Thursday Labs Case Study

"I've Never Liked an AI Tool Before This": How a Skeptical Podcaster Cracked Instagram Growth in 2 Weeks

The Conventional Wisdom Is Wrong

Most podcasters follow the same Instagram growth playbook: post one high quality reel per day, engage with comments, and wait six to twelve months for the algorithm to notice you. Some try to speed things up with ads. It is slow, it is expensive, and for most shows, it still does not work.

Jake Hurwitz, founder of Thursday Labs, a podcast production company that has launched over 50 shows in the last two years, wanted to test a different hypothesis. What if volume, not perfection, was the real unlock? The traditional approach assumes growth comes from crafting the perfect clip, posting at the right time, and hoping it goes viral. Jake saw a different pattern in the data: aggregate view count can matter more than any single clip, because posting at scale creates far more chances for something to catch.

So he ran an experiment. One month ago, he launched a brand new clips Instagram account for one of his podcasts and posted 20 to 30 reels per day, every day, all organic with zero paid ads. The goal was not to make every clip perfect. The goal was to flood the zone and let the algorithm decide what resonates.

The Problem: Slow Growth, High Costs, Limited Learning

Before this experiment, Thursday Labs was following industry best practices and running into the same limits most podcasts face on Instagram. The standard strategy is to post one to two high quality clips per day, spend hours polishing each one, and often rely on paid ads to amplify reach, typically two to five thousand dollars per month, then wait six to twelve months for traction while guessing what themes work from limited data.

The result is slow, expensive growth with weak feedback loops, and it does not scale when you are managing multiple shows at once. Jake believed there had to be a better way to generate more distribution opportunities and learn faster without blowing up the budget. The question became simple: could volume be a strategic advantage instead of something that feels impossible to execute?

The Strategy: The 5K Rule and Posting at Scale

Jake built a system he calls the 5K Rule, a volume first strategy designed to find what resonates quickly and then amplify only the winners. Instead of posting dozens of clips on the main podcast account, Thursday Labs launched a separate clips account built specifically for testing at scale. This gave them the freedom to experiment aggressively without overwhelming the existing audience on the primary brand page.

From there, they used Overlap AI to publish 20 to 30 reels per day, all organic with zero paid promotion. The clips spanned different themes, formats, and moments from the show to create a large testing surface. Jake’s belief was simple: individual clip performance matters, but aggregate view count matters more, because posting at scale dramatically increases the odds that something catches fire.

Then they applied the filter. Any clip that crossed 5,000 views on the testing account was promoted to larger audiences by adding the main podcast account, with around 40,000 followers, and Jake’s personal account, with around 25,000 followers, as collaborators. This turned the clips account into a proving ground where everything contributes to reach, but only proven content gets amplified. Over time, the volume of tests generated fast, reliable insights that could shape creative decisions across the board, from trailers to episode structure, replacing guesswork with data backed storytelling.

The Results: Why This Required AI Automation

Jake’s “5K Rule” turned Instagram growth into a repeatable system instead of a slow guessing game. By creating a dedicated clips account, Thursday Labs separated high volume testing from the main podcast presence, which let them experiment aggressively without overwhelming their existing audience. With Overlap powering output, they published 20 to 30 reels per day, all organic, across a wide range of themes, formats, and podcast moments, creating far more chances for content to break through and generating clearer performance patterns in days rather than months.

The 5K threshold then acted as a scalable filter for amplification. Only clips that crossed 5,000 views on the testing account were promoted to larger audiences through collaborator posting on the main podcast account and Jake’s personal account. This kept the primary feeds focused on proven content while still benefiting from the cumulative reach of the testing account, resulting in faster learning cycles, more consistent discovery, and a workflow that scaled distribution without scaling manual effort.