As AI agents gain real-world capabilities, companies are prioritizing security controls while building infrastructure for autonomous workflows.
The AI industry is maturing from rapid feature development to responsible deployment, with security, transparency, and user control becoming competitive advantages rather than afterthoughts.
This Week in AI Products
 ChatGPT |
Feb 13 |
OpenAI adds Lockdown Mode and Elevated Risk labels
OpenAI introduced two new security features for ChatGPT: Lockdown Mode to prevent prompt injection attacks and Elevated Risk labels to warn about potential AI-driven data exfiltration. These tools help organizations protect sensitive data when using AI assistants. Source →
Designer's Takeaway: Design security indicators that inform without creating alarm fatigue. Use progressive disclosure to show risk levels contextually, and make security features discoverable without disrupting core workflows.
Pattern: Responsible AI Design
 Perplexity |
Feb 10 |
Model Council feature compares responses across multiple AI models
Perplexity launched Model Council, a new feature that lets users compare answers from three different AI models side-by-side. This addresses the growing challenge of understanding which AI gives better responses for different types of queries while improving trust and transparency. Source →
Designer's Takeaway: Use comparison interfaces to reduce AI uncertainty. Design side-by-side layouts that highlight meaningful differences without overwhelming users, and consider when multiple perspectives add value versus when they create decision paralysis.
Pattern: Confidence Visualization
| ChatGPT |
Feb 9 |
Testing ads in ChatGPT with user controls and privacy focus
OpenAI announced they're testing ads in ChatGPT to support free access. The ads will be clearly labeled, won't influence answer quality, and include strong privacy protections with user control options. This marks a significant shift in how AI chat interfaces might monetize. Source →
Designer's Takeaway: When integrating sponsored content into AI interfaces, prioritize transparency and user agency. Design clear visual distinctions between AI responses and ads, and give users meaningful control over their advertising experience.
Pattern: Responsible AI Design
 OpenAI GPT-5.3-Codex-Spark |
Feb 12 |
OpenAI launches first real-time coding model with 15x faster generation
GPT-5.3-Codex-Spark is OpenAI's first real-time coding model, offering 15x faster code generation with 128k context window. It's currently in research preview for ChatGPT Pro users, signaling a shift toward specialized AI models for specific tasks. Source →
Designer's Takeaway: Design for real-time AI assistance by considering how instant feedback changes user behavior. Build interfaces that can handle continuous updates without overwhelming users, and provide clear indicators of AI processing states.
Pattern: Augmented Creation
 Vercel |
Feb 10 |
Agents can now access runtime logs through MCP server integration
Vercel's new MCP (Model Context Protocol) server allows AI agents to directly access runtime logs for debugging and monitoring. Agents can retrieve logs for specific projects or deployments, inspect function output, and investigate runtime issues without human intervention. Source →
Designer's Takeaway: Design APIs and interfaces that serve both human users and AI agents effectively. Consider how autonomous systems will interact with your product and build appropriate access controls and monitoring capabilities.
Pattern: Human-in-the-Loop
 Uber Eats |
Feb 11 |
Cart Assistant uses AI to build grocery lists from text or images
Uber Eats launched Cart Assistant that automatically adds items to your cart based on text prompts or image uploads. The feature streamlines grocery shopping by interpreting user intent and translating it into actionable cart items. Source →
Designer's Takeaway: Use multimodal inputs to reduce friction in complex selection tasks. Design interfaces that accept both text and images when users might struggle to articulate their needs, especially in product discovery scenarios.
Pattern: Multimodal Interaction
 Figma |
Feb 10 |
New research shows increased demand for designers in the AI era
Figma released a study revealing that AI is driving increased design hiring rather than replacing designers. Companies need more designers to navigate AI integration and create human-centered experiences, with hiring managers prioritizing skills that complement AI capabilities. Source →
Designer's Takeaway: Position yourself as the bridge between AI capabilities and human-centered design outcomes. Focus on developing skills in AI collaboration, ethical design decisions, and translating AI possibilities into meaningful user experiences.
Pattern: Augmented Creation
Steal This Week
Perplexity's Model Council comparison interface
Perplexity's side-by-side model comparison reduces user uncertainty about AI quality and builds trust through transparency. This pattern could work for any product where AI outputs vary in quality or approach, from design tools showing different creative directions to analytics platforms presenting multiple data interpretations.
Pattern to Know
Responsible AI Design
Multiple companies launched security and transparency features this week, from OpenAI's security controls to ChatGPT's ad labeling approach. As AI gains real-world capabilities, users and organizations need clear indicators of risk, data usage, and system behavior.
When to use it: Apply this pattern whenever your AI system handles sensitive data, makes autonomous decisions, or could impact users in meaningful ways. Essential for enterprise AI tools and consumer products with privacy implications.
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