惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

D
Docker
Simon Willison's Weblog
Simon Willison's Weblog
H
Help Net Security
F
Fortinet All Blogs
H
Heimdal Security Blog
S
Schneier on Security
L
LangChain Blog
博客园 - Franky
酷 壳 – CoolShell
酷 壳 – CoolShell
NISL@THU
NISL@THU
P
Palo Alto Networks Blog
J
Java Code Geeks
博客园 - 【当耐特】
The Last Watchdog
The Last Watchdog
W
WeLiveSecurity
www.infosecurity-magazine.com
www.infosecurity-magazine.com
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
V
Vulnerabilities – Threatpost
I
InfoQ
Recorded Future
Recorded Future
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
C
CERT Recently Published Vulnerability Notes
T
Tenable Blog
腾讯CDC
C
Check Point Blog
量子位
M
MIT News - Artificial intelligence
GbyAI
GbyAI
罗磊的独立博客
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
B
Blog
小众软件
小众软件
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
C
CXSECURITY Database RSS Feed - CXSecurity.com
Stack Overflow Blog
Stack Overflow Blog
P
Proofpoint News Feed
P
Privacy & Cybersecurity Law Blog
V2EX - 技术
V2EX - 技术
T
Threatpost
Engineering at Meta
Engineering at Meta
Attack and Defense Labs
Attack and Defense Labs
T
Tailwind CSS Blog
S
Securelist
The Cloudflare Blog
博客园 - 叶小钗
L
LINUX DO - 最新话题
T
Troy Hunt's Blog
C
Cyber Attacks, Cyber Crime and Cyber Security
爱范儿
爱范儿

UX Collective - Medium

Designing the Human+AI system AI UX debt: A new bottleneck The case for catholic philosophy in ethical interface design What critical thinking means for senior designers (and how to apply it) Most AI tools make users faster. The best AI tools make users better. From faster pencil to AI Experience Architect: a designer’s path The waiting problem in AI products Be like water, The death of the empty state, AI for UX The big M&M’s color investigation you could’ve totally lived without How mobile apps are reshaping screening for cognitive decline Two gears, one compass: designing at velocity while sustaining quality Should we be kind to machines (for our own sake, really)? How to write a DESIGN.md file Claude can actually use Opening your place to the street The undo problem in AI products The one-dimensional pipe between two high-dimensional minds AI made everyone a creator, not a designer Can a typeface be safe? What do you do if your best design work is a small project? Low cortisol solution to big problems The death of the empty state in AI products Be like water: Rethinking the design process with AI How I use AI to partner on design problems Rethinking design with your hands in the AI world The thinking was never just mine Prompt is not interface, UI patterns that won’t survive, how to make Claude follow your design… Discovery is the work AI gives back The left-handed rope Everything I know about AI, I learned from a genie How to make Claude Code follow your design system in Figma The prompt is not an interface Designing data-intensive applications — advice for interaction designers Users own the present. You own the future. The first taste of Joy We built this. Now we own it. Why you need to protect your work more than ever The psychological fine print of AI The trick to designing agentic AI is learning how to think like a manager St. Augustine and AI’s false promise Pinning is not saving. Saving is not favoriting. Favoriting is not flagging. You skipped the first question. Now you’re adding AI. When AI decides and human signs off Collected consciousness, exhausting moment, UX Research with AI Don’t simply bolt on AI. Rethink from the ground up. The basketball playbook for AI builder teams Can AI make your dating life better? Usability, accessibility, and the human-AI paradigm Thoughtful AI Implementation for UXR Leaders A GenAI perplexed by color theory 10 UI patterns that won’t survive the AI shift What is AI really costing the planet? The most dangerous pronoun in design Staff designers aren’t about shipping the best work. That’s the point. The forgotten conversation problem in AI chat A fantastic voyage, the illusion of good taste, the art of subtraction The right touch: mapping AI presence to user intent The rulebook for designing AI experiences How AI may reshape elderly care What improv taught me about why innovation falls out of sync Working in the open How design leaders influence decisions without being in the room How to mitigate the risk of AI implementation in enterprise environments CSS you didn’t know you could style Product design in 2026: the beginning of a fantastic voyage? The chat box isn’t a UI paradigm. It’s what shipped. The web trained AI to deceive. Now designers have to untrain it. The art of subtraction in a world of infinite features What we behold, the trust-latency gap, designing haptics AI is ruining the way you talk about your work The deceptive nature of today’s AI conversation design and how to fix it Rethinking the shape of design teams in an AI world Becoming an AI-native designer The misrepresentation of “good taste” as a core design skill Test smart: how to approach AI and stay sane? Are we makers by nature — or consumers by design? Your AI agent can read your codebase. It doesn’t know your product. Folder instructions — Instructions for system-level AI Haptics: how to build a consistent cross-platform solution and align code with Figma I watched the manosphere documentary; here is how design is making things worse. Autopilot, agentic AI, and the dangers of imperfect metaphors Oh, but there’s one more thing We become what we behold AI, UX, and the factory model The trust gap in healthcare AI isn’t about the AI How to turn your competitor’s worst reviews into your strongest design argument The erosion of design authority, burnout problems, invisible customers Most products don’t need tone of voice — they need a point Designing adaptive teams The trust-latency gap: why the future of UX is intentionally slower Rethinking design critique Notes from the people building your future taste.md Social media on trial The old design workshop is dead. Long live design workshops. Careful, liable UX is a thing now Beyond the user: why design needs to widen its circle Designing for the invisible customer The UX ground is shaking, synthetic users, building perspective Data models: the shared language your AI and team are both missing We didn’t mean to build this- engagement at any cost
Designing with AI without losing your mind
Heenesh Pate · 2026-04-24 · via UX Collective - Medium
With critical thinking skills on the line I built a real-time AI collaborator, Thia — with vision and voice capabilities to keep early ideas raw, the loop tight, and the thinking mine. Sketching on a whiteboard with an AI collaborator — image generated by AI You don’t typically notice changes in your own behaviour until they become more pronounced. I recently found myself reaching all too quickly for LLMs to prompt on design problems I would have previously spent time digesting and sketching out solutions, now I was summoning up high-fidelity designs in seconds. Was I unintentionally outsourcing my thinking? So I built an app to not just reclaim my critical thinking, but strengthen it. Critical thinking is being outsourced The sheer flood of recent AI tools to design and build products has shown we’re spending less and less time doing the actual thinking as designers. Clients and stakeholders want processes to run faster, faster doesn’t always mean better solutions — sometimes you don’t need to test a half-baked solution with users because it should never have got past early scrutiny. Testing and learning has become misconstrued into an organisational experimental edict of throwing spaghetti against a wall and seeing what sticks, because making spaghetti has suddenly become cheap. Digital spaghetti thrown against a wall — image generated by AI “Testing and learning has become misconstrued — into throwing spaghetti against a wall to see what sticks, because making spaghetti has suddenly become cheap.” Furthermore people are losing critical thinking skills as they outsource more and more of their thinking to AI. Ironically these are the skills that will be sought after once the dust has settled in the wake of AI’s current charge; being able to make informed decisions, ask difficult questions and to evaluate beyond prompt construction. I too have found myself turning to AI for menial tasks and I began to become more concerned about my reliance upon it. AI is making light work of building, but there are some spaces in the design process where I believe deep thinking is sacred, where I didn’t want AI to encroach upon. Keeping ideation sketching human For me that key stage in the design process is whiteboarding and sketching, rapidly ideating solutions and refining them. I find I’m most effective when I have individuals to bounce ideas around with, that can critically question and help shape those seedling ideas into something more fully formed. Working remotely and on solo-projects means collaborators aren’t always at hand to be sounding boards or have the deep context you need to build upon each other’s ideas and most importantly scrutinize and evaluate their merit. So why not have AI work for me to support this deep thought space, not eviscerate it. A solution began to take form, an AI collaborator that would engage in socratic dialogue whilst sketching ideas like a great colleague. My collaborator, my terms This collaborator app had to address a very specific user-base of just one, me. It was imperative that it work on my terms and it supported my design process, by which I meant it had to see what I was sketching, have context to understand and discuss it with me in real-time. I wanted my ideas to flow freely, like they might in a workshop or meeting with a colleague, so uploading a sketch to an LLM then chatting to it and asking for ideas was not going to cut it. That’s too slow a feedback loop and akin to a waterfall process, with a staccato rhythm that kills any chance of achieving a flow state. Creative thinking and ideas are messy and fluid, I believe in getting them out, organising later. But I also wanted scrutiny, I didn’t want feedback that amounted to ‘yes’ all the time or ‘great idea’. I wanted to weed out the weak ideas and build on stronger ones — to bring in different perspectives, to push and challenge them, until I had kernels worthy of further development. Some might say use Google Stitch, it can fire up a bunch of design ideas through a simple prompt, and verbally address it using natural language; or Google’s AI Playground with real-time capabilities where you can set-up a webcam and do exactly what you’re asking or even the Gemini app. These all fell short, Gemini and Playground weren’t tuned to be critical — which is what I wanted from a collaborator, so they didn’t fit the bill. Stitch is impressive — but goes immediately to high-fidelity, great for later ideation, but isn’t what I was after. “I didn’t want feedback that amounted to ‘yes’ all the time. I wanted to weed out the weak ideas and build on the stronger ones.” Breathing life into Thia So it had to feel like my AI collaborator was there working on the design concepts with me, being critical and not just spewing out countless ideas. I landed on using Google AI Studio to build my App, a contained development environment with access to the frontier real-time models I needed. I also wanted to use this opportunity to delve deeper into building AI tools beyond a POC or vaporware for user testing, to something that I could genuinely use. I had a working prototype with one prompt, which did pretty much the bare bones of what I wanted. It worked, it wasn’t pretty by any means, but it wasn’t that usable. Through countless prompt refinements about a day later I had brought to life my AI collaborator, Thia. Sketching with Thia to design new features I now began to use this early incarnation of Thia, to design Thia. I simply pointed the webcam at my whiteboard, began sketching the ideas I wanted to explore and engaged in Socratic dialogue with Thia. Ultimately, I sketched out concepts for more of the elaborate features, such as note summaries and camera controls. I found that at this stage, I began to reach for adjacent AI tools for specific needs, Figma and Stitch to explore design systems and motion animation to add more polish and refinement, before folding it back into AI Studio. The process was liberating, addictive, and very easy to be sucked into rabbit holes. It’s easy to see why designers feel that the design process is drastically changing, but it’s here that discipline is needed most, to keep re-evaluating your designs against your problem statement. After three days of heavy prompting, hitting my token spending caps (twice) I released the Thia app onto Github for all to play with and build upon. I highly recommend giving it a go; it’s by no means perfect but it works across mobile and desktop devices and I have found it’s been useful in the early stages of other projects I’m working on, too. If you want to try out Thia yourself, there are some links at the end of the article. When speed becomes the enemy of thinking I could not have built anything close to this app in three days without AI, the capabilities we have at hand are truly immense. I got to play and design features like animating Thia’s breathing cadence — something I would have written off as nice to have in the past. I can see this replacing UI pixel pushing in prototypes and this finesse all too easily acting as a facade papering over fractured concepts and weak value propositions. Adding life to Thia through simple motion With so much noise in AI tooling and collective hype driving everyone to ship faster — the rigour of the design process is being glossed over in favour of building quickly. But what happens if you don’t invest the time in proving the concept early on and just build the wrong thing, your competitors will just leap frog you with a superior product, regardless if you’re first to market. Those developing enterprise software will know that it’s all too easy to fall into the feature factory trap, shipping features every quarter onto a product that feels increasingly held together with sticky tape. Then you land in the world of balancing the deluge of experimental archaic features that some customers love, but comes with the cost of fragmenting your overall experience and inhibiting you from growing at pace. A real reason why it’s so important to make sure we build the right thing. For this app I wanted to embrace new approaches and treated it as a learning experience, but beyond prototyping, these tools simply augment the design process, not upend it. If there is one thing I learned from experimenting is that they are all still in their infancy, good for ideation and going wide or exploring ideas deeper, everyone is still figuring out how to use them as part of their process. Critical thinking requires some friction If you take a step back, the real game changer with AI in product development is the speed at which we can execute at each stage. It doesn’t mean we stop researching with users to inform our solutions or cut out time to create and refine robust ideas, it just means we can accelerate the design process — not skip out on parts of it. “The only way to retain critical thinking skills is to use them, by keeping them sharp — that means embracing cognitive friction and not simply rushing to the finish line.” The tools will become easier to use, but to build robust systems we will need designers who understand how to ensure products and value propositions are robust and support a healthy business model. It’s here we need critical thinking skills where we can analyse, evaluate and cross-pollinate ideas across domains in order to create something greater than the sum of its parts. The cost of losing those skills is too high a price to pay. For me it was about keeping that sketching and ideation time sacred, the act of realising an idea through physically sketching and writing is a primeval one, it literally builds memories compared to typing , it activates parts of the brain to forge new connections deeper into long-term memory and helps us internally evaluate and think. I do not want to lose these very human skills. I built an AI collaborator not so I could build faster, but so I could spend more time critically thinking and making sure I nurtured the most robust ideas. Explore further Thia Critical Collaborator partner, on AI Studio — Give it a go and try it yourself on Google AI Studio. Use an API key if you don’t want it to train on your data. Thia Critical Collaborator on GitHub — Explore the source code, fork and remix. Google AI Studio Tutorial by Bex Tuychiev on Data Camp , Great article on understanding and using the suite (Dec 2025) To be human is to live with friction. That’s something AI boosters will never understand by Alexander Hurst on the Guardian (Apr 2026) The last interface by Heenesh Patel, I wrote about the impact of multi-modal AI agents on SAAS products (Mar 2026) Thia’s roadmap I’m evolving the feature set as Thia becomes a key part of my design process, a flavour of things to come: ​​Overwriting on screenshots to amend or illustrate new ideas Increasing the number of modalities with simultaneous multiple participants Calling upon multiple models for more complex tasks Orchestrating multiple agents on OpenClaw’s platform Acting as a sketching tutor Feel free to reach out on LinkedIn if you want to connect and collaborate on Thia. Designing with AI without losing your mind was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.