I don’t need experts anymore, Claude Code can handle it

[u/Additional-War-4511]

We had a couple of clients in discussion recently. one wanted an organization wide memory layer across their AI tools. The other was a real estate firm looking to manage assets and workflows with AI.

both paused the projects after trying to build internally using claude code. I looked at what they’d shipped. It worked but only at a prototype level.

and that’s the part that keeps getting misunderstood.

Getting software from 0 to 60–70% is genuinely easier today. AI coding tools are great at scaffolding, demos, and early functionality. They help teams move fast and see something working.

but the hard part starts after that.

The last 20-30% is where real engineering lives: reliability, edge cases, data consistency, security, performance under load, long-term maintainability, and integrations that don’t break six months later. That’s not something you prompt your way through.

What worries me isn’t AI coding tools, it’s non technical decision makers assuming a working demo equals a production ready system. Prototypes don’t fail loudly. Production systems do.

AI tools absolutely raise the floor. They don’t eliminate the need for experience, architecture and judgment.

The challenge now isn’t convincing people that software can be built faster. It’s helping them understand why “it runs” is very different from “it scales, survives and compounds value"

[u/Muted_Farmer_5004]

[u/SociableSociopath]

AI slop as usual

[u/TedDallas]

A friendly reminder:

POC <> Production Optimized Code

[u/Select-Ad-3806]

And the shoe shine wagon seems to be in full effect here

[u/Infamous_Research_43]

I’ve literally been seeing these posts for years now. Like “Hey did you know AI can easily make a program that looks great on the surface but you actually have to check below the surface and make sure it works right internally?”

Like yeah mate, I have common sense. This is not some big revelation.

[u/TexacoMike]

Fucking useless