- Published on
Memory, state, and skills solve different problems in AI systems. Blurring them leads to muddled architecture, confusing product behavior, and weaker workflows.
Hi, I'm Ankush Patel
I write about AI engineering, product thinking, and the systems behind reliable software. If you're building with AI or just curious about what actually works in practice, you're in the right place 🚀
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→The Missing Layer in Your AI Stack: Intermediate Knowledge
Why intermediate representations are critical for practical AI systems.
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→The MLOps Engineer: Bridging ML and Product
A practical look at shipping reliable machine learning in production.
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→Accelerating Your Python Projects with Poetry
A lightweight guide to dependency management and reproducible workflows.
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Memory helps only after a workflow is clear and reliable. Otherwise it preserves inconsistency and makes a shaky AI system harder to understand.
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