's behavioral tone to suppress sycophancy, ensuring the system remained objective and safe rather than overly validating unsafe or unverified user assumptions.

Platform Systems & The Universal Container

To protect users from information overload, I defined the layout logic for a responsive, modular container system that broke complex, model-generated text into digestible, interactive units. This spatial layout allowed users to navigate fluid variations with minimal cognitive effort.

In the spirit of engineering efficiency, this framework was built around a single, flexible UI container. Rather than allowing cross-functional teams to deploy bespoke elements for different workstreams, I designed a universal component capable of dynamically adapting across distinct layout states:

  • Asynchronous Informational Hierarchies: Designed the internal container structure to gracefully accommodate highly variable lengths of model-generated content, shifting fluidly from compact headline alerts to deep, multi-tiered instructional steps and conversational macro-data points without breaking the visual grid or requiring manual designer intervention.

  • Dynamic Component Injection: Built the card container to dynamically swap its internal layout assets, shifting between image-heavy editorial layouts and structured data lists based on the specific variables returned by the model.

This universal card component was adopted across internal model teams as a standard, saving significant development hours by requiring only one core component build to handle an infinite array of response variations.

Cross-Functional Governance & Delivery

Operating at this scale required balancing rapid iteration with rigorous platform compliance. I led the UX strategy across three critical pillars:

  • Legal & Safety Alignment: Collaborated with compliance teams to ensure necessary disclaimers and safety boundaries were surfaced contextually without fracturing the core user experience.

  • Engineering Precision: Authored comprehensive system behavior documentation and partnered directly with front-end engineering to execute pre-launch design QA, establishing clear interaction rules to safeguard the integrity of the design system and reduce design-to-code drift.

  • Executive Visibility: Developed interactive prototypes and presentation frameworks utilized for high-stakes executive buy-in sessions, including leadership reviews with Sundar Pichai.

The Impact

In the end, I delivered a successful high-context MVP that defined how Gemini structures agent-driven content, establishing the foundational patterns and layout logic for the platform's next-generation adaptive interfaces.