The Mono Summer Internship Programme is back! 🥳💙
We’re now accepting applications for different roles across our Engineering, Business, HR, Legal, and Product teams.
If you’d like to spend the next three months, learning how API products are built at Mono and do really meaningful work, please send in your applications here: https://t.co/5bvFlOtxpC
https://t.co/uNXS9jEgpg is Next.js for agents.
I built Next with a simple premise: 𝚙𝚊𝚐𝚎𝚜/𝚒𝚗𝚍𝚎𝚡.𝚓𝚜 is all you need. Put some React in there and you’re good to go.
Eve asks for even less. 𝚊𝚐𝚎𝚗𝚝/𝚒𝚗𝚜𝚝𝚛𝚞𝚌𝚝𝚒𝚘𝚗𝚜.𝚖𝚍. Put some English in there and you’re good to go.
Like Next, it embraces the filesystem. You can guess what 𝚝𝚘𝚘𝚕𝚜/𝚚𝚞𝚎𝚛𝚢-𝚍𝚋.𝚝𝚜 does. An agent is just a directory, whose entire spec fits in the tweet below.
And like Next on Vercel, it’s seamless to deploy. The infra, like Sandbox, Gateway, Workflow… is the output of your creation.
It’s never been easier to design your dream house.
Draw a shape. Define your rooms. Set your constraints.
@DraftedAI generates complete floor plans, elevations, and 3D home designs in seconds.
Over the last month, 120,000 people generated 325,000+ home designs with https://t.co/XqC0LP5n3y.
A List Of Things Always Worth Chasing
Joy. Purpose. That inkling you could be doing something more with your life. Kindness. Compassion. A better tomorrow. Platonic soulmates. Places that remind you of home. The little things and the grand things, too. Burning desire. Ideas so crazily absurd they just might work. The bigger picture. Dreams. Connection with God. Your intuition.
Good conversation. New perspectives. Mindset shifts. Accountability. Your north star. Yourself. Your work. Your art. Your family, chosen or otherwise. Something to believe in. Someone to fight for. Anything that makes you feel glad to exist right here, right now.
if software is spec, what if we got AI to make specs that weren't slop?
working on this
(very inspired by the beauty of https://t.co/Ay6AdyvOm8 by @danhollick)
Yann LeCun closed $1.03B for AMI Labs on March 10. Three days later, this paper dropped from his NYU collaborators.
15M parameters. Single GPU. A few hours of training.
LeWorldModel is the first JEPA that trains end-to-end from raw pixels. Two loss terms: predict the next embedding, keep the latent space Gaussian. Previous JEPAs needed exponential moving averages or pretrained encoders to avoid representation collapse. LeWM doesn't.
Six hyperparameters down to one.
The numbers are the story. Foundation-model-based world models require hundreds of millions of parameters and serious compute to plan a control task. LeWM plans up to 48x faster while staying competitive on 2D and 3D benchmarks. The whole thing fits on a laptop GPU.
Look at the trajectory. Yann announced his Meta departure in November 2025 after 12 years and called founding FAIR his "proudest non-technical accomplishment." On March 10, 2026, AMI Labs closed the largest seed round in European history at a $3.5B pre-money valuation. Bezos, Nvidia, Samsung, and Toyota all wrote checks.
Three days later: a paper showing that JEPA-from-pixels is no longer fragile and no longer compute-heavy. The engineering scaffolding that made it look like an academic curiosity is gone.
The authors sit at Mila, NYU, Samsung SAIL, and Brown. None at Meta.
Yann's bet was that the path to machine intelligence runs through world models, not language models. He left a public company to build it. Each JEPA paper from his network resets the assumed cost structure for that bet. This one makes world modeling laptop-cheap.
Meta still has the GPUs. The architecture left.
At the start of 2026, Sycamore had 25 open roles out of a team of 170: about 15% vacancies. Moniepoint’s reported 500 vacancies out of 3,500 people? Roughly 14%. Our realities aren’t that different (relatively speaking).
In this weekend’s article, I explore the deeper forces shaping Nigeria’s talent gap and the Talent Constraint Matrix I coined that shows what we can actually do about them.
Enjoy!
https://t.co/R7djLgFzPU
Couldn't keep my midnight learning streak. I had to switch to learning at every free time I have during the day.
Learnt to develop LLM applications(and agents) using LangChain, prompting, LCEL, RAG, LangGraph, and Vector Databases.
#AIEngineering#Langchain
We’ve raised 25M to build the world’s first Personal Intelligence.
Introducing Vellum: AI that belongs to you.
My assistant @ash_vellum has his own X (like grok), tag him and he'll answer.