An LLM idiom is a pattern or format that models understand implicitly - things their neural nets have built logic and world models around, without needing explanation. These are the native languages of AI systems. To me, this is one of the most important concepts in prompt engineering. I don&
From tedious manual work to comprehensive automated analysis in one afternoon 0:00 /2:41 1× If you're like me, you probably dread writing those monthly product update emails. You know the ones – where you have to comb through dozens (or hundreds) of commits across multiple repositories, trying
HumanLoop is shutting down on September 8, 2025. If you're among the many teams who relied on HumanLoop for prompt management, evaluations, and observability, you need to act fast. The good news? PromptLayer offers everything HumanLoop did—and more. What is PromptLayer? PromptLayer is a comprehensive prompt engineering
Context Rot: How modern LLMs quietly degrade with longer prompts — and what you can do about it Context Rot: What Every Developer Needs to Know About LLM Long-Context Performance How modern LLMs quietly degrade with longer prompts — and what you can do about it If you've been stuffing
So you need a team to build an LLM multi-agent system... how do you interview candidates? I'll try to provide some ideas and strategies in this article. Firstly... What is an AI Engineer? AI engineers build the future. They create scalable AI systems and agents. They test, evaluate,
The term "prompt engineering" really exploded when ChatGPT launched in late 2022. It started as simple tricks to get better responses from AI. Add "please" and "thank you." Create elaborate role-playing scenarios. The typical optimization patterns we all tried. As I've written
Building conversational AI agents is hard. Ensuring they perform reliably across diverse scenarios is even harder. When your agent needs to handle multi-turn conversations, maintain context, and achieve specific goals, traditional single-prompt evaluation methods fall short. In this guide, I'll walk you through best practices for evaluating conversational
Most companies are drowning in data but sending generic outreach that makes you want to hit unsubscribe. This SaaS unicorn with a 100+ person sales team figured out how to use PromptLayer to auto-craft millions of fully-personalized outbound emails at roughly $0.002 each, while keeping both engineers and marketers
A growth marketing startup specializing in e-commerce faced a significant challenge: personalizing cold outreach at massive scale—covering over 30,000 domains and 90,000 contacts—without excessive copywriting costs. The challenge was compounded by fragmented data sources—including website scraping data, SMS messaging frequency, tech stack details, and funding
The real innovation that separates post-ChatGPT UX from pre-ChatGPT UX isn't about chatbots. It's not about intelligence or even about AI thinking through and reasoning. It's about assumptions. In traditional software, users must explicitly provide every piece of information the system needs, but AI-powered
For two years, Midpage has used PromptLayer to transform how they build legal AI, putting lawyers next to engineers to own prompt quality. Their approach has scaled from manual tracking in Notion to automated evaluation pipelines that catch regressions before they reach users. * 80 production prompts across 10 AI features
NoRedInk has been on a mission to unlock every writer's potential since 2012. Today, their adaptive writing platform serves 60% of U.S. school districts and millions of students worldwide. But when they decided to build an AI grading assistant, they faced a challenge that many EdTech companies