Product and engineering lessons from building a pack-based AI photo workflow around a single reference portrait.
GenBlink generates 10–50 portrait photos from one source via curated packs with transactional credits and streamed partial results. For tech leaders: AI becomes product through workflow design—bounded directions, quality review, partial resilience—more critical than raw model choice.
AI image generation demos usually optimize for one impressive output. A product
has to solve a different problem: helping a real user get a repeatable, useful
result.
I have been building GenBlink, a workflow where a
user uploads one clear adult portrait, chooses a curated visual pack, and
A few months ago I had a group photo from a trip where one friend was missing — she'd left early. I...
AI image generation is easy. Building the handoff layer is harder. A few days ago, I launched and...
Over the last few years, I have built products in very different domains: generative AI, job search,...
A practical look at why production AI image generation works better as an asynchronous workflow.
Most AI image experiments fail for a boring reason: the prompt is treated as a one-off sentence...
AI tools have changed the game of selfies, allowing people to improve lighting, facial details, and create polished versions of…
