Samuel D.

Agentic Workflow Loops for Developers

Agentic workflow loops for developers

Agentic Workflow Loops for Developers

There’s a future where you might go months without touching a single line of code.

That’s not a dystopia. It’s probably just Tuesday.

With the rise of agentic workflows powered by LLMs, the role of developers is shifting—not disappearing. We’re moving from writing code to designing systems that write code, from implementers to orchestrators.

The interesting question isn’t “Will AI replace developers?”
It’s: What does a good development workflow look like when coding is delegated?

The Shift: From Writing to Shaping

In traditional development, you:

  • Gather requirements
  • Write code
  • Test and debug
  • Ship

In an agentic workflow, you:

  • Define intent
  • Design constraints
  • Orchestrate agents
  • Validate outcomes

The core skill becomes product thinking + system design, not syntax.

You still need strong engineering judgment—but you apply it differently:

  • Reviewing instead of writing
  • Guiding instead of implementing
  • Designing feedback loops instead of fixing bugs manually

The Minimal Agentic Workflow

At its simplest, an effective agentic loop can be broken into three roles:

1. Planner

The Planner is responsible for:

  • Collecting requirements
  • Asking clarifying questions
  • Breaking down the problem
  • Creating an execution plan
  • Delegating tasks

Think of it as your tech lead in a box.

A good Planner doesn’t just translate prompts—it reduces ambiguity. If your workflow feels chaotic, the Planner is usually the missing piece.

2. Coder

The Coder does what you’d expect:

  • Implements features
  • Writes functions, classes, modules
  • Follows instructions from the Planner

This is the easiest role to automate—and the one people over-focus on.

The real leverage comes from what surrounds it.

3. Reviewer

This is where most workflows fail.

The Reviewer should not behave like a human nitpicking code line by line. Instead, it should enforce standards through automation:

  • Run linters and formatters
  • Execute tests
  • Validate contracts
  • Check for regressions

The key idea:
Don’t ask an LLM to “review code quality” when tools already do it better.

The Reviewer is not a critic—it’s a gatekeeper.

Extending the Loop: Where Things Get Interesting

Once you have the minimal loop, you can start layering more structure.

Test-Driven Development (TDD) with Agents

TDD becomes surprisingly powerful in an agentic setup.

Why?

Because LLMs are context-driven. They bias heavily toward what already exists.

If you start with implementation:

  • The model optimizes locally
  • It reinforces mistakes already introduced

If you start with tests:

  • You define behavior upfront
  • The implementation is guided by explicit expectations

This leads to:

  • Fewer logical errors
  • Better alignment with requirements
  • More predictable outputs

In short:
Tests become the anchor of truth for the system.

Dedicated Tester Agent

Instead of bundling testing into the Coder or Reviewer, introduce a Tester agent:

Responsibilities:

  • Generate unit tests
  • Add integration tests
  • Optionally define e2e scenarios
  • Focus on product behavior, not implementation details

This separation matters.

The Coder thinks in implementation.
The Tester thinks in outcomes.

That difference catches real-world bugs earlier.

Architectural Enforcement

One subtle failure mode of AI-generated code is structural drift.

Even if the code works, it might:

  • Violate layering rules
  • Break modular boundaries
  • Ignore domain conventions

This is where architectural tests come in.

Tools like ArchUnit allow you to:

  • Enforce dependency rules
  • Validate package structures
  • Ensure consistency across the codebase

These checks should be part of the Reviewer stage.

Not as suggestions—but as hard constraints.

Because if you don’t enforce architecture automatically, AI won’t respect it consistently.

The Real Skill: Designing the Loop

The challenge isn’t “getting AI to write code.”

It’s designing a loop where:

  • Errors are caught early
  • Feedback is fast and reliable
  • Each agent has a clear responsibility
  • The system improves over time

Bad workflows feel magical… until they break.

Good workflows feel almost boring:

  • Deterministic
  • Structured
  • Observable

That’s what you want.

So… Will Developers Stop Coding?

Maybe not entirely. But it will become optional in many contexts.

You’ll still jump in when:

  • The system gets stuck
  • Edge cases explode
  • You need deep debugging

But most of the time, your job will look more like:

  • Defining intent
  • Designing constraints
  • Reviewing outputs
  • Improving the loop

Final Thought

The future of development isn’t about writing less code.

It’s about building systems that make writing code the least important part of the process.

And the developers who thrive won’t be the fastest typers—

They’ll be the best loop designers.