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Part 4 – AI & AppReviews This is part 4 of my series on AppReviewshttps://apprevie.ws/. - Part 1: From “I should check the reviews” to a SaaShttps://dev.to/que...
Overview The deployment of Large Language Models LLMs in production has shifted the bottleneck of software engineering from code syntax to data quality. - In t...
Why Prompt Engineering Matters Now Whether it’s Microsoft 365 Copilot, ChatGPT, Claude, or GitHub Copilot, AI tools can only produce good results if the user k...
For the last few years, the AI industry has been fixated on scale—bigger models, more parameters, longer context windows. That focus made sense for a while, but...
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Mastering Prompt Engineering Patterns for Production Apps Have you ever built an AI feature that works great in testing but falls apart in the real world? It's...
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The uncomfortable truth about GPT-5.2 GPT‑5.2 doesn’t fail because it’s weak. It fails because most people prompt it like it’s still 2023. I went through the o...
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For the last two years, the fundamental unit of generative AI development has been the 'completion.' You send a text prompt to a model, it sends text back, and...
Purpose of This Document This document records the historical context, architectural motivations, and rationale behind the design decisions of FACET. It exists...
