Coding-Equivalent Work Audit
Find the task AI will automate next and move one level higher
- Difficulty
- Moderate
- Time to result
- ~weeks to results
- Steps
- 6
- Confidence
- 98%
Software engineering provides a preview of how AI changes other professions: first it automates the visible execution layer, then it begins moving into planning and architecture. Apply that pattern to your own role by identifying the equivalent of writing code—the repetitive production work that consumes time, such as maintaining spreadsheets in finance. Expand the audit beyond current chores to include valuable work you should do frequently but never reach, or work you perform below the standard it deserves. Test AI against those units, then deliberately decide what higher-level strategic, relational, or creative work should absorb the recovered capacity. Because capability moves quickly, a failed test is temporary evidence rather than a permanent verdict; retry it in a month.
Origin
Joshua Wöhle uses the rapid automation of software engineering as a transferable model for anticipating how AI will reshape every knowledge-work role.
Core principles
- 01Every profession has an execution layer analogous to coding
- 02Automating a task should move the worker toward higher-value work
- 03Neglected high-value work is a major AI opportunity
- 04AI capability should be retested because it changes rapidly
- 05Workers should participate actively in redesigning their role
How to run it
- 1
Map recurring work
List tasks you perform frequently and note how much time and attention each consumes.
Watch out Do not list only the most visible tasks.
- 2
Surface neglected value
Add useful tasks you rarely reach and tasks that deserve a higher standard than you currently provide.
Pro tip This neglected-work list can hold more upside than obvious time savings.
- 3
Name the coding equivalent
Identify the execution layer in your profession most analogous to a software engineer manually writing code.
Pro tip For finance, Wöhle suggests spreadsheet management as one example.
- 4
Test AI capability
Experiment with having AI perform increasing portions of the task and assess the real output.
Pro tip Give it process, context, and examples before judging capability.
Watch out One superficial attempt is not a reliable test.
- 5
Move one level higher
Define the strategic, relational, or judgment-heavy work that becomes possible when the execution layer shrinks.
Watch out Reclaimed time without a deliberate destination can simply produce more low-value work.
- 6
Retest the frontier
If AI cannot yet meet the standard, schedule another practical test in one month.
Watch out Do not treat today's limitation as a durable boundary.
In the wild
A finance professional identifies manual spreadsheet updating as the role's coding equivalent. AI takes over more of the maintenance, while the professional redirects time toward the strategic financial picture, supplier decisions, and financing structure.
→ The role shifts from maintaining artifacts to making higher-level financial decisions.
Hala Taha used AI to uncover her workflow and build an app that turns an episode transcript into hooks, clips, and quotes. A recurring production task became a system, freeing attention for editorial judgment.
→ A non-coder automated a repetitive content-preparation layer in minutes.
Common mistakes
Auditing only current busywork
Ignoring valuable work that never gets done misses a major source of AI-enabled improvement.
Freeing time without redesigning work
Automation creates capacity, but value appears only when that capacity is deliberately moved to a higher level.
Treating one failure as permanent
Fast capability gains mean a task that fails today may work when tested again next month.
Is it for you?
Best for
It is best for professionals and teams whose roles contain repeatable execution work alongside higher-level judgment.
Not ideal for
It is not ideal for tasks where human presence, accountability, or physical action is the core value.
From the transcript
“what is the equivalent of coding for a software engineer but for someone in finance or for a lawyer or for an HR professional or…”
“what are the things that I am doing that I'm doing fairly frequently and that take a decent amount of of work”
“Try it again in a month.”
From the episode
Joshua Wöhle: Turn AI Into Your Competitive Advantage and 50X Your Productivity
Joshua Wöhle