Intent-Driven Engineering Is Getting Simpler
Intent-Driven Engineering Is Getting Simpler
Small intents. Real software. Continuously improving.
Intent-Driven Engineering has evolved.
Not by adding more process, more templates, or larger specifications.
By removing what was unnecessary.
The practical model is now built around one simple idea:
Start with the smallest intent that can produce something real. Then let evidence tell you what to add next.
Traditional software development often tries to specify the solution before the team has seen the solution.
AI makes that problem even more obvious.
Too much specification constrains the intelligence that is supposed to help us. Too little specification gives AI permission to redefine the outcome.
Intent-Driven Engineering sits between those extremes. Humans define what must be true. AI determines how to achieve it. Systems prove whether it actually worked.
IDE-White-Paper.pdf
The IDE Loop
The operating model is five steps:
State the intent — Human declares. Define the desired outcome, authoritative inputs, required outputs, and only the boundaries that genuinely matter.
Build something real — AI reasons. Let the AI choose the design, implementation approach, tools, and alternatives.
Observe and judge — Human judges. Use the result. Inspect it. Even “I don’t like this” is legitimate engineering feedback.
Add the smallest refinement — AI adapts. Capture only what the real result taught you. Do not turn the refinement into instructions for how the AI must think.
Validate with evidence — System proves. Tests, hooks, policies, telemetry, and observable behavior demonstrate whether the requirements actually hold.
IDE-White-Paper.pdf
Then run the loop again.
That is Progressive IDE.
Progressive IDE: The Best of Both Worlds
Progressive IDE is not a replacement for Intent-Driven Engineering.
It is the practical way we execute it.
The human keeps authority over the outcome.
The AI keeps freedom over the solution.
The specification grows only when working software gives us a reason to grow it.
IDE-White-Paper.pdf
That distinction matters.
The human owns what must be true.
The AI owns how to satisfy it.
The system owns proof.
When those responsibilities stay separate, humans stop micromanaging AI reasoning, and AI stops moving the goalposts.
IDE-White-Paper.pdf
Less Specification. More Evidence.
The goal was never to eliminate engineering discipline.
The goal was to put discipline in the right place.
Instead of trying to predict everything before implementation, IDE allows the team to learn from the running system.
Build something.
Look at it.
Judge it.
Refine it.
Prove it.
Every additional requirement should earn its place.
That produces something traditional specifications rarely achieve:
a specification shaped by reality rather than prediction.
Start Small
A team does not need a transformation program to begin.
Pick one real outcome.
Write the smallest useful intent.
Give it to the AI.
Build something that runs.
Judge the result.
Add only what you learned.
Prove what matters.
Then do it again.
IDE-White-Paper.pdf
That is the direction Intent-Driven Engineering is taking:
Small intents.
Real software.
Human judgment.
AI reasoning.
System proof.
Continuously improving.
Progressive Intent
The best of both worlds.
Intent-Driven Engineering Is Getting Simpler: Introducing Progressive IDE
Progressive IDE | The Practical Intent-Driven Engineering Model
Intent-Driven Engineering now follows a simpler execution model: start with a small intent, build something real, judge the result, refine only what you learn, and prove completion with evidence.
Comments