Explainers that stay current
Short, plain-English guides to the ideas behind the news. Each is revisited when the facts change.
For executives
Executives brief →
Flagship, mid-tier, small: which AI model tier should you actually use?
Every vendor sells three or four sizes. How to match tier to task, and why most production traffic belongs on the middle one.…
LLM API pricing explained: tokens, caching, batch and the cliffs
How per-million-token pricing works, why output costs more, and the four levers that cut a bill by half or more.…
Open-weight vs closed AI models: what the difference means for you
Open-weight models can be downloaded and run anywhere; closed models live behind an API. The trade-offs on cost, control, capabili…
Prompt injection explained: the attack every AI agent is exposed to
Why text that an AI reads can hijack what it does, why there is no complete fix, and the controls that actually reduce the damage.…
RAG explained for business leaders
Retrieval-augmented generation is how companies make a general model answer from their own documents without retraining it. What i…
What is an AI agent? A plain-English explanation
An agent is AI that takes actions, not just answers. Here is what that means, why every company is suddenly announcing one, and wh…
For finance
Finance brief →
How to read an AI benchmark without being fooled
Vendor charts always show the vendor winning. The handful of questions that separate a meaningful result from marketing.…
LLM API pricing explained: tokens, caching, batch and the cliffs
How per-million-token pricing works, why output costs more, and the four levers that cut a bill by half or more.…
RAG explained for business leaders
Retrieval-augmented generation is how companies make a general model answer from their own documents without retraining it. What i…
For security
Security brief →Open-weight vs closed AI models: what the difference means for you
Open-weight models can be downloaded and run anywhere; closed models live behind an API. The trade-offs on cost, control, capabili…
Prompt injection explained: the attack every AI agent is exposed to
Why text that an AI reads can hijack what it does, why there is no complete fix, and the controls that actually reduce the damage.…
For ml engineers
ML engineers brief →How to read an AI benchmark without being fooled
Vendor charts always show the vendor winning. The handful of questions that separate a meaningful result from marketing.…
Open-weight vs closed AI models: what the difference means for you
Open-weight models can be downloaded and run anywhere; closed models live behind an API. The trade-offs on cost, control, capabili…
What is a context window, and does a million tokens matter?
The context window is how much a model can read at once. Why it grew from 4K to 1M tokens, what it costs, and when it actually hel…
For developers
Developers brief →Flagship, mid-tier, small: which AI model tier should you actually use?
Every vendor sells three or four sizes. How to match tier to task, and why most production traffic belongs on the middle one.…
How to read an AI benchmark without being fooled
Vendor charts always show the vendor winning. The handful of questions that separate a meaningful result from marketing.…
LLM API pricing explained: tokens, caching, batch and the cliffs
How per-million-token pricing works, why output costs more, and the four levers that cut a bill by half or more.…
Prompt injection explained: the attack every AI agent is exposed to
Why text that an AI reads can hijack what it does, why there is no complete fix, and the controls that actually reduce the damage.…
What is a context window, and does a million tokens matter?
The context window is how much a model can read at once. Why it grew from 4K to 1M tokens, what it costs, and when it actually hel…
What is an AI agent? A plain-English explanation
An agent is AI that takes actions, not just answers. Here is what that means, why every company is suddenly announcing one, and wh…
For beginners
Beginners brief →Flagship, mid-tier, small: which AI model tier should you actually use?
Every vendor sells three or four sizes. How to match tier to task, and why most production traffic belongs on the middle one.…
Open-weight vs closed AI models: what the difference means for you
Open-weight models can be downloaded and run anywhere; closed models live behind an API. The trade-offs on cost, control, capabili…
RAG explained for business leaders
Retrieval-augmented generation is how companies make a general model answer from their own documents without retraining it. What i…
What is a context window, and does a million tokens matter?
The context window is how much a model can read at once. Why it grew from 4K to 1M tokens, what it costs, and when it actually hel…
What is an AI agent? A plain-English explanation
An agent is AI that takes actions, not just answers. Here is what that means, why every company is suddenly announcing one, and wh…
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