---
title: "The AI API : The Twilio Moment for Machine Learning"
description: "Explore how AI APIs are transforming startup development, with 90% of companies launching AI features in 2023 using minimal resources - the Twilio moment for ML is here."
categories: ["AI"]
keywords: ["AI API","Twilio moment","machine learning","SaaS","startup development","large language models","chatbot development","vector database","AI features","technology deployment"]
ai_summary: "AI APIs are revolutionizing startup development, enabling rapid deployment of machine learning features with minimal resources."
date: 2023-06-06
lastmod: 2026-07-20
canonical_url: https://www.tomtunguz.com/ai-ease-of-dx/
author: "Tomasz Tunguz"
---

90% of startups have plans or have released an AI feature, 54% of those features will launch in 2023, but only 30% of companies are hiring new people to do it, [according to Productboard's survey](https://www.productboard.com/blog/generative-ai-and-products/). 

![image](https://res.cloudinary.com/dzawgnnlr/image/upload/b3ztahlfh8o71zvgzyhu.png)

These figures highlight three points: 

1. AI has become [an essential product component for most software companies](https://tomtunguz.com/ml-as-table-stakes/).
2. Startups have aggressively prioritized these features on their roadmaps with 54% launching a feature this year.
3. AI deployment is sufficiently straightforward that a majority of teams won't hire new experts to build them & will staff 1-2 people to launch them.

The last one is the most striking. 

Training, deploying, & optimizing machine learning models has historically required teams of dedicated researchers, production engineers, data collection & labeling teams. Even fully staffed, teams required years to develop models with reasonably accurate performance. Today, it's a matter of days or weeks.

Newer LLMs (large-language models) simplify AI-feature development in the same way Twilio empowered developers to send an SMS with five-lines of code, abstracting the complexities of carrier-integration. Stripe did the same, simplifying credit card payments.

Building a chatbot for some collection of customer support articles or blog posts is straightforward : 

1. Gather your documents
2. Save them in a vector database
3. Upload the vector database 
4. Start chatting away by hitting the API

[The time to utility is measured in minutes.](https://tomtunguz.com/time-to-utility/)

Every [company will be an AI company](https://tomtunguz.com/every-company-will-be-an-ai-company/), because the technology is simple-enough to deploy & powerful-enough to work sufficiently well out-of-the-box that most companies can get started today.