๐ฆ๐๐ผ๐ฝ ๐ฉ๐ถ๐ฏ๐ฒ ๐๐ผ๐ฑ๐ถ๐ป๐ด. ๐ฆ๐๐ฎ๐ฟ๐ ๐จ๐๐ถ๐ป๐ด ๐๐ ๐๐ถ๐๐ต ๐๐ป๐๐ฒ๐ป๐.
Most people vibe code. They prompt an AI, accept the result, and ship it. This works until it breaks. When it breaks, no one knows why.
Vibe coding assumes the model knows your goals. It does not. It only knows your text. Vague prompts produce vague code. This code looks fine at first but fails on edge cases.
The output depends on your intent. This is a thinking problem, not a model problem.
I see engineers build a demo in 20 minutes and spend two days debugging production. The model made a decision that looked reasonable but failed for their specific data. The model was not wrong. It just lacked context.
Before I write a prompt, I define three things:
- What the code must do
- What the code must not do
- How I will verify the result
Most people skip the last two steps. Skipping step two leads to security holes and errors. Skipping step three means you did not understand the problem.
I use AI for low-risk, high-speed tasks:
- Boilerplate code
- Repetitive data transforms
- First drafts of tests
- Scaffolding new routes
I take over for high-judgment tasks:
- Data modeling
- Failure modes
- Authentication
- External APIs
AI is a force multiplier. It amplifies your skills. If you bring no direction, you get no results faster.
I read AI output line by line. I do not skim. I treat it like code from a confident junior engineer who makes subtle mistakes.
At Datawise, I evaluate models using structured benchmarks. These models are great at looking right. Looking right and being right are different. Bugs live in that gap.
Reading the output is your job.
A vague prompt: "write a function that processes user input" A specific prompt: "write a Python function that validates a username. Use ASCII only. Length must be 3 to 30 characters. No spaces. Raise a ValueError on failure. Use only the standard library."
The second prompt gives you code you can ship. The first gives you code you must rewrite.
The real skill is writing prompts that leave no room for interpretation.
- Plan in plain language first.
- Write your requirements and constraints.
- Let the AI draft.
- Read every line.
- Reject clever code that is wrong.
- Verify against your intent.
Vibe coding is fine for prototypes. It is a bad way to build reliable software.
Source: https://dev.to/gmoustakas/stop-vibe-coding-start-using-ai-with-intent-3km3
Optional learning community: https://t.me/GyaanSetuAi