Three ways to think about coding automation

Apr 10, 2023

Gradient Team

AI/ML tech is moving fast. Whether you’re an engineer, CTO, or somewhere in between, you’re likely wondering how to prepare for today and for tomorrow.

AI/ML tech is moving fast. Whether you’re an engineer, CTO, or somewhere in between, you’re likely wondering how to prepare for today and for tomorrow.

AI/ML tech is moving fast. Whether you’re an engineer, CTO, or somewhere in between, you’re likely wondering how to prepare for today and for tomorrow.

AI/ML tech is moving fast. Whether you’re an engineer, CTO, or somewhere in between, you’re likely wondering how to prepare for today and for tomorrow.

AI/ML tech is moving fast. Whether you’re an engineer, CTO, or somewhere in between, you’re likely wondering how to prepare for today and for tomorrow.

To benefit from new tech, you have to figure out what problems it can solve for you. This is very true of LLMs.

One way to figure it out is to look at demos. But that doesn’t put you in the driver’s seat. The better way is to generate your own ideas.

So, here are three ways to think about what’s coming:

  1. Where will automation plug in? Three traits of a task you can automate.

  2. What will step-function increases to AI capabilities look like? Defining levels of coding automation.

  3. How will traditional software roles evolve? Product engineers as a case study.

These posts were born out of our own questioning, and we hope you find them helpful. Please let us know what you think by leaving a comment.

Now, let’s dig into these questions one by one.

Next up: Three traits of a task you can automate