There’s a pretty great deal knocking about right now on the Samsung Galaxy Tab S10 Ultra, with £300 cashback up for grabs on purchases made up until June 24th. Customers will need to claim this offer via Samsung’s offers site within 30 days of buying the tablet, and it’s that simple.
To sweeten the deal, Samsung is also throwing in a free Slim Book Cover Keyboard for the tablet (worth £199), and customers can also bag a guaranteed £150 off when trading in any device, in any condition (even non-working!).
(Image credit: Samsung)
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(Image credit: Future)(Image credit: Samsung)
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YouTube CEO Neal Mohan announced that the platform’s short-form video format now generates 200 billion daily views during a keynote address at the Cannes Lions International Festival of Creativity.
The milestone comes as the Google-owned platform marks its 20th anniversary and faces increasing competition from TikTok and Instagram Reels in the short-form video space.
During his presentation, Mohan shared several performance metrics:
The television viewing data represents an evolution from YouTube’s mobile-first origins, with creators increasingly producing content formatted for larger screens.
YouTube will introduce Veo 3, Google DeepMind’s video generation model, to Shorts creators later this summer.
The tool enables users to create AI-generated backgrounds and video clips, building upon the existing Dream Screen feature.
The company also reported that its Auto Dubbing feature has processed over 20 million videos since launch six months ago. The tool currently translates content across nine languages, with 11 additional languages planned.
YouTube’s announcements come as the platform competes for creator attention and viewer time with TikTok, which popularized the short-form video format, and Meta’s Instagram Reels.
The emphasis on television viewing and longer-form content may represent an attempt to differentiate from mobile-first competitors.
While YouTube leads in platform breadth and viewing hours, TikTok still holds a cultural edge in mobile-native short video. YouTube’s push toward TV-based viewing and AI creation tools may help retain creator loyalty and expand monetization opportunities across formats.
The AI tools announcement follows similar features from competitors, including TikTok’s AI effects and Instagram’s creative tools.
The shift toward television viewing and serialized content marks a departure from YouTube’s roots as a platform for amateur video uploads.
As YouTube enters its third decade, the platform’s strategy appears focused on supporting professional content creation while expanding its technological capabilities through AI integration.
Featured Image: Screenshot from: blog.youtube/news-and-events/neal-mohan-cannes-2025/, June 2025.
Most people still think of AI as a tool for generating content or powering chatbots. But agentic AI is already driving deeper transformation—especially in customer experience.
Unlike traditional AI, AI agents don’t just respond—they act. These systems plan, reason, and execute tasks across departments, pulling from structured and unstructured data to deliver real results.
From reducing time-to-resolution in support, to enabling real-time personalization in marketing, AI agents are helping brands move faster, serve smarter, and scale customer impact—without scaling headcount.
In A Practical Guide to Agentic AI for Customer Experience from Snowflake, you’ll learn:
If you’re serious about putting AI to work—not just experimenting with it—this guide is a must-read. Get your copy here.
The post Beyond ChatGPT: What AI agents really do (and why it matters for customer experience) appeared first on MarTech.
Even for a series loaded with generational talents, it was mainly elements of the visual, narrative and writing design that defined the show and helped turn it into one of the most quietly genre-pushing animated series of the 90s. First of all was the invention of Squigglevision, a loop-based animation style masterminded by Tom Snyder. “In this method, the animator loosely traced the outline of each cartoon image several times and when these separate images ran together as a loop, the image would appear to be vibrating,” says Annette. Lacking the budget for traditional animation, this method allowed the image to possess the illusion of motion, much like the microscopic movements that happen in our eyes, without animating a metric ton of finicky animation frames. Similar to “Jittercam”, the antonym of Steadicam, the “boiled lines” effect also helps create a documentary-esque vibe, as if the characters are being filmed with a handheld camera.
Annette, Tom and their team found their animation style through Autodesk Animator, a clunky painting program developed in 1989 for the MS-DOS, which the team had previously been using for its original intention: creating educational math videos. In 1995, traditional 2D animation did not know its future was going take place on computers, but the team behind Katz stuck to what they knew best and set forth whilst smash hits like Toy Story illustrated the massive budgetary differences between the two studios.
Google is rolling out Search Live with voice features through its AI Mode Labs experiment.
You can now have natural, spoken conversations with Search while receiving web links in real-time.
The was previewed at Google I/O and is now available today for U.S. users.
You can access the feature by opening the Google app on Android or iOS.
Tap the new “Live” icon under the search bar, as shown below.
Once started, you can ask questions out loud and get AI-generated audio responses. Google says it uses a custom version of Gemini with advanced voice features.
The system remembers what you talked about before, which lets you ask follow-up questions naturally. For example, you could ask about preventing wrinkles in linen clothing while packing. Then you could ask what to do if wrinkles still happen.
Search Live keeps working even when you switch to other apps. Your conversations continue while you check email, browse social media, or do other things on your phone.
A “transcript” button shows you text versions of the audio responses. This means you can switch between talking and typing in the same conversation.
The feature also saves your conversation history. You can go back to previous Search Live sessions through your AI Mode history.
Web links show up on your screen alongside voice responses. This gives you quick access to source content if you want to dig deeper.
Google’s custom Gemini model for Search Live builds on the company’s existing search systems.
The setup uses what Google calls a “query fan-out technique” to find diverse web content. This aims to give you different sources and viewpoints during your search sessions.
Google plans to add more Search Live features in the coming months. This includes camera integration for real-time visual queries.
Visual search was also previewed at I/O. It would let you show Search what you’re seeing while talking about objects, locations, or situations around you.
Voice-driven conversational search could be a big shift in how people use search engines.
Google’s continued focus on natural language queries means optimization must go beyond traditional keyword targeting.
Web links still appear with AI voice responses. Marketers should test it out and consider how their content appears in conversational situations. This matters more as people ask follow-up questions and explore topics through natural dialogue.
This change may also affect how we understand search intent. Conversational queries often show more detailed needs than regular typed searches.
If you’re looking to learn more about AI Mode, check out this webinar: New Google AI Mode: Everything You Need To Know & What To Do Next
To use Search Live, you must join the AI Mode experiment through Google Labs.
Once signed up, the Live icon appears right away in the Google app.
Having decided that the value of live — be it live sports, live shopping, live-streaming, live events or live conversations — is of essential importance to its clients, Omnicom is partnering with several major platforms and publishers to harness live’s power.
DIgiday has learned that the holding company today is announcing partnerships with payment platform PayPal as well as with X, in hopes of getting clients closer to influencers and content that shows a higher propensity to spur consumers to purchase – and adding valuable purchase data to show where consumers are spending.
Starting with the X partnership, Omnicom is looking to take advantage of the fact that X is working to attract more creators and influencers, given its clout as a major second-screen hub. X has already solidified its status as a real-time reflector of trends too — both elements that Omnicom is looking to tap into, according to Megan Pagliuca, Omnicom Media Group North America’s chief product officer.
“What’s really different here is the role X plays as this cultural epicenter where we’re able to take this trends data, fuse it with audiences, fuse it with our elements of culture, use it for both brand creative execution on X and then also use it for influencer discovery and influencer activation,” said Pagliuca.
Here’s how the partnership, currently active in the U.S. only, works: X’s API data and Trends API are fed into Omni, Omnicom’s open operating system. Omni then matches the signals to find moments that work for an Omnicom client to attach itself to. The audience segments and corresponding trends by audience are both used to plan activations, which are pushed back into X for influencer discovery. Finally, all the insights gleaned are fed back into Omni’s Influencer Discovery Agent, an AI-powered agentic tool that identifies influencers and creators with the most impact on consumer engagement and performance, based on multiple criteria including audience match and cultural relevance.
Similar to Omnicom’s earlier Cannes announcements this week with Meta and Walmart before it, the Influencer Discovery Agent keeps amassing more knowledge with each deal the holdco makes, because it’s collecting input from all the major platforms where influencers and creators reach their audiences, and ostensibly getting smarter with each new input.
“What I’m most excited about here is looking at what moments of culture are being engaged with on X, and how we could use that to inform the content that those influencers are producing,” added Kevin Blazaitis, U.S. president of Creo, Omnicom Media Group’s influencer arm. “You have a very active base of niche communities — identifying the right voices of those. We’re excited to have our data play a larger role, to again expand voices and have that many to many communication.”
“This partnership is a prime example of how we help marketers take advantage of key moments, conversations and live moments taking place on our platform,” said Monique Pintarelli, X’s head of the Americas.
Zaryn Sidhu, OMG’s svp of social for North America, shot down any notion that the holdco might have lingering concerns over X’s recent history of eroding brand-safety efforts, citing Omnicom’s CASA efforts at ensuring brand safety protocols. “X is actually on par in terms of controls and partner verification,” said Sidhu. “We have adjacency and placement controls even down to the keyword level. We have third-party post-bid and pre-bid verification capabilities. We have content violation reporting.”
Omnicom today also unveiled a partnership with PayPal, which centers on attaching the finance app’s cross-merchant transactional data to OMG’s streaming TV inventory curation. OMG’s negotiated deals and curated supply paths are overlaid with PayPal’s transactional and purchase data via Magnite’s and PubMatic’s SSPs, enabling Omnicom clients to bid on both live and pre-recorded streaming inventory based on purchase data as a means of connecting with their audiences as effectively as possible.
Available in the U.S. in coming weeks before rolling out internationally, the arrangement lets OMG tap a vast transaction data set that also includes Venmo and Honey — two other payment platforms PayPal has that contribute to its transaction graph. It’s estimated some 430 million consumers use one of them, giving PayPal a 45% share of the global payments market, with $1.68 trillion in total payment volume in 2024.
“Live TV has long made it difficult for brands to reach the right audience in real time,” said Mark Grether, svp and general manager of PayPal Ads. “Bringing our technologies together and connecting transaction data with Live TV inventory improves the efficiency of awareness campaigns.”
“The ability to understand what users are shopping across merchants in this first party, deterministic data set, means we can pair the scale of PayPal and their transaction graph and their data with the Omnicom Media Group negotiated rates and inventory capabilities,” said Keagan McDonnell, senior director of product innovation and partnerships at OMG North America. “We believe that’s a very powerful use case in the market.”
Cox Automotive, an Omnicom client, is tapping into the data to more carefully target its streaming ad efforts. “This collaboration allows us to reach automotive audiences built on signals from PayPal’s extensive network of merchant partners, merging precision and scale,” said Jillian Davis, director of marketing technology at the client, which includes the Auto Trader and Kelly Blue Book brands. “By pairing PayPal transaction data with Omnicom’s media curation strategies, we can reach these hyper-relevant audiences without sacrificing inventory quality.”
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Despite reviewing and testing drawing tablets all the time, there’s something uniquely exciting about getting my hands on the latest from Wacom, and after using the new Wacom Intuos Pro Medium, I can honestly say it remains the gold standard for pen tablets in 2025.
This new Intuos Pro is a precise and beautifully designed drawing tablet that will no doubt remain the go-to choice for professionals in digital art and graphic design despite stiff competition from brands including XPPen, Huion, and Xencelabs. (Read my guide to the best drawing tablets for more choice.)
You may like
(Image credit: Future / Wacom)
What you get
Swipe to scroll horizontallyWacom Intuos Pro Medium specs
Dimensions:
291 x 206 x 4~7 mm / 11.5 x 8.1 x 0.160.28 inches
Active area:
187 x 105mm / 7.4 x4.1 inches
Weight:
411g / 14.50 oz
Battery life:
16 hours (10-12 real life experience)
Keys:
10 customisable keys, 2 customisable dials
Stylus:
Pro Pen 3 (pressure-sensitive, cordless, battery-free)
Pen pressure levels:
8,192
Pen tilt:
60 degrees
Pen resolution:
5,080 lpi
Multi-touch:
No
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Swipe to scroll horizontallyWacom Intuos Pro Medium score card
Attributes
Notes
Rating
In the box::
Everything you need, but a USB-C adapter would be welcome.
4/5
Specs:
Good sized drawing area and pressure levels..
4/5
Setting up:
Easy and comes with instructions.
5/5
Design:
Slim, lightweight, good Express Key position.
5/5
Pro Pen 3
Superb customisation and performance.
5/5
Performance
Accurate, precise and mobile.
5/5
Wacom Intuos Pro (2025): Price Comparison
This week’s Ask an SEO question about affiliate strategies comes from Mike R:
“How is AI changing affiliate marketing strategy in 2025? I’m concerned my current approach will become obsolete but don’t know which new techniques are actually worth adopting.”
Great question, Mike. I’m seeing a few trends and strategies that are changing, for the better and for the worse.
When AI is used properly in the affiliate marketing channel, it can help businesses and brands grow.
If any of the three types of businesses (defined below) in affiliate marketing use it in a way that AI and large language models are not ready for “yet,” it can backfire.
I’m answering this question in three parts, as I’m unsure which side of the industry you’re on.
For the record: The affiliate channel is not at risk (i.e., affiliate marketing is not dead) because affiliate marketing is more than a content website that creates a list or writes a review, and coupon sites intercept the end of sale.
Affiliate marketing is a mix of all marketing channels, including email, SMS, online and offline communities, PPC, media buying, and even print media.
It is not going to be as impacted by AI as SEO and content marketing – and in many ways, it will likely grow and scale from it.
Affiliates are the party that promotes another brand in hopes of earning a commission.
Here’s some of what I’m seeing regarding the use of AI and its impact on affiliate revenue.
Programmatic SEO is not new, and using LLMs to create content or lists is burning what were quality sites to the ground.
It is almost never a good idea; it doesn’t matter if AI can spin up content and get it publish-ready in minutes.
In the early 2000s, affiliates and SEO professionals would use pre-AI article spinners to create massive quantities of content from one or two professionally written and fact-checked articles, then publish them to blogs and third-party publishing platforms like Squidoo.
This is equivalent to affiliates publishing their content on Reddit or LinkedIn Pulse to rank it.
The algorithms caught up and penalized the affiliate websites. Squidoo and some of the third-party platforms managed to stay afloat as they had trust and a strong user base for a while.
Next, PHP became the go-to for programmatic SEO, and affiliates would generate shopping lists or pages with unique mixes of products and descriptions via merchant data feeds and network-provided tools. Then, these got penalized. Again, nothing new.
Media companies have been getting penalized and devalued for years for this, and plenty of content creators, too.
If an affiliate manager is telling you to use LLMs to create content, or someone is using LLMs and AI to do programmatic SEO, look for advice elsewhere.
I’ve watched multiple quality sites fall since ChatGPT, Perplexity, and others began writing and spinning their content.
In traditional affiliate marketing, if an affiliate is not making sales, even if they send quality traffic, they get ignored. LLMs have changed this 100%.
I’ve seen affiliates, including bloggers, YouTubers, forums, and social media influencers, are being sourced and cited by AI systems.
If the brand is not on the content being used for fact-checking (grounding) and sourcing, the brands begin to disappear from outputs and results. I’m seeing this firsthand.
Not getting traffic or sales, or being number seven to 10 on a list, now has value. The citations and mentions from the resources that LLMs trust can help your brand gain visibility in AI.
Affiliates can and should begin charging extra fees for these placements until the LLMs begin penalizing or ignoring pay-to-play content.
We’re likely a couple of years away from their algorithms being anywhere near that advanced, so it is a prime opportunity while Google is reducing traffic to publishers via AI Overviews.
I think coupon sites are going to take a substantial hit, as AI is starting to create its own lists of coupons that work.
It also includes where and how to save, where to shop, and current deals on specific products. For example, “I want to buy a pair of Asics Kayano 32 men’s running shoes and get them on sale. Where can I find a deal?”
Right now, Google’s AI Overviews are populating lists of where to find deals, and it is showing the coupon sites as the sources to the right. These sites are likely getting clicks now.
I’ve seen ChatGPT pull the codes directly and preventing the need to click to the coupon website and set their affiliate tracking. It does show the website it came from, though – just no reason to click since you get the code in the output.
One interesting thing is that ChatGPT may pull in vanity codes.
The output from ChatGPT featuring these could give an influencer who was sourced for the code or a coupon site credit for their sales, throwing attribution off, because it was the coupon that triggered the commission, even though the user was using the LLM.
The influencer did not have anything to do with this transaction, but they’ll be getting credit.
The brand may now pay more money to the influencer, when, in reality, it should be ChatGPT – that is where the customers are, not the influencer.
By showing where to find the deals and which deals are available by product (not brand), AI eliminates one of the deal and coupon site’s top-funnel traffic strategies to brands.
The biggest hit I see coupon sites taking is ranking in search engines for “brand + coupon” for the last-second click from someone who is already in the brand’s shopping cart.
If Google AI Overviews creates its own coupon lists as the output, like ChatGPT is doing, there is no reason to click on a coupon website and click their affiliate links.
But, don’t count deal and coupon sites out. They still have email lists and social media accounts that can drive top-funnel traffic, and they can reintroduce customers who have forgotten about you by utilizing their own internal databases of shoppers.
These are the people who manage programs by recruiting affiliates into the program, giving the affiliates the tools they need, and ensuring the data on the network is tracked and accurate so the brands being promoted have the sales and touchpoints they’re looking for.
Some managers hit the panic button because they relied on content sites and publishers who have SEO rankings, but AI Overviews is using affiliate and publisher content and not sending the same amount of traffic to the publishers.
This reduces the number of clicks and traffic. The publishers are still driving traffic, but it is coming in via Google and not the affiliate channel.
With that said, affiliate managers can shift their focus to channels not as impacted by AI Overviews, including:
From seeing this on a daily basis, it appears that high-quality publisher accounts are being created en masse as fronts for fraud and fake affiliate accounts.
I’ve had conversations with people hired by the fake affiliate account who are being paid to talk to the affiliate manager, so it makes these sites look even more legit. We’ll have back-and-forth emails, and in some cases, a call.
Once the traffic and sales start, it turns out to be stolen credit cards or program violations. In some instances, the person or websites they applied with no longer exist.
Interestingly, when they activate a year later, thinking you forgot about them, magically, the site reappears when they know you’re not checking.
Always evaluate a site, and if the content is being generated by LLMs or AI, it may be best to reject it and reduce the risk of a fake account.
AI content may rank temporarily, but this is not a long-term strategy. If your brand is being written about by AI and spun out to a site via programmatic SEO, there is a reasonable chance that the details won’t be as factual or as on-brand as they should be.
An affiliate who cannot take the time to create good content and use AI to edit, versus using AI to create and then edit, should not be trusted in your affiliate program.
When your affiliates are generating content or fact-checking via LLMs and AI, they’re not doing their jobs as your partners to promote your program factually, with correct talking points, and following brand guidelines.
There’s a reasonable chance that incorrect claims about financial products, medical treatments, or even books to buy and read will be in the content you, as a brand, are paying to have made.
Even if you’re paying on a performance basis, you are approving this content to be live and represent your brand. This is why affiliates in your program using AI to create content are a high risk.
Set rules and enforce them so that your brand cannot be included in any AI-created content, or remove the affiliate from your program until they’re ready to treat your brand or your clients’ brands with the same care as you do.
One interesting use of AI for affiliate management is merchant and affiliate matching using machine learning and AI by agencies and larger brands.
Just because a partner does well in one vertical or with one affiliate program that has a similar audience, it does not mean it is a good match for others.
One exception to using AI for matching is to build a list of potential partners from a database. But automatically approving that list because the output creates a list is problematic.
Each affiliate that is recommended still needs to be vetted by hand to make sure they meet the requirements of the new program.
Some of the best uses of AI, especially LLMs, have been building lists of potential partners.
You can train GPTs to validate the lists, remove current partners so you don’t accidentally email or call them, do a gap analysis, and even customize the recruitment email to a very strong degree.
No, it isn’t perfect, but you can save hours each week from the manual tasks of discovery, validation, and outreach.
The recruitment emails still need to be reviewed and sent manually, but it is a massive time-saver.
We manually review every email before it goes out and have to do a decent chunk of rewriting, but we’re saving large amounts of time, too.
We also pre-schedule the emails using a database tool, but we’ve slowly begun implementing new discovery and drafting methods, and they’re turning out to be fantastic.
I was a non-believer in AI for this at first, but now I’m about ready to double down, especially as the systems advance.
These are the tracking and payment platforms that power the affiliate programs.
Affiliates rely on them to accurately record sales and release payments.
Affiliate managers use them to track progress, simplify paying partners around the world, and generate reports based on the key performance indicators (KPIs) their company uses.
All of the networks we’re working on have an influx of AI-generated sites. I’ve talked to agencies and managers on the ones we don’t work on, and they’re seeing the same.
The networks would be wise to add filters and create an alert for affiliate managers to let them know if the affiliate is human or AI, meaning that AI would be a website and promotional method without quality control.
There are no advanced controls in place on any networks that I’ve seen specifically for AI affiliates. But most networks do have compliance teams to which you can report fake accounts.
From the networks I’ve talked to, they’re working on solutions to help detect and reject these sites, but it is a massive problem because they’re being generated at high volumes, and some are really hard to detect.
The spammers and scammers are getting smarter, and AI has given them a new advantage.
This is a double-edged sword. Networks have more data than any affiliate agency, and they may be best suited to try partner and program matching algorithms.
They can create a list of programs that an affiliate may want to test, or a list of partners a program manager can pay to recruit based on program goals and dimensions.
The downside is that programs spend countless hours recruiting partners for their programs. Networks doing matching and recruitment take that work and give it for free to that program’s competitors.
A second downside is that affiliates get bombarded with program requests, and this can cause that to skyrocket, making it harder to get them to open emails, including program updates and newsletters.
Once they start ignoring emails because of too many, you may not get compliance issues fixed or promotions that would normally have benefited both parties.
One of the most beneficial things a network can do, but none are currently doing on a mass scale (some are starting to, and it’s looking promising), is to use AI to create custom reports for affiliate programs. These could be charts and graphs on trends over XYZ years.
Another is a gap analysis of products that get bundled together by type of affiliate, and then which similar affiliates already in the program don’t have a specific SKU in their orders.
The manager can recommend pre-selling the SKU within the content that drives the sale, or adding that specific SKU as an upsell to any customer who came from that affiliate’s link, based on the affiliate ID passed in the URL.
It can show trends where there are cross-channel (SEO, email, PPC, SMS, etc) touchpoints and how it modifies seasonally, annually, and if the goal creates more or less sales for the affiliate channel or company as a whole.
One important thing to remember is that not all affiliate networks offer true cross-channel reporting. Multiple only offer it once the user has clicked an affiliate link.
AI is going to be amazing and horrible for each of the three entities above that make up the affiliate marketing channel.
If used correctly, it can save time, increase efficiency, and create more meaningful strategies.
At the same time, it could result in violations of a program’s Terms of Service (TOS), steal traffic from publishers, and harm multiple types of businesses.
More Resources:
Featured Image: Paulo Bobita/Search Engine Journal
In a world where attention is fleeting and culture moves at hyperspeed, brands must do more than advertise—they must emotionally resonate. As technology changes how we connect, the art of storytelling remains timeless.
In this episode of The Speed of Culture, Matt Britton speaks with Arturo Nuñez, founder and CEO of AIE Creative, a brand consultancy helping companies craft emotionally resonant, culturally authentic experiences.
Arturo shares how he builds brand love by leading with cultural authenticity. From Nike to Apple to entrepreneurship, he offers insights into how to fuel iconic brand moments.
Previously, Arturo held senior marketing roles at Apple, Nike, the NBA, and NuBank. From global expansion to brand storytelling, Arturo’s work has transformed how brands connect with diverse audiences across generations and geographies.
[03:57] Curiosity Is the Marketer’s Superpower — Arturo emphasizes that staying relevant in a fast-moving industry requires relentless curiosity. Whether adapting to AI, social media, or mobile trends, marketers must be lifelong learners. At Nike, this mindset translated into initiatives like Eakins, where insights from youth on the street shaped brand decisions. Brands that stay curious, listen closely, and adapt rapidly win.
[05:44] Culture Is Built on the Sidewalk, Not in the Boardroom — Youth no longer consume culture—they create it. Arturo reflects on how the rise of social platforms flipped the traditional power structure. Brands must now listen to and participate in conversations led by consumers, not control them. His work at the NBA showed how following players—rather than just teams—became the new path to fan engagement.
[15:07] Emotional Connection Is the Real Brand Currency — Arturo recounts how brands like Nike and Apple achieved irrational levels of loyalty—people tattoo Nike’s logo on their bodies or place Apple stickers on luxury cars—not because of features, but because of what these brands represent. At NuBank, he built Brazil’s most loved brand by crafting emotionally resonant stories that gave consumers hope and dignity. His message to marketers: product specs don’t build tribes—identity does.
[20:18] Authenticity Over Optimization: Passion Brands Win on Truth — Dante’s HiFi, Arturo’s vinyl-only bar in Miami, was created with no commercial intent, just a love for music. Yet it became a cultural destination. He explains that building something you personally believe in will always attract others who share that passion. Today’s consumers see through brands chasing trends for clout. Brands that build communities, not just campaigns, succeed by showing what they love, not just what they sell. Authenticity is your loudest differentiator in a market full of algorithms.
[33:33] Obsession, Not Perfection, Is the Path to Impact — In a powerful moment, Arturo shares a lesson from the late Kobe Bryant: greatness doesn’t come from natural talent—it comes from discipline, failure, and relentless improvement. Whether pitching a product, running a business, or chasing a dream, what matters most is obsession with your craft. Arturo warns aspiring creatives and entrepreneurs not to wait for perfect conditions—they’ll never arrive. The brands and people who win are those who jump, build the plane on the way down, and keep going no matter how often they’re told “no.”
That process really messed with my head. But I did it. I got the visa, got the awards, worked with big clients, built a studio and hired a team. I did what I was supposed to do. Even so, I didn’t feel like I fit the mould; I don’t sound like a typical founder. I didn’t grow up speaking English. I didn’t come from money. I never had training in public speaking. And I’ve tried to play the part, but it’s not really me. I’ve always felt like I had to prove myself twice – once with the work, and again to be taken seriously.
A few months ago, I was invited to close the main stage at one of the biggest design conferences in the world. It felt like a big moment. But the whole process leading up to it was more intense than what I’m used to. There were multiple rounds of content feedback, rehearsals, a lot of back and forth. I went along with it, but it didn’t feel great.
Then, a couple of nights before my talk, during a speakers’ dinner, someone from the company pulled me aside and said they wanted another rehearsal. The person hadn’t even seen my talk – they were just passing along the message. It felt off. Out of context, and kind of undermining. Like what I’d done so far wasn’t good enough.
I went back and rehearsed on my own. Not because I needed to, but because I felt like I had to prove something. Again.
