Deep technical write-ups, architecture breakdowns, and lessons from real engagements.
A demo that works in a notebook is not a product. LLM applications fail in ways traditional software does not: outputs are non-deterministic, quality is subjective, costs scale with usage, and a…
A large language model is a context engine: the quality of what comes out is bounded by the quality of what you put in. Most bad AI output is not a model failure, it is a context failure. Here is how…
AI is a power tool, not a teammate. Power tools are fantastic when you respect their edges and dangerous when you pretend they do not have any. For platform work, the line is surprisingly clear.…
Most ML incidents are not modeling problems, they are deployment problems. Here is a boring, repeatable path from notebook to production. Train reproducibly Pin everything and log the run. If you…
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