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Pitrat on AI Research (1997)
Building Solutions to Understand Problems
While preparing my HDR mémoire in 2013, I discovered Jacques Pitrat’s 1997 paper “Comment faire de la recherche en intelligence artificielle” buried in the LAFORIA archives (now LIP6). It was a .doc file from another era of AI research. I’m grateful I saved a copy—it seems lost to the internet now, yet its insights still feel to me.
Zen and the Art of Vibe-Coding
How AI-assisted coding eliminates the contemplative pauses between architecture and implementation—and whether beginners can still build expertise without that rhythm.
Computational Thinking
Frameworks from research and expert practice
Computational Thinking encompasses the practices and knowledge involved in designing computer technologies. It bridges two domains: pedagogy (how we teach programming and computer science) and expert practice (how experienced developers actually design software).
Agent Coin
Autonomous AI Economic Transactions
AI agents need to transact—research agents buying API access, creative agents selling content, agents grounded in expert content monetizing their expertise—but every payment requires manual configuration and human approval. Give agents wallets so they can pay each other directly, autonomously. Coinbase’s Payments MCP could already provide the infrastructure.
Let the Agents Do the Talking
Why should AI screen AI-generated resumes?
On one hand, candidates use AI agents to tailor their resumes for recruiters. On the other hand, recruiters use AI agents to screen those AI-generated resumes. So, why have a resume at all? Let the agents talk directly.
Idea Cards NFT
Monetizing Creative Concepts as NFTs
Most ideas die in notebooks while others search desperately for starting points. Sell your unused concepts as NFTs with clear licensing—turn dormant intellectual property into income, build your reputation as an idea generator, and potentially earn royalties when they succeed.