Honeycomb + Google Gemini
Today at Google Next, Charity Majors demonstrated how to use Honeycomb to find unexpected problems in our generative AI integration. Software components that integrate with...
Three Properties of Data to Make LLMs Awesome
Back in May 2023, I helped launch my first bona fide feature that uses LLMs in production. It was difficult in lots of different ways,...
Using Honeycomb for LLM Application Development
Ever since we launched Query Assistant last June, we’ve learned a lot about working with—and improving—Large Language Models (LLMs) in production with Honeycomb. Today, we’re...
Effortless Engineering: Quick Tips for Crafting Prompts
Large Language Models (LLMs) are all the rage in software development, and for good reason: they provide crucial opportunities to positively enhance our software. At...
So We Shipped an AI Product. Did it Work?
Like many companies, earlier this year we saw an opportunity with LLMs and quickly (but thoughtfully) started building a capability. About a month later, we...
LLMs Demand Observability-Driven Development
Many software engineers are encountering LLMs for the very first time, while many ML engineers are being exposed directly to production systems for the very...
Improving LLMs in Production With Observability
In early May, we released the first version of our new natural language querying interface, Query Assistant. We also talked a lot about the hard...
All the Hard Stuff Nobody Talks About when Building Products with LLMs
There’s a lot of hype around AI, and in particular, Large Language Models (LLMs). To be blunt, a lot of that hype is just some...