Stop Measuring Story Points, Start Measuring Realization Speed
Every developer's been there. You start coding with what feels like a solid plan, only to hit that oh crap moment, the realization that your entire approach doesn't actually work. Maybe the product requirements shifted, maybe you misunderstood an edge case, or maybe someone on the team finally spoke up with context you didn't have.
That moment, the first realization, is the most critical metric in software development.
Time to First Realization
"Time to first realization" is how long it takes between starting and realizing you were wrong about something important.
That could be realizing:
- you find out there's an existing internal service that already does half of what you built
- your UI pattern won't work with real data
- your data source has a subtle business rule that breaks your assumptions
- your assumption about user behavior was just… wrong
The faster you get to that point, the faster you can course-correct. Most engineering waste doesn't come from slow implementation — it comes from building the wrong thing, then realizing it too late.
Stop Writing Perfect Code First
Too many engineers start by writing "good code." They set up the folder structure, write all the tests, configure the linter, and make sure it's production-grade before even knowing if the idea works.
That's backwards.
Your first goal should be to learn, not to ship perfect code. Write the messiest, most minimal version possible, something that just barely runs, and use it to validate whether the approach even makes sense. Once you and your team are aligned that, yes, this is the right direction, then refine it.
Good engineers iterate. Great engineers iterate fast.
The Real Purpose of AI
This is where AI shines. AI isn't great at writing production-quality code that matches your team's standards. But it's fantastic at helping you reach that first realization faster.
It can generate a rough draft of your idea — something messy but functional enough to expose what's missing, what's misunderstood, or what's impossible. That's its real superpower: acceleration of learning.
Writing the final code might still take time, but now you're confident you're building the right thing.
How to Improve Your Time to First Realization
If "time to first realization" is the metric that really matters, the next question is obvious — how do you actually make it shorter?
It starts before you even touch the keyboard. The biggest gains come from reducing the gap between assumptions and reality.
1. Talk early, talk often.
The fastest way to realize you're wrong is to involve others before you go heads-down. Ask dumb questions. Share half-baked ideas. Over-communicate decisions. A ten-minute chat can save ten hours of refactoring.
2. Be intentionally scrappy.
Your first version shouldn't be elegant — it should be fast. Write code that just barely works. Hardcode values, skip tests, mock APIs — do whatever you need to validate direction. You can polish later; the goal now is to learn quickly.
3. Accept that code is meant to be rewritten.
Great engineers treat code like clay, not marble. It's temporary by design. Once you truly believe that, iteration becomes painless. You stop fearing refactors and start chasing insights.
4. Use AI to accelerate prototypes.
AI can't replace deep engineering judgment, but it's great for getting a messy idea into code fast. Use it to sketch out rough architectures or stub out components — anything that moves you from concept to reality faster.
The goal isn't to avoid being wrong — it's to get to wrong sooner, so you can move toward right faster.
Everything Else Is Noise
Story points, velocity, burndown charts, they all orbit around a single truth: none of it matters if your team is slowly realizing they're wrong.
Actual implementation time is rarely the bottleneck. The bottleneck is how long it took you to realize you were wrong. The shorter your time to first realization, the better your software and your process will become.