Ever since I started reading the docs before asking an LLM:
- Debugging got faster
- I catch bad AI suggestions earlier
- Fewer "it works but I don't know why" moments
- Better questions in my prompts
- Understand my own codebase again
Should have done this years ago
AI coding agents are mostly a context game.
When an agent does a bad job, the usual cause is that you never gave it the files, the constraints, or the plan it needed to do the job right.
The context you give it shapes everything else the agent does.
the highest level of being a software engineer is when your friends think you never read the docs and never get stuck, and the LLM gives you the right answer on the first try
software is dead...
trust me, most of these people have never maintained a production system.
they've never been paged at 3am or migrated a database with real users on it.
and they tell you to stop learning to code.
these people are suffering from the Dunning-Kruger effect.
(this means people with little skill in a field tend to overestimate how good they are at it.)
my AI tool stack as a software engineer (imo):
- coding: claude code
- planning: claude, talking it through before I open the editor
- research: grok + gpt
- learning something new: read the docs first, then ask an LLM
- teaching: record the video, see where I get stuck
my AI tool stack as a software engineer (imo):
- coding: claude code
- planning: claude, talking it through before I open the editor
- research: grok + gpt
- learning something new: read the docs first, then ask an LLM
- teaching: record the video, see where I get stuck
4 things I wish I understood earlier as a software engineer:
- being able to read code is more important than writing code fast.
- most hard problems become easier when you define them properly.
- you don't need to know every new framework.
- the best engineers communicate clearly.
your technical skills get you into the room.
your ability to think gets you promoted.