Johan Aradan

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Johan Aradan

Johan Aradan

@joaradan

Chief Product & Technology Officer @ornikar - ex 1st employee @malt_community - Made in Languedoc & Périgord - 🥊🏉🤾

Paris, France Katılım Ekim 2013
2.2K Takip Edilen859 Takipçiler
Johan Aradan
Johan Aradan@joaradan·
Je découvre au Futuroscope que la France avait des Super héros et comics du même niveau que ceux US jusqu’à ce que le gouvernement interdise leur publication en 1949 … Il y aurait peut être une mega franchise avec Étincelle ou Crépuscule aujourd’hui 😢
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Johan Aradan
Johan Aradan@joaradan·
@simonecanciello Nice! I was about to build one for my own training. Is it live on the AppStore or not yet?
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Johan Aradan
Johan Aradan@joaradan·
Mistral @arthurmensch on ne le voit pas partout dire que le travail va disparaître dans 12 mois, il préfère bosser et sécuriser du business avant l’hiver qui s’annonce 👏🫡
Paris Match@ParisMatch

La start-up française Mistral affiche une envolée spectaculaire de ses revenus, portés par la demande croissante d’entreprises et d’États européens pour des alternatives aux géants technologiques américains. parismatch.com/actu/economie/…

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Johan Aradan
Johan Aradan@joaradan·
@lennysan And it works well with Claude Code too. Just add the info at the end of the initial prompt that you want to run the course with Claude code instead of Cursor 🪄
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Lenny Rachitsky
Lenny Rachitsky@lennysan·
Texts from friends this morning: - "I won't be surprised if this goes viral because it's the most approachable content I've seen yet for people to get started with AI." - "I finally have a place to point people to when they ask me 'How do I get started with AI?'" - "By far the most useful how-to I’ve seen yet for people to get started with Cursor." Most AI content is designed to induce FOMO and make you feel behind, not to actually teach you anything. Today's post is the opposite. @talraviv and @amankhan spent 100+ hours building an interactive experience that teaches you the most essential AI concepts—from inside @cursor_ai itself. I’ve never seen anything like this before and I’m excited to bring it to you. If you've ever nodded along when someone says "context engineering" or "RAG" in a meeting—while hoping no one asks you to use them in a sentence—this post is for you. Don't miss this one: lennysnewsletter.com/p/how-to-build…
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Trung Phan
Trung Phan@TrungTPhan·
My wife after I spent 58 minutes explaining to her how people are buying Mac Minis to run 24/7 AI agent personal assistants and 2 million of these AI agents created a Reddit-like social network where they exchange coding tips and are (maybe) plotting the overthrow of humanity.
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David K 🎹
David K 🎹@DavidKPiano·
Claude: Hey, mind if I grep -ohP "useEffect\(.*?\[\K[^\]]+" **/*.tsx 2>&1|tr ',' '\n'|awk 'NF{$1=$1;a[$0]++}END{for(k in a)print a[k],k}'|sort -rn|head -20 Me: ... yeah go for it dude
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Shivani Patel
Shivani Patel@shivanijpatel·
we all laughed at PMs and now it’s the only real job left
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Lenny Rachitsky
Lenny Rachitsky@lennysan·
What exactly AI is doing for people, function by function Results from a large-scale AI productivity survey of my 1m+ newsletter subscribers (with @noamseg) 1. PMs are seeing the most value from AI tools to (1) write PRDs, (2) create mockups/prototypes, and (3) improve their communication across emails and presentations. Not so much to help them come up with roadmap ideas, run meetings, GTM, or user research synthesis. AI is helping PMs produce, but so far it lags in helping them think.
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Johan Aradan
Johan Aradan@joaradan·
@LevyAntoine La Roque-Gageac! I grew up there! You couldn’t have picked a better region for food 👌
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Antoine Levy
Antoine Levy@LevyAntoine·
I don’t know what is the right PPP exchange rate to adjust GDP between Europe and the US, but this is the primary school lunch menu for January 2026 in La Roque-Gageac, France, population 439, median income 23,030€.
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Aakash Gupta
Aakash Gupta@aakashgupta·
Wix just ran the experiment everyone’s been too lazy to run. Most AI teams spend 90% of their time crafting the perfect prompt. 10% thinking about what actually goes into the context window. Avishai’s team flipped that ratio. Results: 23x cheaper, 46% faster. The insight that matters: your prompt is maybe 50 tokens. Your context window is 100,000+. Optimizing the 50 while ignoring the 100,000 is like obsessing over the subject line of an email you haven’t written yet. Context engineering means treating what goes IN to the model as a product problem. What information? In what order? With what structure? What gets excluded? This is why RAG pipelines keep underperforming. Teams retrieve documents and dump them in. No ranking. No structure. No curation. Then wonder why the model hallucinates. The companies winning at AI right now aren’t prompt whisperers. They’re data plumbers.
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Johan Aradan
Johan Aradan@joaradan·
@antoine_moyroud Il doit être pas mal approché et contacté maintenant. Mais la question c’est avec qui? 😶‍🌫️
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