Episode 12
After a run of guest episodes, Redacted gets back to its roots. Today we show what it actually looks like to run a company with AI in 2026. Not just the shiny thing they built, but why they built it and how the pieces connect. It's mostly an inside look at Offline's product process, with plenty of lessons any founder can steal.
What We Cover
The Hot List: A prototype Raleigh restaurant feed tracking what’s opening soon, newly opened, and changing daily, complete with opening-day Instagram reels and a map.
Hiring an AI to watch the city: The backend mimics a human scanning Instagram and local news, using a $148/month RapidAPI social data API plus an LLM to determine when restaurants actually open and write the stories.
Steal your own app’s skeleton: Rather than design a new UI, David pointed Claude at Offline’s Flutter repo and had it recreate the existing home screen with the new data, interactions, icons, and colors.
“We don’t have lots of time and people anymore”: Offline’s old prototype, interview, meeting, repeat process took months and significant headcount, so the team is building tools to dramatically compress that loop.
Every feature gets an LLM interface: Taylor’s rule is that anything new he builds for Offline also gets an interface an LLM can operate, including a survey API that lets Claude or Codex generate complete surveys from chat.
The survey Typeform couldn’t do: Taylor built a survey with an intro video, embedded live prototype, direct questions, up to three AI-generated follow-ups, automatic progress saving, and a paid-interview booking link, running on Cloudflare with a Qwen open-weight model.
Build it vs. wait for it: David checked Typeform’s new AI form product live and found it offered only a fraction of Taylor’s functionality, reinforcing the idea that waiting 12 to 18 months for a SaaS vendor can now be unnecessarily slow.
North Star first: Offline’s key metric is members who visit a restaurant each month, and with roughly 3,600 active Triangle subscribers, the focus is whether the Hot List can get inactive members thinking about and using Offline more often.
“Are you even going out to eat?”: Drawing on Itamar Gilad’s Evidence Guided and frameworks like RICE and ICE, David emphasized validating the fundamental behavioral link first. If customers aren’t dining out, no product feature will change the outcome.
The product loop gets faster: A test cycle might shrink from two months to one month, then two weeks, then one week, eventually allowing five parallel experiments with different user groups while an agent monitors the results.
Bonus, a website in an hour: Taylor used the Webflow MCP and Fable 5 to rebuild Offline’s website in Next.js with roughly 10 prompts and under an hour of his own time, while also fixing an FAQ that had been wrong for nine months.
No guests, no polish, just two people figuring out how a tiny team can run a real product process with AI. Enjoy the conversation.
It’s best viewed on YouTube to fully see the examples (make sure to subscribe!)
But also available on all audio podcast players through Tweener Talks!
PLUS we have a new spot for show notes and files discussed in the episode. Check it out: https://github.com/instanttaylor/redacted-podcast
We need your [Redacted] AI experiences for upcoming episodes! Who’s the most underrated AI builder you know? Someone running real systems inside a real business? Send us a message at contact@tweenerfund.com because we want to get them on the show!
What’s Next?
New episodes drop twice a month/every other Wednesday. If you want to be on the show as a guest and show your [REDACTED] builds, email us here.