OpenAI Tangents
OpenAI Tangents
ROLE
Product Designer
TIMELINE
January 20 - February 27
TEAM
Solo!
SKILLS
Product Design & Motion Design
UX/UI Design
ROLE
Product Designer
TIMELINE
January 20 - February 27
TEAM
Solo!
SKILLS
Product Design & Motion Design
UX/UI Design
ROLE
Product Designer
TIMELINE
January 20 - February 27
TEAM
Solo!
SKILLS
Product Design & Motion Design
UX/UI Design
OVERVIEW
When does AI stop being a tool and start shaping how we think?
As AI becomes integrated into daily thinking, there’s a risk it becomes a hindrance rather than a catalyst. OpenAI Tangents reimagines ChatGPT as a cognitive mirror helping users explore their thinking patterns, not just complete tasks faster.
When does AI stop being a tool and start shaping how we think?
As AI becomes integrated into daily thinking, there’s a risk it becomes a hindrance rather than a catalyst. OpenAI Tangents reimagines ChatGPT as a cognitive mirror helping users explore their thinking patterns, not just complete tasks faster.
When does AI stop being a tool and start shaping how we think?
As AI becomes integrated into daily thinking, there’s a risk it becomes a hindrance rather than a catalyst. OpenAI Tangents reimagines ChatGPT as a cognitive mirror helping users explore their thinking patterns, not just complete tasks faster.
PROBLEM
ChatGPT makes it easy to offload thinking, but hard to understand it.
By forcing complex, non-linear reasoning into linear chat threads, users lose visibility into how ideas connect, evolve, and repeat, turning thinking into disposable output rather than cumulative understanding.
ChatGPT makes it easy to offload thinking, but hard to understand it.
By forcing complex, non-linear reasoning into linear chat threads, users lose visibility into how ideas connect, evolve, and repeat, turning thinking into disposable output rather than cumulative understanding.
ChatGPT makes it easy to offload thinking, but hard to understand it.
By forcing complex, non-linear reasoning into linear chat threads, users lose visibility into how ideas connect, evolve, and repeat, turning thinking into disposable output rather than cumulative understanding.
MOMENT
Reflection as the missing layer in conversational AI.
ChatGPT already captures rich signals about how users think. Your Year with ChatGPT is a personal year-in-review that reflects how you used ChatGPT over the past year. But these insights arrived once a year, despite ChatGPT capturing signals of curiosity, reasoning, and interest every day.
Reflection as the missing layer in conversational AI.
ChatGPT already captures rich signals about how users think. Your Year with ChatGPT is a personal year-in-review that reflects how you used ChatGPT over the past year. But these insights arrived once a year, despite ChatGPT capturing signals of curiosity, reasoning, and interest every day.
Reflection as the missing layer in conversational AI.
ChatGPT already captures rich signals about how users think. Your Year with ChatGPT is a personal year-in-review that reflects how you used ChatGPT over the past year. But these insights arrived once a year, despite ChatGPT capturing signals of curiosity, reasoning, and interest every day.
The spark is realizing that the value isn’t just in storing this data, it’s in surfacing it continuously, helping users visualize their thinking, explore tangents, and discover connections in real time.
Patterns create meaning
Reflection transforms history into insight.
Reflection should be continuous
Annual summaries delay awareness that could happen instantly.
Thinking amplification
AI becomes a partner in sensemaking, not just output.
Patterns create meaning
Reflection transforms history into insight.
Reflection should be continuous
Annual summaries delay awareness that could happen instantly.
Thinking amplification
AI becomes a partner in sensemaking, not just output.
SOLUTION
Design AI systems that make human thinking visible, explorable, and cumulative
FLOWS
Making Thinking Visible
Tangent Branching
Fork any conversation to explore related ideas without losing your place.
Connection Mapping
Visualize how your conversations relate through an interactive grid view.
Intelligent Suggestions
ChatGPT actively surfaces relevant past conversations and suggests meaningful connections.
Thinking Patterns Dashboard
Periodic insights that reveal how your thinking evolves over time.
RESEARCH
The Hidden Cost of Helpful AI
To understand how conversational AI shapes thinking, I studied real-world ChatGPT usage over time and reviewed existing online research on AI-supported cognition, looking at how users explored ideas, followed tangents, and revisited similar questions.
The Hidden Cost of Helpful AI
To understand how conversational AI shapes thinking, I studied real-world ChatGPT usage over time and reviewed existing online research on AI-supported cognition, looking at how users explored ideas, followed tangents, and revisited similar questions.
The Hidden Cost of Helpful AI
To understand how conversational AI shapes thinking, I studied real-world ChatGPT usage over time and reviewed existing online research on AI-supported cognition, looking at how users explored ideas, followed tangents, and revisited similar questions.
Across these interactions, three patterns emerged, along with a key insight.
Thinking is non-linear, chat is not
Users explored ideas through associations and tangents, but the interface forced linear progression.
AI encourages cognitive offloading
Fast answers reduce reflection and sensemaking.
Patterns exist, but remain invisible
Users repeatedly explore similar topics without awareness.
Thinking is non-linear, chat is not
Users explored ideas through associations and tangents, but the interface forced linear progression.
AI encourages cognitive offloading
Fast answers reduce reflection and sensemaking.
Patterns exist, but remain invisible
Users repeatedly explore similar topics without awareness.
KEY INSIGHT
Reflection increases engagement: When shown their own usage patterns, users became more self-aware.
AI needs to externalize thinking, not just accelerate it, by making ideas visible, connected, and reflective, so users stay actively engaged in their own reasoning. This shift from linear chat to dynamic, pattern-revealing interfaces can turn passive offloading into active cognition, fostering deeper self-awareness and exploration.
INTERGRATION
Learning from Node-Based Canvases and Patch Flows
My thinking drew from the node-based canvas of Obsidian Canvas and the structured, directional flows of the Origami Studio 3 patch editor. I focused on enabling visual freedom while still maintaining a clear beginning and end to a thought.
Learning from Node-Based Canvases and Patch Flows
My thinking drew from the node-based canvas of Obsidian Canvas and the structured, directional flows of the Origami Studio 3 patch editor. I focused on enabling visual freedom while still maintaining a clear beginning and end to a thought.
Learning from Node-Based Canvases and Patch Flows
My thinking drew from the node-based canvas of Obsidian Canvas and the structured, directional flows of the Origami Studio 3 patch editor. I focused on enabling visual freedom while still maintaining a clear beginning and end to a thought.
To carry this thinking forward, I mapped the core interactions as flows, capturing how users can explore ideas freely while still moving through a defined start and progression.
DESIGN DECISIONS
Branching Conversations
Branching is initiated directly from a message rather than a separate tool, keeping the interaction lightweight and integrated into the natural flow of chat. This reduces friction and prevents users from feeling overwhelmed by the need to manage structure.
Branching Conversations
Branching is initiated directly from a message rather than a separate tool, keeping the interaction lightweight and integrated into the natural flow of chat. This reduces friction and prevents users from feeling overwhelmed by the need to manage structure.
Branching Conversations
Branching is initiated directly from a message rather than a separate tool, keeping the interaction lightweight and integrated into the natural flow of chat. This reduces friction and prevents users from feeling overwhelmed by the need to manage structure.
Each branch preserves the original context and provides clear navigation between related paths, allowing users to explore ideas at multiple depths without losing their place.
Intelligent Suggestions
Suggestions are intentionally limited and high-confidence, designed to surface meaningful connections, reflection, and idea expansion rather than simply prompting the next response. They appear as natural pauses within the conversation and are framed as optional prompts, not directives, so users remain in control of their thinking flow
Intelligent Suggestions
Suggestions are intentionally limited and high-confidence, designed to surface meaningful connections, reflection, and idea expansion rather than simply prompting the next response. They appear as natural pauses within the conversation and are framed as optional prompts, not directives, so users remain in control of their thinking flow
Intelligent Suggestions
Suggestions are intentionally limited and high-confidence, designed to surface meaningful connections, reflection, and idea expansion rather than simply prompting the next response. They appear as natural pauses within the conversation and are framed as optional prompts, not directives, so users remain in control of their thinking flow
Reflection Layer
The Thinking Patterns Dashboard brings everything together in a dedicated space within the sidebar, giving users quick access to their cognitive activity over time. It is designed to support both short-term reflection on recent conversations and long-term awareness of evolving interests, habits, and connections in their thinking.
Reflection Layer
The Thinking Patterns Dashboard brings everything together in a dedicated space within the sidebar, giving users quick access to their cognitive activity over time. It is designed to support both short-term reflection on recent conversations and long-term awareness of evolving interests, habits, and connections in their thinking.
Reflection Layer
The Thinking Patterns Dashboard brings everything together in a dedicated space within the sidebar, giving users quick access to their cognitive activity over time. It is designed to support both short-term reflection on recent conversations and long-term awareness of evolving interests, habits, and connections in their thinking.
Connection Mapping
A node-based map view was chosen over a traditional list to better support visual thinking and pattern recognition. Instead of navigating users away from the map, nodes expand inline to reveal more detail. This keeps users oriented within their thinking space, allowing them to explore connections without losing context or disrupting their flow.
Connection Mapping
A node-based map view was chosen over a traditional list to better support visual thinking and pattern recognition. Instead of navigating users away from the map, nodes expand inline to reveal more detail. This keeps users oriented within their thinking space, allowing them to explore connections without losing context or disrupting their flow.
Connection Mapping
A node-based map view was chosen over a traditional list to better support visual thinking and pattern recognition. Instead of navigating users away from the map, nodes expand inline to reveal more detail. This keeps users oriented within their thinking space, allowing them to explore connections without losing context or disrupting their flow.
Dotted links between nodes are generated by the system to reduce user effort and surface relationships that may otherwise go unnoticed. By making these hidden patterns visible, the interface supports reflection and helps users recognize how their ideas connect over time.
REFLECTION
What I learned
Designing for thinking, not just tasks
This project pushed me to move beyond designing for task completion and instead consider how interfaces shape curiosity, reflection, and sensemaking. It reframed my definition of success in AI, from faster answers to more intentional thinking.
Making the invisible visible
Working with thinking patterns meant designing for something users can’t normally see. I learned to translate behaviors like revisiting ideas, following tangents, and forming connections into visuals that feel clear, lightweight, and immediately understandable.
Designing for thinking, not just tasks
This project pushed me to move beyond designing for task completion and instead consider how interfaces shape curiosity, reflection, and sensemaking. It reframed my definition of success in AI, from faster answers to more intentional thinking.
Making the invisible visible
Working with thinking patterns meant designing for something users can’t normally see. I learned to translate behaviors like revisiting ideas, following tangents, and forming connections into visuals that feel clear, lightweight, and immediately understandable.
Balancing structure and freedom
Users need the freedom to explore ideas, but also a sense of orientation. Designing that balance, between open exploration and clear progression, became central to every feature decision.
Designing with the system, not just for the user
This work reinforced that AI experiences are co-created. The system has a role in surfacing patterns, suggesting connections, and prompting reflection. I learned to design these system behaviors to feel supportive, timely, and never intrusive.
Balancing structure and freedom
Users need the freedom to explore ideas, but also a sense of orientation. Designing that balance, between open exploration and clear progression, became central to every feature decision.
Designing with the system, not just for the user
This work reinforced that AI experiences are co-created. The system has a role in surfacing patterns, suggesting connections, and prompting reflection. I learned to design these system behaviors to feel supportive, timely, and never intrusive.