Everyone is raving about text models, but I'm even more excited about vision, audio, and image models. They'll push creativity and accessibility forward, making AI truly open for everyone. GPT Voice can shift the way you work. Vision and image models might change the rest.

I bought something unique and it took me 20 years to complete the checkout funnel. But it was worth it.

The Longest Checkout Flow: 20 Years

I recently bought a special kind of art that I discovered long time ago: a glass sphere with a unique depth effect when you look at it and when the light shines on it. I think it took me around 15 to 20 years to buy it. I first came across these spheres around 20 years ago, probably on Reddit. I do not remember exactly where I first encountered it.

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Working with agents using voice mode (specifically Codex voice) feels like a totally different way of interacting. It'll even feel more magical if we'll ever reach GPT 5.6-Luna levels of speed, with Sol quality

Life for me has always been about scents, about things that linger and fade away, only to reappear later, evoked by the scents themselves.

Scents of Life

Life for me has always been made of scents. Of smells that emerge and unsettle you. Of thoughts that cling to a single fragrance molecule, to a particular accord, lingering not only on your clothes but in your memory. Like the scent of me embracing my mother on a cold winter night, when she came home from work and her coat carried the faint smell of smoke, along with the crisp note of the winter air woven into the worn leather of her jacket.

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Read this 3 times because the HuggingFace / OpenAI security incident is scary and fascinating at so many levels 👇

Traits, Teaching, Time, Admiration, Credit, AI, Endings. Here's what it took me (and my recipe) to ask for guidance in today's world.

Asking for Guidance

How do you ask for guidance in today's world? Here's what comes to mind for me, based on a recent experience. Traits I wanted to ask for specific guidance and feedback from some people I admired, people I worked with. I wanted to understand if and how my work, and the way I am, impacted them. There are people who are able to spot their strong traits and weak traits easily.

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Here's an informative read if you're into prompt injections and want to understand the attack surface of them. OpenAI shared an article around GPT-Red, an automated way to test how their models perform against prompt injection.

You should own your content, and you should be free to move it to whatever platform you want. Sadly, that is not always the case. This film from @codeforthepeople.com is a reminder of why people stand for open source and their values. Worth the 20' watch, trust me. www.youtube.com/watch?v=8lQi...

Code for the People | A Film by Bao Nguyen | Full Documentary

YouTube video by Code for the People

youtube.com

3+1 books worth reading to think better about numbers and biases: 1️⃣ Factfulness, by Hans Rosling, Ola Rosling, and Anna Rosling Rönnlund: Instincts and biases tricks us, this will help you reading the world (with some optimism).

Your agent can use MCPs to control apps and websites, yet sometimes you don't even know what they're doing. It shouldn't be like this. Security should always come first. @wpvip.com just released the Secure MCP, and I hope others will follow this lead, honestly, because it's just that useful.

I didn't expect to write this, but here we are: Slop is actually good for you.

Slop is Inevitable, Slop is Good

More than 15 years ago, I decided I wanted to learn singing. Up until that point, I was the guy who didn't sing. I didn't sing in public, nor privately.We have this image of people singing in the shower. I didn't sing in the shower. Singing was not part of my radar, it was invisible to me, it was a skill I never thought existed, although I could clearly see (and hear) singers.

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(effective) Agentic Loops are the Deep Work state for LLM. What is your human loop, then?

I always trusted numbers, and while I was often skeptical of stats, only recently I realized how easy it is to game them. The Will Rogers phenomenon changed the way I see the world.

The Problem with Statistics and Averages: The Will Rogers Phenomenon

One of the problems with statistics and numbers is that we trust them as if they're always trustworthy. But the problem with those numbers is that they depend on which domains and which sources they're using. Averages are even trickier than that. One concept that blew my mind recently is the Will Rogers phenomenon. A Simple Example Let's say you're a sales manager.

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There's a new discussion paper based on 26.000 Chinese students comparing those using AI vs those not using it. The result: AI kids were faster in the short term, got worse after 2 years. No surprise. We're still adapting. We can't just replace our skills with AI and be done with it.

Either you're locked into a system, or you're free to change your mind, with no chains. Having something that stands for that freedom is truly priceless in today's world, where most of the products try to lock you in. Be brave (and read this beautiful post from @zeldman.bsky.social ).

zeldman@zeldman.bsky.social · last mo.

The Human Story of the Open Web STOP ME if you’ve heard this one: The members of an extended family spend years curating a shared online photo album. Then the website they posted on vanishes, flushing their collective memories away forever....

Imagine a self evolving SAAS software where you can pay the tokens to build a feature you needed, in addition to a monthly fee. If others will use it then I the fee you pay will be detracted by your monthly costs. If you’ll be the only one using it, that’s it. Would you use it?

Multiple Dimensions of AI Cerebras just announced Gemma 4 31B running at over 1,800 tokens per second.

This resonates hard with me. It's not happening every day, but it is happening. It's hard to say if it's caused by willpower depletion or just exhaustion. Not so unexpectedly, @elijahpotter.dev added a very smart idea at the end of the blog post. Worth a read. elijahpotter.dev/articles/slo...

OpenAI just announced its first chip, and it’s no surprise. AI is not cheap. It takes quite a lot of money and electricity to run, and there’s a reason companies are starting to build chips.

To understand we need to let go of our ego and stop trying to ask smart questions. Simple, basic questions are incredibly effective to get deeper into any problem and get a superior understanding. Letting the ego go is the hard part.

Understanding by Asking Questions

One of the things that makes understanding easier is asking questions. We are often tricked by our own intelligence because we think we understand, whereas in fact we don’t: We’re not truly understanding something. What’s stopping us from understanding the solution is getting deeper into the problem.But how do you get much deeper into the problem? It’s something that I also touched…

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ChatGPT is offsetting Pulse in favor of Scheduled actions and this is a strong reminder of what AI truly unlocked for product development: The acceptance of experimental features.

AI will happily spend tokens all day long. It won’t question assumptions. It won’t ask whether the idea is worth pursuing. Which brings us back to the same product question we’ve always had: What’s the value of what you want to build?

Cutting Costs / Adding Value

What is price? It can be a measure to "weight value".For example, there was this person on Twitter that stated stated how $30 per PR shipped is a good price, and I tend to agree. The thing we have with AI now is that you can spin up a model ask it to build something. Guess what? The model will agree and will start using tokens (spending tokens).

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The Midjourney pivot to medical stuff is mindblowing. I'm really curious to see how that will turn out.

“60% say AI in a brand’s messaging is a turnoff, not a feature.” That’s one of the findings from the @wpvip.com article "Future of the Web 2026: AI Brand Visibility Research." And… I kind of agree. I mean, who really wants to talk to an AI unintentionally? (continues)

This WhatsApp scam had my real booking reference and hotel dates. That’s exactly why it was dangerous and worth sharing so you know how phishing is evolving. Enjoy!

When Phishing Comes With Your Booking Details and What To Do About It

Last Saturday, I received a WhatsApp message.The interesting thing was that it contained very precise information about a booking I had with a hotel that I was going to in a few weeks. My first reaction was, hey, I need to confirm the reservation. I want to make sure that my reservation is being kept. At the same time, I realized that there were a couple of things that were off.

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DataBricks released a new meta-harness that's model agnostic and I feel many players in this space are all trying to build similar solutions to similar problems only to see which one will stick.

I've been thinking about what it takes to keep a project opinionated as it grows. It's easy to take a stance early on, but passing that vision down with the same intensity over time is harder than it seems. My take below.

Opinionated vs Not Opinionated

You're maintaining a project that is going to be used by other people, think about a library or a set of components. One of the key elements is to choose whether you want that project to be opinionated or not opinionated. Opinionated means that you have a vision, you care about that vision, and you adapt to the goal, so that you get closer to what that vision is.

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How many times have you thought, “I’d really love to do X (vacation, new hobby, etc) but I have do Y (insert random excuse) so it's not the right time”? Guess what? The time was actually right. I get more into why below

It’s Never the Right Time, Yet It Always Is

How many times have you thought, “I’d really love to take this trip right now, but I have work, I can’t afford it.” Or, “I’d like to have a child, but my life is too messy right now, I wouldn’t know how to handle it.” When is the right time? When does that mysterious alignment of planets, events, things, and people happen, where everything is in its place and the only choice you have to make is handed to you by what we might call fate, ready to be seized?

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We're treating AI like something that "knows it all", but a recent paper showed how easy it is to bias it, even with one single element in the training data. From a human perspective this is a reminder that you should always question the output (as you would with an actual human).

Anthropic’s ban on AI tools during job interviews is a reminder of what has always been special about humans.