If you use it right, Twitter is the best place to learn more about Data & Analytics Engineering.
Finding the right people to follow is hard. So I scoured every nook and cranny to find the best people talking about data.ย
Follow these thought leaders ๐งต๐
Here's what's been working for me:
1. Ask specific questions about the code base to get high level understanding.
2. Create a spec for the problem in hand based on the shared understanding from step 1.
3. Review parts of the spec, ideate alternatives, specify testing harness and output validation.
4. Once the spec looks good. Move to phase wise implementation, ensure there's shared understanding and tests pass
https://t.co/RnLGwoQMFf
After 6 months of watching engineers use coding agents, I found the most productive users have something in common
The best ones use what I call "Socratic mode"
Instead of just telling the agent what to do, they start with questions that force it to load the right files and actually understand the abstractions. They keep going (and correcting the agent) until they're confident both they and the agent understand the shape of the problem and the goals
The benefit here is that instead of guessing at a plan upfront, you're helping both yourself and the agent truly understand the codebase first before starting to make any changes
By the time you ask it to do something, all the context is already "built" and the path forward is clear