THE RESEARCH DESK
Understand what matters.
Original analysis. Visible evidence. Practical next steps.
Your Ethereum L2 transfer says complete. Can you actually withdraw?
A practical comparison of optimistic and ZK rollups, with a worked transfer example and a worksheet for separating confirmation, settlement and usable funds.
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Prompt caching: the AI cost comparison that a token price misses
How to evaluate repeated AI workloads using Gemini's caching documentation, a worked cost example and an acceptance-based comparison method.
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Claude, OpenAI, Gemini or Kimi for coding? Choose the workflow first.
A practical four-way shortlist: repository agents, API building blocks, operating costs and a repeatable test you can run on your own code.
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NVIDIA’s growth is spectacular. The harder question is what customers earn from it.
Beyond the revenue headline: a framework for following deployment, utilisation and the economics of AI infrastructure.
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More stablecoins do not automatically mean more real-world payments.
How to read supply, reserves and transfer activity without confusing liquidity with adoption.
Read the analysis →The next AI-agent test: what can it do, and what can it touch?
Why a capable model needs a carefully designed operating environment—and how to evaluate one without being an engineer.
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