Johan Aradan

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

[Johan Aradan @joaradan]

I mean, running AI transformation in a 250 person company is already brutal.

Can’t imagine doing it at Uber or Microsoft if they nuked a decade of HR, IT & procurement processes chasing FOMO

[Thierry from arvy 🇨🇭 @ThierryBorgeat]

In the last 30 days alone:

– Microsoft cancelled most of its Claude Code licenses, citing cost
– Uber burned through its entire 2026 AI budget in 4 months
– Uber's COO publicly said AI costs are "harder to justify"
– A Fortune 20 CEO ordered token spending to be "dramatically slashed"
– One company spent $500M in a single month on Claude with no usage limits
– H200 rental prices crashed from $7/hr to $4/hr in three weeks

The stocks: still at all-time highs.

How long can the market keep ignoring the receipts?

[Johan Aradan @joaradan]

💡"I believe that the wrong strategy is to have your PMs shipping code - that just introduces another bottleneck that the best engineers will waste their time on. To be clear, PMs should be coding but they should do this in a playground to iterate, validate, and scope."

[Zeb Evans @DJ_CURFEW]

Today we reduced headcount by 22%. The business is the strongest it's ever been. So I think it's important to be direct about what I'm seeing and why.

First, I made this decision and I own it. I did it because the way to operate at the highest level of productivity is changing, and to win the future, ClickUp needs to change with it.

Second, this wasn't about cutting costs. Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional bands.

Most importantly, I have the deepest gratitude for those affected. We're doing this from a position of strength specifically so we can take care of people properly. Everyone affected receives a package aimed at honoring their contributions and easing the transition.

I only see two options: wait for this to play out gradually in the market or be honest about what I'm seeing and act proactively.

THE 100X ORGANIZATION
The primary change is that we're restructuring around what I call 100x org. The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago.

Incremental improvements to existing systems won't get us there. We need new ones. That means creating enough disruption to rebuild rather than iterate on what's already broken.

The common narrative is that AI makes everyone more productive. It doesn't. Many of the workflows of today, if left unchanged, create bottlenecks in AI systems.

These roles will evolve. But waiting for that to happen naturally means falling behind now.

The 100x org is actually heavily dependent on people - infinitely more than today. This is only possible with 10x people that have embraced and adopted new ways of working.

THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS

— THE BUILDERS: 10X ENGINEERS
I don't think most companies have internalized what's actually happening with AI in engineering. The common narrative is that AI makes all engineers more productive. That may be true in isolation, but at an organization level - that is the farthest thing from reality.

Here's what we've validated recently at ClickUp: the great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers. They're not writing code. They're directing agents that write code. The skill is judgment.

AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down.
Think about it - the bottlenecks are (1) orchestration - telling AI what to do, and (2) reviewing - what AI did. Everything is leapfrogged and no longer needed.
So who do you want orchestrating and reviewing code?

And how do you want your best engineers to spend their time?

If your best engineers are spending time reviewing other people's code, then this is inherently an inefficient bottleneck. These engineers can review their agent's code much faster than reviewing human code.

The new world is about enabling your 10x engineers to become 100x.

The wrong strategy is to push every engineer to use infinite tokens. Companies doing this are celebrating 500% more pull requests. But customer outcomes don't match the volume of code being generated.

I call this the great reckoning of AI coding, and every company will face this soon if not already.

More code is just another bottleneck to the best engineers, and ultimately to your company's impact as well.

— THE BUILDERS: 10X PRODUCT MANAGERS
Product management and design roles are merging.

Designers that have customer focus, become more like product managers.

And product managers that have intuition for UX become more like designers.

The bottleneck of user research is gone. It takes us just one mention of an agent to kickoff research and analyze results.

The bottleneck of product <> design iteration is also gone. The product builder iterates on their own, along with agents and skills that ensure alignment with quality and strategy.

Also controversial today - I believe that the wrong strategy is to have your PMs shipping code - that just introduces another bottleneck that the best engineers will waste their time on.

To be clear, PMs should be coding but they should do this in a playground to iterate, validate, and scope. That code should not go to production.

Everything outside of managing systems, orchestrating AI, and reviewing output becomes a bottleneck.
That's why the other roles that are critical along with these are the systems managers (to reduce bottlenecks) along with a bottleneck you can't replace - customer meeting time.

— THE SYSTEM MANAGERS
Ironically, the people that automate their jobs with AI will always have a job. They become owners of the AI systems - agent managers. We have many examples of these people at ClickUp.

The underlying systems in which we operate are absolutely critical to get right. I think most companies are delusional to think they can iterate on existing systems and compete in this new world.

You must create enough disruption so that old systems are deprecated entirely. If there's any definition for 'AI native' that's what it is.

— THE FRONT-LINERS
In a world that will become saturated with AI communication, the human touch will matter more than anything to customers.

This is a bottleneck that you shouldn't replace - even when agents are high enough quality to do video meetings.

One-on-one meeting time with customers is something that shouldn't be automated. The systems around the meetings should be - so that front-liners spend nearly 100% of their time with customers.

REWARDING 100X IMPACT
In a world where companies are able to do so much more with less, where does that excess money go?
In our case, much of the savings in this new operating model will flow directly back to those that enabled it.

We must reward people that create productivity accordingly. This aligns incentives on both sides. Plus, in a world where your best people create 100x impact, you can't afford to lose them.

You should aim to retain these employees for decades. The context they have and their ability to efficiently orchestrate and review will be nearly impossible to replace.

Compensation bands of today should be thrown out the door. We're introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems.

THE FUTURE
Nearly every company will make changes like these. The ones that do it proactively will define what comes next.

The future is not fewer people. It's different work, new roles, and better rewards for those who embrace it. We're already seeing entirely new roles emerge, like Agent Managers, that didn't exist a year ago.

ClickUp is positioning to lead this shift, not just internally, but for our customers too. I've never been more certain about where we're headed.

[Samuel Fitoussi @SamuelFitouss10]

Quelques statistiques intéressantes sur le bilan environnemental de l'IA trouvées sur le blog du chercheur Andy Masley :

Bilan carbone de l’entraînement de Chat GPT 4 :

Entraîner GPT-4 a consommé l’énergie nécessaire à alimenter la ville de San Francisco pendant trois jours. Mais Chat GPT-4 est un produit qui a été utilisé par des centaines de millions de personnes pendant deux ans. À titre de comparaison, la fabrication des Iphones 16 a consommé l’énergie nécessaire à alimenter la ville de San Francisco pendant treize ans.

Bilan carbone de l’entraînement de Chat GPT 4 : 15 000 tonnes de CO2, soit les émissions annuelles de 1 550 citoyens américains.

C’est inférieur au bilan carbone de la fabrication des chaussures Nike vendues sur une seule journée ou à celui de la fabrication des Légos vendus sur un mois. Si l'on pense qu'il aurait été bénéfique pour la planète d'empêcher l'entraînement de GPT-4, il faudrait aussi envisager d'arrêter la production de Lego pendant un mois.

Bilan carbone de l’inférence :

Une requête ChatGPT moyenne consomme autant d'énergie qu'une recherche Google en 2008 (la dernière fois où Google a indiqué la consommation d'une recherche).

Même en incluant les « coûts cachés » comme l'entraînement, les émissions liées à la fabrication du matériel, l'énergie utilisée pour le refroidissement et les puces d'IA en veille entre les prompts, le coût carbone d'un prompt moyen représente moins de 1/150 000ᵉ des émissions quotidiennes d'un Américain moyen (0,00067 %).

La consommation d’eau :

Les data centers aux États-Unis ont consommé 0,2% de l’eau douce du pays en 2023.

L’IA ne représente que 20% de la consommation des data centers. Elle consomme donc 0,04% de l’eau douce américaine (ceci inclut la consommation d'eau pour produire l'électricité alimentant les data centers).

Il est prévu que ce chiffre triple d’ici 2030, atteignant 0,12% de la consommation américaine d’eau douce. Cela équivaudra à 8% de la consommation d’eau par l’industrie du golf aux États-Unis.

En 2030, les data centers d'IA consommeront annuellement autant d'eau que 0,07 % de la population américaine.

À l’échelle individuelle, un prompt consomme 0,2 ml d’eau (à nouveau, en incluant l’eau utilisée pour produire l’électricité utilisée par le datacenter). Quotidiennement, avant l'arrivée de l'IA, l'Américain moyen utilisait l'eau équivalente à 800 000 prompts.

Quelques équivalences consommation d’eau/prompts:

Chaussures en cuir : 4 000 000 prompts
Smartphone : 6 400 000 prompts
Jean : 5 400 000 prompts
T-shirt : 1 300 000 prompts
Une feuille de papier : 2 550 prompts
Un livre de 400 pages : 1 000 000 prompts

Chaque seconde passée à marcher dans la rue use un peu vos chaussures, qui finiront par devoir être remplacées. Or, leur fabrication nécessite de l'eau. Andy Masley calcule que chaque seconde de marche consomme en moyenne autant d'eau que 7 prompts. Rester assis devant son ordinateur permet donc d'économiser de l’eau.

Tout cela sans évoquer tous les bienfaits environnementaux qui seront apportés par l’IA (efficacité des chaînes d’approvisionnement, découvertes scientifiques, libération de ressources à investir dans le renouvelable, etc.)

[Johan Aradan @joaradan]

@libremax_off Forgeron

[Johan Aradan @joaradan]

@SakumiBLR @wittgensteinien C’est vrai mais il me semble que c’est comme ça que la Chine a fait pour sortir du communisme, en créant des exceptions qui ont très bien marché et au final sont devenues la nouvelle règle. C’est + pragmatique et efficace que réouvrir un débat théorique pour supprimer X normes

[dany @danywander]

me and @claudeai

[Geoff Charles @geoffintech]

https://t.co/CaKyQS1Fl4

[Hugo Navarro @HugoNavarroPer2]

EBITDA (2026 edition): Earnings Before Iran, Tariffs, and Donald Announcements.

[Johan Aradan @joaradan]

@QsB75 @mtwit75 Regardez les jardins d’enfants. On est dans celui du 12eme c’est super et de très bonnes structures pour les enfants

[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 😢

[Johan Aradan @joaradan]

Perfect timing. We built our product &amp; design repo inside Ornikar github 2-3 months ago and now the whole team is working on it. Product, Design and Tech teams share the same stack and process 🤞

[Aakash Gupta @aakashgupta]

Only 24% of PM candidates have a GitHub.

Every PM I placed at OpenAI, Anthropic, Meta AI last year had one.

I wrote the first guide on how to build yours:

https://t.co/RUVnhoznpP

[Johan Aradan @joaradan]

@simonecanciello Nice! I was about to build one for my own training. Is it live on the AppStore or not yet?

[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. https://t.co/tEzbkK60Ph

[Johan Aradan @joaradan]

@PEntremont 🤩

[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 🪄

[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.

[Johan Aradan @joaradan]

Les retraités*

[BFM Business @bfmbusiness]

Les Français n'y avaient plus déposé autant d'argent depuis 15 ans: l'assurance vie a engrangé des dépôts records de 50,6 milliards d'euros en 2025
https://t.co/hgz19xBUpC

[David K 🎹 @DavidKPiano]

Claude: Hey, mind if I grep -ohP "useEffect\(.*?\[\K[^\]]+" **/*.tsx 2&gt;&amp;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

[Swarthy Swabian @MuKuDk2]

Here we can see the difference between a german and a frenchman solving the same problem:

[Johan Aradan @joaradan]

Not sure this was part of Paris Climate Accords

[Polymarket @Polymarket]

JUST IN: Weight loss drugs like Ozempic on track to save U.S. airlines more than half a billion dollars in fuel costs this year.