My tech stack used to be: VS Code GitHub Stack Overflow Coffee Now it’s:

Hey @grok, what’s a job that will be disrupted by AI NOT because AI is better at it, but because AI is simply cheaper? I think this distinction matters.

Would you pass your own technical interview today without AI?

Reaching the first $1K of MRR fast only proves people wanted the product. What matters is whether month three looks like month one. Retention is the real milestone.

Drop your landing page. I'll rewrite your headline in one sentence and tell you what's confusing about it. Honest feedback only.

Hey @grok, which high-paying career could become a terrible investment for someone starting college in 2027? Be specific.

I'm testing a new rule for AI tools: If it can't save me time on a REAL task, I don't care how impressive the demo looks. What's the most useful AI workflow you've actually used?

Hey @grok, what’s one profession that people think AI will NEVER replace, but you believe could look completely different by 2030? Give me an unexpected answer.

Retries can hide flaky systems. Track first-attempt success separately from eventual success.

Add a "this was wrong" button. It's free training data and free product feedback.

The cost of an AI coding task isn't just the API bill. It's inference + tool execution + retries + review + regression risk + maintenance. A cheaper model that needs three correction cycles may be more expensive than a stronger model that gets the architecture right on the first attempt. I'd benchmark cost per verified change.

Being a good developer got you to the product. Being a decent marketer will get you the customers.

One unexpected effect of AI-assisted development: I spend less time typing code and more time deciding what code should exist. Requirements, boundaries, failure modes, and verification have become a bigger part of my workflow.

Optimizing tokens per task can be the wrong objective. If aggressive context reduction removes the one constraint that matters, you save tokens and increase the probability of an expensive failure. The metric I'd care about is cost per correctly completed task—not cost per response.

The same model gives different answers to different prompts. It's not the AI that's inconsistent, it's the input.

What's a business model that looks boring from the outside but is secretly excellent? I'm more interested in sustainable businesses than billion-dollar fantasies.

Code review for AI-generated changes should focus on invariants, trust boundaries, hidden coupling, and failure behavior—not merely whether the implementation looks idiomatic.

"We'll monetize later" is how you build a product nobody values.

Hey @grok, if AI keeps getting smarter at analyzing cases, writing contracts, and researching laws… What exactly will lawyers still be doing in 2035? I’m asking for a friend.

Shipping faster doesn't help if you're shipping features nobody needs.

Narrow agents win. "Summarize my support tickets daily" beats "run my business."