Adrien Tsagliotis

Tech writer @JDNebusiness - Author @dunod - Lecturer @sorbonneparis1

[Adrien Tsagliotis @scoolada]

Wow - merci @joinstationf :) https://t.co/RBNMIjcq89

[STATION F @joinstationf]

Can’t be a good week end without a good book! Here are our favorites about startups and entrepreneurship 😉📚 @peterthiel @nireyal @scoolada @ericries @mikkelsvane @yegg @jwmares 🙏 #VendrediLecture #FridayFeeling

[Sac @Saccc_c]

花费16天，我用 Opus 5.5 将小王子的故事制作成了3D剧情游戏

结合Tripo+Blender，Opus 5.5 将小王子故事中的每一个星球变成了可探索的3D场景

希望大家能支持一手，后续会开源整个游戏，以及详细制作流程

Welcome to The Little Prince: Across the Stars✨：https://t.co/qr4wR0jLu3

[Adrien Tsagliotis @scoolada]

Just tested Seedance 2.5 on @runwayml Really impressive.

Better realism, scene understanding, and especially character consistency (with much less work than before)

We’re entering an era where anyone can become a filmmaker 🎬

Next step: real-time, personalized movies? 🤔

[Adrien Tsagliotis @scoolada]

@sulfurscales Prompts

[Jason Fried @jasonfried]

A bespoke software revolution? I don't buy it.

It'll exist. It already exists. Small consultants and big consulting firms have made custom software for years. It almost always sucks. It’s bloated, confusing, and because the client pays, it’s built wrong in all the ways.

Who’s excited about bespoke software? Software makers! Of course they're excited about building bespoke software — that's what they do. X is full of them. Your feed is full of people who love making software talking about making software. Of course they’re excited about the revolution. Echo, echo, echo...

Most people don’t like computers. Nobody in tech wants to say that out loud. People tolerate computers. They use them because they have to. Given the choice, most would rather not think about them at all.

So when someone suggests that AI means everyone will build their own custom tools, ask who "everyone" is. The three-person accounting firm drowning in client paperwork? They want the paperwork gone, not a new system to maintain. The regional logistics company with 40 trucks? They want the routes optimized, not Joe spouting off about this new system he’s been messing around with. The law firm billing 70-hour weeks? They want leverage on their time, not a software project to design.

They don’t hate technology. But building and maintaining their own critical systems isn’t their wheelhouse, regardless of how much faster and easier it’s become. It's another job on top of the job.

Will these people use AI? Absolutely, for all sorts of things. Will some outliers go deep and build real custom systems? Sure, but they're almost always people who already had some pull toward software. The curiosity was already there. They were dabblers before.

Giving everyone access to software building tools doesn't mean everyone becomes a builder. A powerful excavator doesn't turn a homeowner into a contractor. Most people just want the hole dug by someone else. They don’t want the responsibility either.

[Journal du Net @JDNebusiness]

Contrefaçon... ou pas ? Ce que vous avez le droit de faire avec l'IA https://t.co/BcOXhz3SjX

[Gensai.ai @gensai_ai]

Marc Theermann (Boston Dynamics) : "Boston Dynamics débutera la commercialisation du robot Atlas en début d'année", par @scoolada : https://t.co/ZO1NGZJSDy via @journaldunet

[Adrien Tsagliotis @scoolada]

@setu_ai_expert G

[Adrien Tsagliotis @scoolada]

@samruddhi_mokal Gamma

[Gilles Babinet @babgi]

La situation sur les multiples et la valorisation des principaux acteurs de l'IA fondationnelle.

[Ethan Mollick @emollick]

This paper shows that you can predict actual purchase intent (90% accuracy) by asking an LLM to impersonate a customer with a demographic profile, giving it a product & having it give its impressions, which another AI rates.

No fine-tuning or training & beats classic ML methods.

[Adrien Tsagliotis @scoolada]

@mikefutia Sora

[Adrien Tsagliotis @scoolada]

@eyad_khrais @perplexity_ai Prompt :)

[Adrien Tsagliotis @scoolada]

@shl 🙋‍♂️

[Andrew Ng @AndrewYNg]

The invention of modern writing instruments like the typewriter made writing easier, but they also led to the rise of writer’s block, where deciding what to write became the bottleneck. Similarly, the invention of agentic coding assistants has led to a new builder’s block, where the holdup is deciding what to build. I call this the Product Management Bottleneck.

Product management is the art and science of deciding what to build. Because highly agentic coding accelerates the writing of software to a given product specification, deciding what to build is the new bottleneck, especially in early-stage projects. As the teams I work with take advantage of agentic coders, I increasingly value product managers (PMs) who have very high user empathy and can make product decisions quickly, so the speed of product decision-making matches the speed of coding.

PMs with high user empathy can make decisions by gut and get them right a lot of the time. As new information comes in, they can keep refining their mental models of what users like or do not like — and thereby refine their gut — and keep making fast decisions of increasing quality.

Many tactics are available to get user feedback and other forms of data that shape our beliefs about users. They include conversations with a handful of users, focus groups, surveys, and A/B tests on scaled products. But to drive progress at GenAI speed, I find that synthesizing all these sources of data in a PM's gut helps us move faster.

Let me illustrate with an example. Recently, my team debated which of 4 features users would prefer. I had my instincts, but none of us were sure, so we surveyed about 1,000 users. The results contradicted my initial beliefs — I was wrong! So what was the right thing to do at this point?
- Option 1: Go by the survey and build what users told us clearly they prefer.
- Option 2: Examine the survey data in detail to see how it changes my beliefs about what users want. That is, refine my mental model of users. Then use my revised mental model to decide what to do.

Even though some would consider Option 1 the “data-driven” way to make decisions, I consider this an inferior approach for most projects. Surveys may be flawed. Further, taking time to run a survey before making a decision results in slow decision-making.

In contrast, using Option 2, the survey results give much more generalizable information that can help me shape not just this decision, but many others as well. And it lets me process this one piece of data alongside all the user conversations, surveys, market reports, and observations of user behavior when they’re engaging with our product to form a much fuller view on how to serve users. Ultimately, that mental model drives my product decisions.

Of course, this technique does not always scale. For example, with programmatic online advertising in which AI might try to optimize the number of clicks on ads shown, an automated system conducts far more experiments in parallel and gathers data on what users do and do not click on, to filter through a PM's mental model of users. When a system needs to make a huge number of decisions, such as what ads to show (or products to recommend) on a huge number of pages, PM review and human intuition do not scale.

But in products where a team is making a small number of critical decisions such as what key features to prioritize, I find that data — used to help build a good mental model of the user, which is then applied to make decisions very quickly — is still the best way to drive rapid progress and relieve the Product Management Bottleneck.

[Original text: https://t.co/1tulDs3k7U ]

[Adrien Tsagliotis @scoolada]

Very interesting demo on how to make infinite videos

[fabian @fabianstelzer]

Kling 2.5 "infinite" videos are HYPE rn, so here's a 15 min full tutorial that shows you exactly how you can create your own - I made a custom agent that does everything for you so you can focus on the creative direction:

[Grant Lee @thisisgrantlee]

Yes, our team of 30 could fit in a small restaurant. But we serve 50 million users profitably while most AI startups burn millions serving thousands.

The future belongs to tiny teams of extraordinary people.

[Travis Davids @MrDavids1]

I think I'm the first person to generate more than 8 items into a single image using Google Gemini Flash Image (Nano Banana). I have even exceeded the 8 upload limit on Freepik. How did I do this? Create a collage with everything and label each item on the image. When you upload the image, be descriptive and give each item the same name you labeled it on the image. Look at the end result, 10 items in a single image with excellent accuracy (Only thing not super accurate is the watch). I think this method is even more accurate than uploading individual photos. Go and try it!

The prompt I used to generate 10 items into a single image is as follows: A man is standing in a modern electronic store analyzing a digital camera. He is wearing a watch. On the table in front of him are sunglasses, headphones on a stand, a shoe, a helmet and a sneaker, a white sneaker and a black sneaker

[Adrien Tsagliotis @scoolada]

@framer_x I actually used Einstein as a character for consistency.

Script (and « jokes ») by ChatGPT, voice with ElevenLabs

[Adrien Tsagliotis @scoolada]

@framer_x Cool! These AI models enabling multi-shot generation are such a game changer and a huge time saver.

I made this quick video back in January :

At that time everything was done with Runway and Kling, without any multi-shot option (which would’ve made the video more dynamic).

[Adrien Tsagliotis @scoolada]

@SOL_Trending @framer_x Yes, it’s because I actually screenshotted the CapCut result

Nope, not available on YouTube (it was just a quick video I made for my nephews and nieces and to try these multi-shots models)

[Adrien Tsagliotis @scoolada]

The next Walt Disney could be a 12-year-old making a brilliant movie from their bedroom and sharing it on YouTube. These are exciting times! 🍿

[Framer 🇱🇹 @Framer_X]

This is Hopeless Steve.

A cartoon character you've created with AI.

You grew up watching Simpsons, South Park and now you dream of Hopeless Steve becoming the next big IP.

So you start posting short sketches on Youtube, TikTok, IG, etc.

Then one day... 👇