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If 2026 is the year of AI, it's also the year to read more papers. LLMs make writing code cheaper. This places greater emphasis on architectural choices, understanding design tradeoffs, ensuring security, and building things people actually need. Great example: yesterday I read the Dynamo paper.

Though it was published in 2007 (nearly 20 years ago!) it was revolutionary in its day, and an example of how already-known technologies can be combined to make something new and extremely successful.

Merkle trees, consistent hashing, vector clocks, gossip protocols, and quorum algorithms were all previously known and had been used to build other software. But their unique combination to build Dynamo worked super well for Amazon's use-case, and helped them to scale to millions of DAU.