Muntasir Ahmad Chowdhury 
AI in ecommerce is most valuable when businesses automate the right decisions rather than every decision. This practical framework shows what to automate, what to keep human-controlled, and how to build an AI-ready store.
ChatGPT, Claude, and Gemini behave very differently once a workflow depends on long system prompts, structured output, or holding a persona over many turns. Here’s which platform actually wins for prompt-heavy work.
AI prompt libraries and marketplaces are splitting into free native tools, community libraries, and a shrinking set of paid marketplaces worth their price. Here’s how to tell which category actually fits your need, using a two-part buy-or-build framework instead of a feature checklist.
Prompt management software went through more consolidation in 2026 than almost any other AI infrastructure category, with Humanloop shutting down and Helicone and Langfuse both changing owners. Here’s how to pick a tool that actually fits your team, using a repeatable scoring framework instead of a feature checklist.
Bigger context windows don’t solve long-document AI tasks on their own. Learn six real compression techniques — truncation, extractive and abstractive summarization, hierarchical map-reduce, semantic retrieval, and token-level compression — and how to pick the right one without losing what your task actually needs.
Role prompting can sharpen an AI’s tone and audience fit, but the research shows it often does nothing for accuracy and can even raise bias and safety risks. Here’s what the evidence actually says, plus a framework for deciding when to use it and how to test whether a persona is really helping.
Reliable JSON extraction from LLMs is a stack, not a single prompt trick. Learn the four layers — schema design, JSON mode, native structured outputs, and validation — and which one your task actually needs.
A 4-part system prompt structure, the research on why shorter prompts often work better, and real leak/injection risks most guides skip.
Few-shot and zero-shot prompting solve different problems. Here is a practical framework for choosing the right one, backed by the latest research on in-context learning.
Why “context engineering” replaced prompt engineering, the research on why more context can make AI worse, and a 3-check framework to fix it.