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Stable Discussion Podcast

What's possible with AI today and what to expect tomorrow
Stable Discussion Podcast
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  • Designers Building the AI Prototype
    Over the last week, I’ve been captivated by the idea that Designers are best positioned to leverage AI on development teams. AI is changing how products are built, but there's a blind spot: designers are still standing on the sidelines, even as the tools finally let them take center stage. Most teams treat AI as the domain of engineers and data scientists, and for designers, this technical barrier makes AI seem unapproachable and out of reach.On the other end of the spectrum, there’s a subculture of “vibe coding” and hustle culture. Small teams or solo builders are cranking out rough AI prototypes, often without rigorous product development practices.But even as these experiments multiply, they rarely result in thoughtful, user-centered products—often sacrificing quality and vision for speed. This highlights a gap: while engineers and hackers can rapidly iterate on technical possibilities, what's too often missing in the process is the guiding hand of design.I’ve noted that the teams closest to the customer are best positioned to deliver real value. Designers, more than anyone, bridge the gap between WHAT a customer wants and HOW the business delivers it. This makes designers uniquely well-placed to drive and shape how AI is applied to solve practical, customer-centric problems.What’s new, and what too few teams have noticed: the AI toolchain has finally become accessible enough that designers themselves can prototype, test, and iterate—without waiting for engineering or hunting down a Python wizard.Design-Driven Product DevelopmentOver the years, I’ve formed a straightforward operating model for developing great products on engineering teams:On most teams, "Make it Work" means building quick, rough prototypes—getting something functional before worrying about polish or coherence. That may sound efficient, but by relegating design and user experience to the end of the process, these products often inherit all the awkwardness, missed opportunities, and makeshift decisions of their early versions. Design becomes an exercise in damage control and technical compromise—not in envisioning or elevating what’s possible.Teams can attempt to avoid this list order by doing big planning cycles, documenting ahead of time, or other attempts to "shortcut" the process. However, when they run into problems, these approaches often revert to doing things in this order. This is just the tried and true way of getting things done.Why not flip this script? What if, from the very beginning, designers were the ones to shape the prototype—not as a surface afterthought, but as the driving force for both how the product functions and feels? If prototyping is the process where key decisions are made, designers should be there, guiding what’s built, not just decorating it after the fact.Now, as AI makes prototyping more accessible and immediate, designers can move from concept to interactive demo without the traditional bottlenecks. This shift helps ensure that design considerations aren’t an afterthought, but baked in from the earliest steps.Some of the most innovative solutions come from design-led exploration—where a designer, by understanding both the user and the technology’s constraints, proposes an approach no one else saw. By leading with design, teams can reduce costly rework, discover what users really want earlier, and prevent soulless or awkward interfaces from ever making it out into the world.Representing Business and TechnologyDesigners bridge the gap between development and business teams. They translate technical constraints into user-centric solutions that meet business objectives. They also transform high-level business requirements into wireframes, prototypes, and visual designs for developers to build out.Negotiation is essential, not just to the design role, but across the triad of product, design, and engineering. Each group brings its own perspective, priorities, and blind spots: designers may champion user needs but sometimes underestimate technical effort; developers possess crucial implementation insight but can occasionally lose sight of broader business or user aims; even product or business leaders may bring great vision but stumble on feasibility. The healthiest teams recognize these dynamics and lean into the creative tension, surfacing their assumptions and sharing context early and often.When these disciplines disconnect, you often see familiar breakdowns: designers shut out of early technical decisions; product obsessing over features without clarity on what’s possible; and developers, at their worst, retreating into reactive “IT mode,” simply processing tickets and change requests rather than partnering in the product vision. Nearly everyone working in tech will have seen these patterns and felt the frustration they create.The opportunity, then, isn’t for designers to take over prototyping alone, but to pull the process closer to multidisciplinary influence—helping organizations build better products faster by dissolving long-standing silos.AI PrototypingAI prototyping is better than ever before. With a competitive landscape of new tools, there are many great solutions that improve over time. And with so many people looking at leveraging these tools, a variety of new techniques are being explored that continue to push what they are capable of.While coders will likely leverage IDEs (Integrated Development Environments) like Cursor or Windsurf, web-based solutions that don’t require a complex development setup tend to be easier to use. These web-based tools additionally offer the ability for teams to remix solutions with others and share prototypes across a team.These days, I prefer v0 because of their direct connection to the Next.js technology and their integrated Vercel deployments which are familiar to me. Finding a tool that matches your experience offers a significant advantage. Additionally, the design aesthetics of v0’s solution seem to be pretty good for my needs.Other tools like bolt.new and lovable.dev offer a similar suite of tools but focus differently to best match the needs of their customers. As this space continues to show huge revenue growth and remains novel to market to users, additional solutions continue to be released.Designers Building with AI PrototypingI was able to run a workshop on AI for the design team at Compass Digital. This workshop provided AI fundamentals for building personalized AI design workflows but also provided guidance on prototyping using vibe coding techniques. By the conclusion of the session, the team felt familiar with the concepts and were putting together some really interesting designs that immediately pushed at the limits of what’s possible with these prototyping tools.Designers often need to guide coders and product managers to understand what’s possible. Because coders are more focused on the code, a user experience that aims at a specific visual style often gets lost on them. Product managers are excited about what they know but are usually a bit more concrete-minded and need to be shown what’s possible. Once they get it they’re usually fully behind an idea.At my first startup, I saw firsthand how designers can expand what teams believe is possible. We were stuck on a UI detail—a post-it note display the developer thought couldn’t be built with CSS. I took a stab at it and sent over a solution. When my cofounder saw it working, he realized more was possible than he’d assumed. That moment not only solved our immediate problem but also deepened our collaborative approach to product development.Designers frequently bridge gaps between vague ideas and concrete solutions. With AI prototyping tools, they're even better equipped to overcome blockers and build stronger, more collaborative relationships with other teams.The New World of Design-Led ImplementationWe’re now establishing a new operating model:* Design to make it work* Develop to make it right* Collaborate further to make it goodWith new AI code generation tools, designers are better positioned than ever to build incredible things. These initial solutions can be the foundation of great features that enable the rest of the teams to better build and establish solutions that bring it to life.If designers remain sidelined, teams will keep shipping products that feel disjointed, generic, or frustrating to use. But if design leads without staying grounded in technical and business realities, solutions may end up beautiful but impractical or impossible to bring through to production. This new approach depends on design remaining tightly connected to both business goals and engineering constraints, stepping beyond old silos to work collaboratively from the start. Rather than throwing things over the fence to development and back again, we must establish clear outcomes and follow them all the way to conclusion.While this is likely only possible with web development teams due to the limitations of these tools, it’s extremely likely that code generation tools for apps are just around the corner. For now, web teams are living in the future and should look to benefit.If you feel like your team is excited about this future or you’d like to learn more about what AI can do for your design team, we’d love to hear from you. At Hint Services, we run workshops specifically for design teams and offer advice for clients looking to leverage AI tooling in their organizations. If this resonates with you, please drop us a line!Stable Discussion is reader-supported. To receive new posts and support our work, consider becoming a free or paid subscriber. Get full access to Stable Discussion at blog.stablediscussion.com/subscribe
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  • Staying Creative in 2024 - Stable Discussion Podcast - Episode 9
    The podcast returns to discuss the significant advancements in AI image generation and video creation technologies, focusing on MidJourney 6 for its photorealism and stylistic capabilities, DALLE 3's improvements alongside ChatGPT, and the emergence of Stable Diffusion 3. They highlight the rapid maturation of image generators, mentioning developments in real-time generation and the potential applications in dynamic environments like video games.The conversation also covers the advancements in video generation, specifically mentioning OpenAI's Sora. They touch on the integration of these technologies with language models, leading to more complex and multimodal AI capabilities. The discussion reflects on the broader implications of these AI advancements on creativity, productivity, and the potential for these tools to understand and generate content with a deeper grasp of context and creativity.Show Links:MidjourneySoraRing Attention with Blockwise Transformers for Near-Infinite ContextInformation articleThanks for reading Stable Discussion! Subscribe for free to receive new posts and support our work. Get full access to Stable Discussion at blog.stablediscussion.com/subscribe
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  • Returning to AI - Stable Discussion Podcast - Episode 8
    Della and Ben return to the podcast and get caught up with months of news bringing together their highlights just in time for the holidays. Stay tuned for an interesting run through the latest major changes that excite and inspire us about AI.LinksDALL·E 3SDXL TurboPikaGPT-4 TurboAWS Bedrockllamafiletwominutepapers $1 GPT gameAda Customer ExperienceThanks for listening to Stable Discussion! Subscribe for free to receive new posts and support our work. Get full access to Stable Discussion at blog.stablediscussion.com/subscribe
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  • Are GPTs a Marketing Gimmick?
    OpenAI released a new feature where you can create "your own GPT" experience within ChatGPT. Builders of the new GPTs can adjust ChatGPT to act differently and read from custom documentation, all without needing any coding knowledge. Additionally, there's potential to make money off of these tools, which adds significantly to the marketability of these features. However, I struggle to see a revolutionary change with GPTs.I see GPTs as something similar to a bookmark or a shortcut for an assistant. The same functionality exists easily in ChatGPT, but this is a faster means of achieving the same things. I use bookmarks frequently and after sitting with GPTs for a little while, I can see their usefulness. I just think that the value is limited.To explore their usage, I built a GPT that can help with writing emails. It templates setting up a chat around what kind of email I'm sending, how that email should be written, and a little context helping to craft the letter. This allows me to write what I want to say using shorthand and it gives me back a structure that matches the intended recipient. You can try it out here.It's a pretty handy GPT and has also helped me teach what's possible to those less familiar with the ChatGPT experience. The prompts and setup are built-in, and you can get right to chatting, which helps cut down on the confusion for those new to working with AI interfaces. Unfortunately, these aren't shareable with others who don't already have a ChatGPT Plus subscription, so the user base is limited. But being accessible to new users isn't the only measure of usefulness. To be highly useful, GPTs need to deliver a great experience to the user around a specific task. To do that, it needs to be hard to distract it from that task. Say we want critical feedback on our writing, and it responds with something true and helpful that we don't want to hear. If we argue with it, it should hold its ground or navigate the conversation in a way that can help to convince us. But GPTs can be derailed by user requests and arguments, which means they'll most likely cave to your opinion rather than help you.This makes using AI programming interfaces, like the OpenAI API, much more powerful for crafting excellent experiences. By interpreting user input in a program, each request can be modified so that the AI responds in a direct and intended way. While you need programming skills, the user experience can be significantly better.One of the most memorable experiences of a stubborn AI has been in my experiences chatting with Pi. After some conversation, I tried to practice Korean with it. The AI unfortunately believed I was joking around and making up words. I tried to correct it and told it how I was learning Korean with my girlfriend. It laughed at me and couldn't believe I had a girlfriend. (Ouch...) Nothing I could say would derail it from its belief that I was joking with it about any topic.This experience was unlike anything I'd experienced with ChatGPT. While the responses weren't following my commands, they did convince me that I was speaking with something that had its own agenda outside my own, which was compelling. Comparing that with the unconfident responses of ChatGPT responding to your criticism shows just how much more there is to explore outside a GPT-driven experience.One other major component of GPTs is the new documentation integration. GPT builders can add documents to be referenced in conversations that improve the responses and provide information that the AIs have not been trained on.However, there isn't a lot of control over how the documents are read by the GPT. Users may ask questions from the documents and get back responses that correctly reference the document but don't actually give you the knowledge that the document holds. This is because you don't have control over how the documents are read compared to hand-tuned retrieval systems. We made a YouTube video about this where you can find more information about how documents are tricky to reference with AI systems.DALL·E 3 integration into GPTs seems unique and interesting. The integration of chat and image generation means that your control over the images is lessened, but the assistant can do a lot to facilitate image generation. If we could control a bit more about how documents are referenced, there could be some interesting avenues where GPTs could define a style or direction for image generation. Again, users generally have more control when dealing with the programming interfaces directly.In all, I think GPTs provide a unique shortcut for your usual ChatGPT experience. While the reality of using them is limited, they may provide a helpful introduction to those who are less familiar with AI. Engineers, programmers, and scientists will likely see the edge cases quickly but may still benefit from some provided shortcuts. The experience isn't revolutionary, but it has some usefulness given the right thinking around what is provided.Thanks for reading Stable Discussion! Subscribe for free to receive new posts and support our work. Get full access to Stable Discussion at blog.stablediscussion.com/subscribe
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  • Finding Good Information About AI (Part 2)
    With the changes at OpenAI this week, I'm assuming your newsfeed is being flooded with speculation and drama. Maybe you've been missing Game of Thrones and that's exactly what you're hoping to see. However, if you'd rather find other sources of information about AI outside the tabloids, then I have a model for you.This continues our prior post from last week that covered the first part of this model. Those were the Commentators, Professionals and Innovators creating AI content. This week's post covers the remaining two groups: Leaders and Misadopters.LeadersThese are engineers and scientists from industry-leading AI companies who form the direction of AI advancement. Seeking to compete with other companies, these groups look for highly scalable solutions that promote their businesses. The latest major releases from OpenAI this week fall directly into this category.There are some seriously incredible things being done by the major companies leading AI. But you can't separate the work from the motivations. Those companies have a specific mission and may look toward that mission over exploring the space that they're helping to develop. Sometimes this can make their announcements feel disconnected from the real world or more important than they actually are.Industry leaders are the best at marketing information about what new technologies are being created. The content is entertaining and informative and provides a good introductory view of these concepts. But if you're looking for a more objective measure of the technology, you might not find that view being publicized by those with the most to gain.Leaders to watch:OpenAI - Pretty clear driver of major change and has "GPT"-of-things as its brand, which has become somewhat synonymous with AI.GitHub Next - A team at GitHub looking at developer applications of LLM software to determine what is possible.MisadoptersThis group largely focuses on shouting down the hype surrounding AI. While some of the content that they create is diligently documented or reviewed, much of the content can be opinionated or situational. Similar to other interest groups, this group is often looking for a place to lead the conversation on technology and the development of a brand.As with many technologies, people question the need for a new technology and its ability to solve problems better than the "tried and true" way. In infancy, the technology seems to have many limitations, and that can often make it seem like we should abandon any further investment. However, those with longer-term vision can see that there is opportunity, despite the advice of Misadopters.This advice can be well-intentioned for many reasons as well. A feature may not be well understood or incorrectly posted on a forum. Teams of engineers may try to take AI practices and integrate them into their existing applications. If it doesn't work as intended, they feel they have evidence that "AI doesn't work". These teams instead need to take a step back and look at their approach to see if maybe there is something that is missing. But that can be hard when you need to release software on a deadline.AI today can be a gimmick that gets rudely tacked onto an existing application like Notion or Snapchat. The service doesn't feel like it fully aligns with the mission of the application and isn't bringing something that the users were looking for. Product leaders need to reevaluate their objectives and find solutions where AI fits more naturally into the product, rather than shoehorning it into their existing solutions.Misadopters provide a great place to find negative opinions about AI. There will continue to be a growing wealth of this type of knowledge on the internet. However, these conversations aren't the most inspirational or pragmatic. As with any of the information produced by any of these groups, be careful to evaluate why the information was created and for what purpose.I try to forget Misadopters exist.While it would be great to have a few negative points to look at, I generally don't get that excited about shouting down ideas even if they're wrong. I don't believe AI fits every niche or possibility, but I also don't think it's just hype.My assumption is that you, the reader, can sniff out what kind of content I'm referring to. If not, that's ok too. Start looking and second-guessing broad statements about how "AI is this" or "AI will do that". Keep in mind that there is a wider range of possibilities if you know where to look.Bringing It All TogetherNow that we have the definitions out of the way it's time to decide what kind of content speaks to you. You've probably already checked out one or more of the sources included, but if not, let me try to point you to where you'll be interested.If you're interested in discussing AI in general and don't want to get too technical, I think Commentators are a good source for you. You'll get conflicting viewpoints often, but that can also be the exciting drama you're looking for.For news straight from the source and to better understand the latest updates that are being released, Leaders offer a one-stop shop. Most people with some interest in AI will be keeping up to date here, and it's good to stay apprised of the latest announcements coming from this group.As someone looking to dive deep into one topic or learn something particular about AI, Professionals are the best to look towards. They've turned teaching a skill into a business and there are a lot of people hungry for your attention and putting a lot of effort into ensuring that you succeed, so you can maybe buy a course or two.If you're looking to be inspired by the things people are building and better understand how and why, look to Innovators. These are the people testing the outer limits of AI and trying things nobody has tried before. You'll feel inspired and maybe a little dumb part of the time. But that's always good motivation to get started building your own thing.Thanks for reading Stable Discussion! Subscribe for free to receive new posts and support our work. Get full access to Stable Discussion at blog.stablediscussion.com/subscribe
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Artificial Intelligence is changing our world and we help better understand what this means to all of us. We'll look at what's possible and where is the technology still not there yet. blog.stablediscussion.com
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