A Day in the Life of a Programmer in 2026

Our jobs are changing. Fast.

In 2018 PWC published a report on how the workforce will change by 2030 and said that 37% or their respondents were worried about automation putting jobs at risk.

We are more than half way to 2030. What does automation look like for a software developer today. What will it look like tomorrow?

Today's Workflow

• Start the day by catching up on what happened while colleagues worked in other time zones.
• Check in on the current project and make sure things are still on track.
• Take a look at bug reports for anything new and surprising.
• Check in with teammates at a standup.
• Get working on a task.
• Get stuck, confused or lost in code.
• Use a mix of Google, GitHub Copilot, and Slack history to find your way back to feeling productive.
• Commit your code and make a PR.
• Work through some code review, and pair with a few developers.

Tomorrow's Workflow

• Start the day by checking in on new tasks completed by AI agents to ensure their work is on track.
• Take a look at few bug fix PRs your AI agents made. Merge the ones that look good, note the ones that need a bit of refining.
• Check in with teammates on the architectural direction their projects are going to ensure you are all giving consistent instructions to the agents.
• Update shared knowledge libraries for the agents based on these conversations so all the agents operate with the same context.
• Go back to a bug fix PR that needed some work and provide clear instructions to the agent that fill in the gaps it had in its knowledge when attempting the fix.
• Work with an agent to build a new feature by describing each step and component so that the agent can build incrementally.
• Provide some final instructions to the agent and ask it to continue working until it finds a solution.
• Log off for the day knowing you can check in on the agent's work in the morning.

Our Jobs are Changing

Developers still need to understand the code they read and understand the implications of the designs they give to AI agents, but the will no longer need to craft beautiful lines of code.

Working with AI will mean that we can focus on outcomes, systems design, and nuanced test cases while offloading implementation details to AI companions.