Your Product Is Now a Wrapper Around Go-To-Market | Hiten Shah

The episode begins with Hiten Shah discussing the progress in local AI models, highlighting that the technology wasn't sufficiently advanced a year ago but has since become capable of achieving over 90% parity with cloud-based models like Granola's. He mentions recent improvements in models like Quen 3.8 and Gemma 4, and details a new application he developed for managing multiple computers through remote windows, which is relevant for AI workflows but doesn’t incorporate AI directly. The conversation emphasizes that running high-quality local models requires substantial hardware, like 100 GB of RAM, and that models trained in different regions or for specific languages show 'flavor' variations, especially Chinese influence, which impacts output.

Hiten discusses his approach to evaluating emerging AI tools immediately after their launch, using a bot to test new models and compare their effectiveness against specific use cases, enabling him to determine usefulness in real-time. He describes his setup as an 'AI factory,' where he continuously experiments by deploying models on various machines his team maintains, ensuring they stay informed about the latest capabilities. Twitter is identified as a vital source for breaking news and product signals, enabling quick assessments for ongoing use or comparison. This strategic setup allows him to keep an up-to-date mental map of the AI landscape, managing the rapid iteration cycle effectively.

A core idea emerging from the episode is that traditionally, products were built first with go-to-market strategies layered on later. Currently, Hiten argues, the opposite is happening: the go-to-market approach is now the foundation, with products tailored or tweaked to fit these distribution channels. He explains this by citing experiments across multiple products—from paid ads and freemium models to community engagement—showing how the entire product suite becomes a wrapper around the chosen go-to-market motion. This shift allows for faster iteration, where marketing feedback and signals drive product adjustments, making the 'product' a means to serve the strategic distribution approach.

Turning to his own business, Castos, a podcast hosting platform, Hiten discusses how competitive commoditization has made core features like hosting and analytics somewhat interchangeable. The focus, he suggests, should be on automating growth—enabling podcasters to increase their audience—by leveraging AI-driven content repurposing, social media automation, and personalized growth tools. He emphasizes that for such platforms, success depends on aligning product features with the ultimate goal of serving and expanding the content creator’s audience. The key is to differentiate by focusing on the user’s growth metrics rather than just the technical hosting functions.

Hiten shares his excitement about recent AI breakthroughs, like models that can now reliably control computers and browsers, effectively transforming AI into interactive teammates. He praises the rapid progress made by models like Muse, Grockbot, and others, which handle a large fraction of previous complex tasks. Despite this optimism, he confesses that the pace of change is also a source of concern, as it makes identifying durable product strategies challenging amidst fleeting opportunities. He also discusses the importance of differentiation and distribution, emphasizing that companies like Meta and others are using their ecosystem advantage to stay ahead in AI influence and deployment. The overarching message is that change creates opportunities but also makes strategic stability harder.

Hiten advocates for deliberate focus—calling out that businesses must choose specific markets or customer groups to serve. He underscores that go-to-market strategy is now the core of product development, urging companies to experiment with different channels and align their products accordingly. His advice includes defining what the business aims to achieve in the near future, then tweaking the product or marketing approach to serve that goal. He stresses the importance of understanding the 'obvious future'—the inevitable direction of your market—and positioning your company to benefit from it. His own examples with Crazy Egg, Notes, and Castos illustrate a flexible approach to adapting product offerings and distribution channels in response to evolving AI capabilities.