Field notes on practical AI adoption.
Writing about data readiness, privacy tradeoffs, and the real-world decisions that separate AI pilots that stick from the ones that stall.
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The Hidden Bottleneck Slowing Down Every AI Workflow: Local Files
Cloud-integrated AI assistants have transformed professional workflows — but only for documents stored in the cloud. Here's why local files are still the bottleneck, and what to do about it.
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Document AI That Actually Works? Start With Data Readiness
Model sophistication and prompt quality get all the attention. In document-heavy workflows, the real determinant of success is upstream — data quality, organization, and access governance.
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AI Tool Evaluation, Through the Lens of Data Privacy
When AI touches your data, "what happens to it?" is rarely a simple question. A four-step framework for evaluating tools that fits the realities of SMBs and regulated organizations.
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Don't Get Left Behind: How SMBs Can Adopt AI Tools That Make an Impact
Privacy concerns, cost, complexity, decision paralysis — the barriers are real. But SMBs hold structural advantages that let them adopt AI faster than the enterprises they compete with.
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