Jonathan Pedoeem

Swapping out Determinism for Assumption-Guided UX

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

Lawyers in the Loop: How Midpage Uses PromptLayer to Evaluate and Fine-Tune Legal AI Models

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

How NoRedInk Used PromptLayer Evals to Deliver 1M+ Trustworthy Student Grades

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

2025 State of AI Engineering Survey: Key Insights from the AI Engineer World Fair

The 2025 State of AI Engineering Survey by Barr Yaron from Amplify Partners offers a comprehensive snapshot of how engineering teams are building, managing, and scaling LLM-powered applications in production. With responses from 500 practitioners, the survey reveals critical insights about the rapid pace of model and prompt iteration, the

Production Traffic Is the Key to Prompt Engineering

Let's be honest—you can tinker with prompts in a sandbox all day, but prompt quality plateaus quickly when you're working in isolation. The uncomfortable truth is that only real users surface the edge cases that actually matter. And here's the kicker: the LLM

How Magid built enterprise-grade AI agents for content creation with PromptLayer

Executive Summary * AI at production scale: Magid's Collaborator suite now handles thousands of newsroom stories/day with all agents orchestrated on PromptLayer. * Efficiency gains: Early stations report 2–6 FTEs of capacity unlocked per newsroom; half of their top-read web stories become AI-assisted. * Rapid adoption: 8/10 journalists

AI Sales Engineering: How We Built Hyper-Personalized Email Campaigns at PromptLayer

TL;DR Our AI sales system automates hyper-personalized email campaigns by researching leads, scoring their fit, drafting tailored four-email sequences, and integrating seamlessly with HubSpot. With this approach, we achieve: * ~7% positive reply rate, resulting in way more meetings than we can handle * 50–60% email open rates The key

Using AI as a Content Writer: How Not to Get Left Behind

There are two schools of thought emerging in the AI space right now. The first is pessimistic: "AI is coming, it's going to be our new God, everything's going to be gone, we're not going to be able to work anymore." The

How to Evaluate LLM Prompts Beyond Simple Use Cases

A common question we get is: "How can I evaluate my LLM application?" Teams often push off this question because there is not a clear answer or tool for them to use to address this challenge. If you're doing classification or something that is programmatic like

Swapping out Determinism for Assumption-Guided UX

Lawyers in the Loop: How Midpage Uses PromptLayer to Evaluate and Fine-Tune Legal AI Models

How NoRedInk Used PromptLayer Evals to Deliver 1M+ Trustworthy Student Grades

2025 State of AI Engineering Survey: Key Insights from the AI Engineer World Fair

Production Traffic Is the Key to Prompt Engineering

How Magid built enterprise-grade AI agents for content creation with PromptLayer

AI Sales Engineering: How We Built Hyper-Personalized Email Campaigns at PromptLayer

Using AI as a Content Writer: How Not to Get Left Behind

How to Evaluate LLM Prompts Beyond Simple Use Cases

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