Tracer Bullets
Continuing the topic from the previous post, let's talk in more detail about implementing vertical slices.
The original concept comes from The Pragmatic Programmer, where it was called tracer bullets. A tracer bullet is a small, end-to-end slice of functionality that touches all layers of the system at once.
Matt Pocock in his article adapts this concept to AI engineering:
- Build a small feature end-to-end
- Test it immediately
- Get feedback
- Move to the next slice in a fresh context window
- Repeat
Matt explained this in the following way: AI's natural inclination is to build big layers in isolation. But we need to do the opposite: build the whole scenario end to end across all layers.
The article also provides a prompt sample:
When building features, build a tiny, end-to-end slice of the feature first, seek feedback, then expand out from there. When building systems, you want to write code that gets you feedback as quickly as possible. Tracer bullets are small slices of functionality that go through all layers of the system, allowing you to test and validate your approach early. This helps in identifying potential issues and ensures that the overall architecture is sound before investing significant time in development.
So this approach forces the agent to think by small chunks and produce more predictable results.
As they say, everything new is just well-forgotten old. As we can see, AI often doesn't bring really new concepts, but rather brings existing ones back to life.
#engineering #ai
Continuing the topic from the previous post, let's talk in more detail about implementing vertical slices.
The original concept comes from The Pragmatic Programmer, where it was called tracer bullets. A tracer bullet is a small, end-to-end slice of functionality that touches all layers of the system at once.
Matt Pocock in his article adapts this concept to AI engineering:
- Build a small feature end-to-end
- Test it immediately
- Get feedback
- Move to the next slice in a fresh context window
- Repeat
Matt explained this in the following way: AI's natural inclination is to build big layers in isolation. But we need to do the opposite: build the whole scenario end to end across all layers.
The article also provides a prompt sample:
When building features, build a tiny, end-to-end slice of the feature first, seek feedback, then expand out from there. When building systems, you want to write code that gets you feedback as quickly as possible. Tracer bullets are small slices of functionality that go through all layers of the system, allowing you to test and validate your approach early. This helps in identifying potential issues and ensures that the overall architecture is sound before investing significant time in development.
So this approach forces the agent to think by small chunks and produce more predictable results.
As they say, everything new is just well-forgotten old. As we can see, AI often doesn't bring really new concepts, but rather brings existing ones back to life.
#engineering #ai