How models learn semantic relationships in language

The survival of your AI app depends on your token economics

The Invisible Tax of AI Tokenization: Why Non-English Speakers Pay More

How your prompt becomes vectors, attention, and text in milliseconds

How words find their place in semantic space through push, pull, and careful trade-offs

How a simple observation about language created modern AI's understanding of meaning

The 35-year engineering journey that turned a linguistic insight into AI's foundation

How I stopped seeing vectors as magic and started seeing them as the geometry of meaning itself.

Should you build a custom tokenizer? A production decision framework

Why Swahili speakers pay 1.8x more than English speakers—and how to fix it

From GPT to BERT to T5 - the algorithms that learned to speak 100 languages

How the invisible step before training shapes model intelligence, costs, and fairness.

Uncover the sources of cache inconsistency, its impacts, and hands-on strategies to measure and mitigate it for reliable systems.

Uncover the sources of cache inconsistency, its impacts, and hands-on strategies to measure and mitigate it for reliable systems.

Keeping Your Cache Lean and Mean

Caching Fundamentals and Core Patterns

Exporting B-Tree Wisdom to Caches, Queues, and Distributed Architectures for Real-World Wins

Databases don’t just store data in B-Trees - they update them concurrently at massive scale.

Every byte you leave empty, every split you delay, and every page-size decision trades space, latency, and bandwidth - here’s how to choose.

The Hidden Design Principle That Makes B-Trees Endure