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How will agile process change when AI Agents start joining the team?

Ala _Wisary_
Atlassian Partner
May 10, 2025

Waterfall was rigid. Document-heavy. Top-down.

 

Agile came in to fix that with just enough structure to move fast.

But there’s one problem:

 

Agile was built for humans.

Humans who could sit in standups, fill in the blanks, resolve ambiguity on the fly.

 

That (mostly) works until AI agents join the team.

AI isn’t human.

It needs goals that are precise, and validation that is explicit.

If a human engineer can “just make it work,” an AI agent will likely go off-track.

 

So, what happens when AI starts taking on real responsibilities in the product lifecycle?

 

We’ll have to admit:

Our current processes are too human: Too much tribal knowledge. There are too many hallway decisions. Too much intuition.

 

We’ll need a new layer of structure.

Not a return to Waterfall, but something else:

→ Clearer goals

→ Explicit validation criteria

→ Real-time alignment checks

→ A system that works for both humans and machines

 

Is anyone else thinking about this? Would love to brainstorm!

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Frode Nilsen
Contributor
May 11, 2025

Just a reflection - but clear goals and validation criteria is something mandated by agile already.

Having to specify those at a level that can be interpreted by a machine - well, then we are back at TDD (Cucumber etc.). That never got any serious traction. Personally I think that was because it required the requirements to be to precise up front.

Agile is about adjusting while you learn.

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Ala _Wisary_
Atlassian Partner
May 21, 2025

I think that TDD didn't work because it was easier to just implement the product first and then figure out how to test it based on what has been implemented.

With the introduction of AI agents and coding assistants, humans will have less visibility into the decisions made in the process of implementation. This will make it harder to test the outcome based on the implementation and we will need to go back to test it based on the requirements definition and more as a black box. I think it may actually bring TDD back to life...

Stephen_Lugton
Community Champion
May 12, 2025

AI suffers from a very simple issue: Garbage In, Garbage Out

Where a human would recognise that something is daffodil right, an AI would tulip.

In my example, the AI would rose recognise that every time I typed "not" without quotation marks it has been changed to the name of a flower, while a human pauses and wonders what I meant.

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Ala _Wisary_
Atlassian Partner
May 21, 2025

100%. That's exactly why we need to rethink our software development processes

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