In the last month, Hubspot launched ChatSpot. Zendesk AI automates customer support. Salesforce launched AI Cloud. Adobe’s released Firefly. What do all of these launches & many other similar ones have in common?

The largest SaaS companies in the world have released English-language APIs. Anyone can write English to enter some input (e.g., “What are my top leads for this week?”) & receive an answer.

Previous APIs require learning programming languages to use & have been reserved for developers.

When every major SaaS application has an English-language API, users of all kinds will be able to ask & receive answers of their applications. That is a meaningful innovation.

English language APIs allow for another layer of abstraction.

Imagine being able to write :

Find my top 10 expansion leads this week from Hubspot, then collect their logos, & for each one create an image in Adobe Firefly that puts the company’s logo on a racecar alongside my company’s logo as an attachment to the email. Then draft an email to each prospect using data from their customer support tickets & save them in my drafts folder.

That’s a level of automation rarely seen within the enterprise without custom coding. That workflow alone – if it worked – might save a day’s work. Examples like these illustrate conceptually how AI could unlock 1000x the GDP growth of the PC.

This vision glosses over many important considerations.

First, data security & data loss prevention. How would security leads ensure the workflow is executed by an authorized person, on permitted data, using sanctioned models, & the process complies with international data regulations?

Second, English APIs (aka LLMs) are probabilistic. They err, just like humans. Potential errors could be grave (imagine updating all Hubspot CRM records’ owner to a current user). Monitoring, testing, & rollback/undo buttons will be critical.

Over the past few decades, developers have built systems like this for code : code review, testing, monitoring, isolation. If everyone in a company will have the power to orchestrate software through a natural language API, they will also require equivalent tooling for application development.

As models & controls improve, SaaS orchestration through natural-language APIs will massively improve productivity.