Building the First LLM Search Engine
In this episode, we sit down with Michael Royzen, CEO and co-founder of Phind. Michael shares insights from his journey in building the first LLM-based search engine for developers, the challenges of creating reliable AI models, and his vision for how AI will transform the work of developers in the near future.
![Building the First LLM Search Engine](/blog/building-the-first-llm-search-engine/thumbnail-10.png)
The Contrarian's Guide to AI
Jason Liu is a true Renaissance man in the world of AI. In this episode, we cut through the AI hype explore effective strategies for building valuable AI products.
![The Contrarian's Guide to AI](/blog/contrarian-guide-to-ai/thumbnail-9.png)
What is beyond OpenAI?
Logan led developer relations at OpenAI before leading product on the Google AI Studio. He's been closer than anyone to developers building with LLMs and has seen behind the curtain at two frontier labs. In this week’s episode of the High Agency Podcast, Logan and I discuss the future trajectory of AI and share our insights on what AI builders can anticipate in the future.
![What is beyond OpenAI?](/blog/what-is-beyond-open-ai/thumbnail-8.png)
What is an AI Engineer?
In this week’s episode of the High Agency Podcast, I had the pleasure of interviewing Shawn Wang, better known as Swyx. As the author of the influential essay "Rise of the AI Engineer," Swyx is at the forefront of defining the evolving field of AI engineering. We discuss the emergence of the AI engineer, the skills required and the optimal make-up of an AI team.
![What is an AI Engineer?](/blog/what-is-an-AI-Engineer/thumbnail.png)
Building Reliable Agents with Ironclad
Over 50% of contracts at Ironclad are now negotiated by AI. I sat with Cai Gogwilt, Co-founder and Chief Architect to understand what lessons product leaders can take from their success of building AI Agents.
![Building Reliable Agents with Ironclad](/blog/building-agents-with-ironclad/cai-thumbnail.png)
Evaluating LLM Applications
An overview of evaluating LLM applications. The emerging evaluation framework, parallels to traditional software testing and some guidance on best practices.
![Evaluating LLM Applications](/blog/evaluating-llm-apps/EvalLLMAppsThumbnail2.png)
How to Maximize LLM Performance
An overview of the techniques that OpenAI recommends to get the best performance of your LLM applications. Covering best-practices in prompt engineering, retrieval-augmented generation (RAG) and fine-tuning.
![How to Maximize LLM Performance](/blog/optimizing-llms/landscape2.jpg)
Prompt Engineering 101
In this post, we'll explore the fundamentals of prompt engineering. We'll explain how Large Language Models (LLMs) interpret prompts to generate outputs, and provide tips and tricks to get you started prototyping and implementing LLMs quickly.
![Prompt Engineering 101](/blog/prompt-engineering-101/cover2.png)
How to Improve GPT‑3 with Human Feedback
Fine-tuning GPT‑3 can make it faster, cheaper and more accurate. Humanloop makes it dramatically easier to do this, while aligning the model with the preferences of your users.
![How to Improve GPT‑3 with Human Feedback](/blog/improving-gpt-3/improving-gpt-3@2x.png)