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#promptengineering

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AAlexmolalex.hashnode.devOct 1 · 9 min read

A Simple Text Skill to Address AI Arithmetic Errors

Can an ordinary free chat handle a task that requires both understanding the problem and working carefully through a sequence of calculations? That was the practical question I wanted to explore. We d

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XAXccelera AIxccelera.hashnode.devOct 1 · 7 min read

Prompt Chains Worked. Until They Didn't: Why Engineering Teams Are Moving to Agent Systems

Teams that built their first artificial intelligence (AI) features as chains of large language model (LLM) calls now hit a wall. Prompt chaining vs AI agents is a production question, not a research d

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TBTanushree Borasecodejoy.hashnode.devOct 1 · 15 min read

From Prompt Engineering to Loop Engineering

For the past few years, developers have been learning how to talk to AI better. Write a better prompt. Give better context. Add constraints. Ask for reasoning. Provide examples. Refine the prompt when

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SBShraddha bhataiinsights1909.hashnode.devSep 30 · 6 min read

𝗧𝗵𝗲 𝗦𝗵𝗶𝗳𝘁 𝘁𝗼 𝗔𝗹𝘄𝗮𝘆𝘀-𝗢𝗻 𝗔𝗴𝗲𝗻𝘁𝘀: 𝗜𝗻𝘀𝗶𝗱𝗲 𝗢𝗽𝗲𝗻𝗔𝗜'𝘀 '𝗗𝗼𝘁𝘀' 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗜𝗻-𝗖𝗵𝗮𝘁 𝗔𝗽𝗽 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺

• 𝗢𝗽𝗲𝗻𝗔𝗜 𝘂𝗻𝘃𝗲𝗶𝗹𝗲𝗱 '𝗗𝗼𝘁𝘀' 𝗮𝘁 𝗗𝗲𝘃 𝗗𝗮𝘆: Persistent, always-on AI assistants featuring customizable avatars built for ongoing background execution. • 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝗮𝘀 𝗮𝗻 𝗮�

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MBMadhav Bhasinblog.madhav.devSep 29 · 6 min read

Prompt Versioning and Cost Control: Running LLMs Responsibly in Production

The monthly bill was ten times the estimate. Investigation took two hours. Three things were wrong. A retry loop was calling the model on every validation error — including schema mismatches that woul

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SBShraddha bhataiinsights1909.hashnode.devSep 28 · 5 min read

Platform Gatekeepers vs Autonomous Shopping: What Amazon Blocking Meta Muse Teaches Developers

TL;DR: Amazon blocked Meta Muse just 12 days post-launch over credential handling and identity obfuscation, signaling a major shift in how e-commerce platforms police autonomous consumer agents. Auton

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SBShraddha bhataiinsights1909.hashnode.devSep 26 · 10 min read

CO-STAR: A Deep Dive Into the Prompt Framework That Fixes Vague AI Outputs

Introduction: the prompt is the interface Every developer has had this experience: you type a quick, half-formed prompt into an LLM, get back something mediocre, and conclude the model "isn't that goo

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GGeekyAntstechblog.geekyants.comSep 23 · 16 min read

How To Build AI Chatbots Using ChatGPT API - With Live Demo Video

Editor's Note: This article was originally written by Priyamvada and published in March, 2024. It was revised and updated by Shivangi Agarwal in July, 2026 to include current technologies, implementat

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NSNagappan Snagspidey.hashnode.devSep 22 · 8 min read

Fine-Tuning vs. Prompting: When Do You Actually Need to Fine-Tune?

A team I know spent two weeks and a few hundred dollars fine-tuning a model to get their internal support bot to answer in a consistent, on-brand tone. They collected examples, cleaned them up, ran th

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KKhaskykhasky.hashnode.devSep 21 · 4 min read

Emphasis Is a Budget and Most Agent Files Have Spent It

Most people assume a model weights a bold line more heavily. It is an easy assumption to arrive at, because bold works on the person and the model is handed the same page 🙈 It does not inherit the re

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#promptengineering

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#promptengineering

Explore Hashnode

Trending tags this week

A Simple Text Skill to Address AI Arithmetic Errors

Prompt Chains Worked. Until They Didn't: Why Engineering Teams Are Moving to Agent Systems

From Prompt Engineering to Loop Engineering

𝗧𝗵𝗲 𝗦𝗵𝗶𝗳𝘁 𝘁𝗼 𝗔𝗹𝘄𝗮𝘆𝘀-𝗢𝗻 𝗔𝗴𝗲𝗻𝘁𝘀: 𝗜𝗻𝘀𝗶𝗱𝗲 𝗢𝗽𝗲𝗻𝗔𝗜'𝘀 '𝗗𝗼𝘁𝘀' 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗜𝗻-𝗖𝗵𝗮𝘁 𝗔𝗽𝗽 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺

Prompt Versioning and Cost Control: Running LLMs Responsibly in Production

Platform Gatekeepers vs Autonomous Shopping: What Amazon Blocking Meta Muse Teaches Developers

CO-STAR: A Deep Dive Into the Prompt Framework That Fixes Vague AI Outputs

How To Build AI Chatbots Using ChatGPT API - With Live Demo Video

Fine-Tuning vs. Prompting: When Do You Actually Need to Fine-Tune?

Emphasis Is a Budget and Most Agent Files Have Spent It