Under the Hood
Engineering
How we build the infrastructure that makes AI remember. Architecture decisions, system design, and hard problems.
Engineering
Context vs. Context Window The AI industry has a language problem. When OpenAI, Anthropic, Perplexity, and Mem0 talk about "memory" and "context," they're almost always talking about the context window — the temporary buffer of tokens a model can see during a single inference pass. Make the buffer bigger, store some facts between sessions, retrieve relevant snippets before generating a response. That's the playbook.
The AI Brain Research Team·
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Case Studies
When the Model Isn't Enough: How a Context Layer Transformed Newsroom Intelligence The AI industry obsesses over which model is best. We ran an experiment that suggests that's the wrong question entirely. When we gave Claude — one of the most capable models available — a complex geopolitical research question three ways, the results had almost nothing to do with model capability. They had everything to do with context. Here's what happened
Raakin Iqbal·
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Engineering
When Context Collapses: What a Geopolitical Crisis Revealed About AI's Missing Layer During the Iran-US crisis, our AI system merged a school strike, an oil analysis, and a Messi controversy into a single event — because they all mentioned Iran. What broke taught us more than what worked
The AI Brain Research Team·
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Engineering
Unboxing the AI Pandora Box: Introducing the AI Audit Panel Advancing transparency, verification, and human collaboration in enterprise AI
The AI Brain Research Team·
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