After what seems like too many years in software, I’ve seen plenty of “revolutionary” tools come and go. Claude Code, though, feels different. Claude Code is all you need starts with brazen boldness :
Have faith (always run it with ‘dangerously skip permissions’, even on important resources like your production server and your main dev machine. If you’re from infosec, you might want to stop reading now-the rest of this article isn’t going to make you any happier. Keep your medication close at hand if you decide to continue).
Look, I’ve been the paranoid engineer. I’ve also been the one pushing boundaries. Both approaches have their place. But with Claude Code, I’ve found that conservative usage gets conservative results. The tool responds to confidence.
Long time ago, “Context is King” used to be a common saying that got morphed into “Cash is King” into many different places. I think we’re cycling back
Give it a lot of input. The more input you give it, the better its output is. It’s a magic tool, but you’d still better be damn good at communicating, either by typing thousands of words into text files or the interactive window.
I find it helpful to tell junior engineers that if you can’t explain what you want in plain English, you probably don’t understand the problem well enough to solve it. AI tools just make this more obvious. They’re amplifiers.
Once more thing that has stuck with me:
I’ve probably read more LLM-generated words than human-generated words in the last few months
That’s probably not a terrible thing if the text were edited afterwards to cohesivness and to mean actually what the writer (prompter?) wanted to say. Mindlessly generated documents are awful dumpster fire that deserve to be sent back.
The post doesn’t oversell it though:
you should know that a) these models are still inconsistent - they can perform wildly differently based on the same or similar inputs, and b) they’re very sensitive to the quality and quantity of input
This inconsistency maps to what I’ve seen - the same prompt can yield brilliant insights one day and complete nonsense the next. It’s like working with a really smart intern who sometimes has off days. You learn to work with the variability rather than fight it.
Something else resonated is that this is all not some magic bullet, its just yet another tool:
I’ve always told people that coding is just conditional logic and looping (which is just conditional logic). So if you want to be a programmer, learn what an if statement is and build stuff.
I keep seeing people expect AI to turn them into programmers overnight. But if you don’t understand the underlying logic, you’re just copying and pasting magic spells to create one massive footgun. The AI can help you write the code faster, but you still need to understand what the code should do to make sure its the right code.
What strikes me is how this mirrors other tool transitions I’ve lived through. The fundamentals stay the same, but the interface for expressing them gets more natural and sophisiticated.
From my purview, the question isn’t whether these tools will change software development. They already have. The question is whether we’ll use them thoughtfully. Sadly, the industry has a history there.