Artificial Intelligence Software Software Development 
TechEmpower SaaS
NOVEMBER 13, 2023
On a different project, we’d just used a Large Language Model (LLM) - in this case OpenAI’s GPT - to provide users with pre-filled text boxes, with content based on choices they’d previously made. This gives Mark more control over the process, without requiring him to write much, and gives the LLM more to work with.
Tom Tunguz
NOVEMBER 8, 2023
LLMs Transform the Stack : Large language models transform data in many ways. If you’re curious about the evolution of the LLM stack or the requirements to build a product with LLMs, please see Theory’s series on the topic here called From Model to Machine.
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How To Buy Saas
MAY 27, 2025
Artificial intelligence is everywhere from smart content generators to coding assistants and its changing how SaaS products are built and marketed. Terms like Large Language Model (LLM) and AI tool often get tossed around interchangeably, but they arent the same thing. and What is LLM orchestration?.
SaaStr
JUNE 14, 2023
“The fastest company will always win,” says Daniel Dines, CEO and Founder of UiPath, one of the fastest-growing software companies in the world. Ten years ago, no one would have guessed Europe would generate the largest software IPO globally, yet UiPath has done it, and net retention is 144%.
Tom Tunguz
JULY 30, 2020
Each team, using their data systems, develops their proprietary data products: analyses, dashboards, machine learning systems, even new product features. Data engineers stand on the shoulders of 70 years of software development experience and take many of the learnings from that discipline.
SaaStr
APRIL 8, 2020
Divvy is a seamless expense management software combined with the world’s smartest business card giving your company total control of finances. UruIT’s Free Machine Learning Consultation. Where can I find the deal? Click here for Divvy’s Seamless Expense Management Platform for Businesses.
Tom Tunguz
OCTOBER 19, 2023
Machine learning’s demand for data has accelerated this movement because AI needs data to function. Data teams receive tickets from their internal customers & develop data products that serve both internal & external users, much like a classic product management & engineering team.
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