AI in NLP didn’t begin with products.
It began with papers.

Pre-training + transformers showed that one model can learn language once and adapt everywhere.
That idea still powers LLMs, search, and RAG today.

Read the research. Build better systems.

AI in NLP didn’t begin with products.
It began with papers.

Pre-training + transformers showed that one model can learn language once and adapt everywhere.
That idea still powers LLMs, search, and RAG today.

Read the research. Build better systems.

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programming is just the art of adding bugs to an empty file

So what do i do now?

Built this visual to capture a simple idea:
Old databases learned new tricks.
pgvector turns Postgres into an AI-native system.
If you’re building search, RAG, or recommendations —
this belongs in your toolbox.
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The engineers who win won't write the most code. They'll orchestrate systems where AI, automation, and humans work seamlessly together.

2026 = stop chasing AI hype. Start shipping AI that works.

• AI writes a lot of the code now
• Real skill = directing systems, not typing
• Rust is default for secure systems
• Git is your infrastructure
• Agentic AI is hot, but prod-ready is hard

Winners orchestrate.
Losers chase models.

2026 is the year we stop chasing AI headlines and start shipping AI that actually works