SkynetLabs internal R&D

Built a 200-asset carousel pipeline that turns 1 brief into a full week of content in under 9 days from null.

Producing voice-locked carousel content at scale for client launches was eating 3+ hours per day of manual layout work in Figma. Worse, every batch was at risk of leaking AI-tell phrases ('In today's fast-paced world…') because the QA was a human reading 200 slides in a row.

The brief — set internally — was to turn one topic brief into 200 PNG-ready carousel slides, with image rotation, AI-tell linting, and a render pipeline that didn't depend on a designer being awake.

Most 'AI content engines' you see on Twitter are a single GPT call dumped into Buffer. Ours is the opposite — most of the value is in the linter and the image-rotation log, not the LLM call. The LLM is the cheapest part of the system.

The 60-phrase AI-tell list was built by hand-rating 500 slides against the Wikipedia 'Signs of AI writing' guide. Phrases like 'In today's fast-paced world', 'Let's dive in', 'It's important to note' — every one of them is a free signal to the reader that they're reading machine output. Stripping them is a one-pass regex.

The image-rotation log is the part nobody talks about. Carousels lose engagement fast when the same illustration shows up across three consecutive batches. The log tracks every asset used per day and prevents re-render within a 30-day window. Engagement stayed flat across 12 weeks of daily output — exactly what we wanted.