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
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
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
When you're having trouble getting one prompt to work, try splitting it up into 2, 3, or 10 different prompt workflows. When prompts work together to solve a complex problem, that's an AI agent. What Are AI Agents and What Are They Used For AI agents
"Evals are your company's intellectual property" - Alexander Bricken at AI Engineer Summit I recently attended Anthropic's talk at AI Engineer Summit, and it offered fascinating insights into how one of the leading AI companies thinks about building robust AI systems. Here are my
OpenAI's Model Spec tells us a lot about how the company thinks about prompt engineering. Let's explore it and see how to use it in your daily prompting. The Three-Layer Approach The Model Spec uses three layers: objectives, rules, and defaults. This structure makes prompts more
As AI models become increasingly sophisticated, there's a growing narrative that prompt engineering – the art and science of instructing large language models – will soon become obsolete. As models get better at understanding natural language, will the need for carefully crafted prompts will disappear? The death of prompt engineering
Software development is being fundamentally reshaped by AI, but the biggest challenge isn't technical expertise – it's domain knowledge. The next generation of AI products will be built by doctors, lawyers, and educators, not just machine learning engineers. We're excited to announce that PromptLayer has
Here's my take on where AI is headed and why subject matter experts, not ML engineers, will be the ones building the next generation of AI applications. Most of this comes from the podcast above. The Big Picture One of the main predictions I base a lot of
My technically curious dad just asked if Deepseek is a game changer. It's a fair question that gets at the heart of what's happening in AI right now. What's Really Going On Deepseek is good. They've built the best open-source model out
What we can learn from o1 models and "Thinking Claude" The AI landscape has shifted dramatically. We now have access to both "smart" and "dumb" models, where smart model families o1 take time to think and reason before answering. But here's where
As language models evolve, their context windows keep getting longer and longer. This evolution is challenging our assumptions about how we should feed information to these models. Enter Cache-Augmented Generation (CAG), a new approach that's making waves in the AI community. What is CAG? Cache-Augmented Generation loads all