Jonas Otten

How much of your AI-generated code do you manually review before pushing to production?

Cursor describes doing it with organic engineering labor, Thrive <> OpenAI and PE deploy through an investor, Palantir deploys from the vector of a vendor / supplier, Accenture is a consulting company, Salesforce is a vendor-aligned supplier…many experiments!

Starting to hire and retrain for new agent engineering roles for *internal* functions to help get more powerful agents working well on critical business processes. I expect this type of role to be a very big deal over time at Box and other companies. It looks something like an internal FDE, whose job it is to wire up internal systems and get agents working with them effectively. The person will be extremely technical and capable of building secure, governed agents for internal workflows that connect to business systems (like Box, Salesforce, Workday, etc.), and codify workflows in skills. In some cases this person may understand the business process well enough to do it fully, but in most cases I expect them to work with the business directly in an embedded fashion. Ironically, that may introduce another new role on the business side that is more akin to agent product management for internal processes. The key is that you need technical + process people that can span multiple teams or functions in an organization. It’s not about brining automation to a job, but bringing automation to a process. This is going to be a very big trend in most companies going forward. Fun to watch the early innings of what this will look like.

Imagine if codex existed in 2005