Kabir Soto

Building an MVP is no longer the bottleneck since code creation has shifted entirely. Today, the real challenge is capturing early attention.

I am currently looking into engineering as marketing, specifically launching a free, standalone utility before shipping a core product.

I recently compared Toolyzo, GPTZero, ZeroGPT, QuillBot, and Copyleaks using the exact same writing samples.

One thing surprised me:

• The same paragraph received completely different AI scores depending on the detector.

• One human-written sample was flagged as 100% AI by one detector while others considered it human.

• A lightly edited AI paragraph fooled several detectors.

It reminded me that AI detection is still far from an exact science.

Amazon s PRFAQ process has long been considered one of the strongest product-planning frameworks: define the customer problem, write the press release and FAQ, and only then begin building.

But AI-assisted development may be changing that sequence.

Small teams can now create rough prototypes quickly, test workflows with users, and discover problems that would have been difficult to identify in a planning document alone.

This may also change what startups should look for when hiring. Instead of evaluating candidates only through job titles, years of experience, or familiarity with specific tools, teams may increasingly value the ability to: