Spec Driven Development for AI Apps
Spec-Driven Development with AI
On this page
- Spec-Driven Development with **AI**
- Hi, I'm **Anirudh Jwala**
- Be **honest** for a second
- "Add Event Bookings." What Did We Forget to **Decide**?
- How we work with AI has **changed**
- From delegating code to delegating **decisions**
- Code is cheap. **Ownership** is not.
- Your fundamentals are your **passport**
- Two users, **one** seat, same moment
- Working code doesn't mean the right **problem** was solved.
- Why this matters for **you**
- Two ways to describe the same **project**
- If AI can write the code, who defines what **correct** means?
Notes
The prompt 'Add event bookings' produces a button, an endpoint and a database insert, and it demos fine.
But none of these rules were ever decided, so the AI either guessed or ignored them.
The code is correct for the problem as it was stated. The problem was simply under-specified.
Notes
We started with autocomplete, where AI typed and we decided.
Then came prompt to code, then agents that understand the repo and edit many files at once.
Now autonomous workflows plan, build and test on their own.
At each step we hand over more. The last box is the real question: who is making the decisions now?
Notes
Look at how vague these prompts are. Each one quietly hands over a product decision, not just a coding task.
'Appropriately' and 'whatever needs improvement' leave the AI to guess what we meant.
Key line: more context about the code is not the same as understanding the product's intent.
Notes
Generating code is now fast and cheap. Living with that code is not.
When production breaks, the model's name is irrelevant. What matters is whether your team can understand and fix the code.
Notes
AI can translate your skills into a new language overnight.
Fundamentals are what let you check whether that translation is actually right.
For example, knowing what a race condition is makes you ask what happens when two people book the last seat.