Hey everyone! With the landscape for building voice agents shifting lately, it feels like we re moving away from heavy, manual API orchestration toward something more streamlined.
How you re currently architecting voice agents. Specifically: Have you used the Model Context Protocol (MCP) to build or provide real-time data/context to your voice agents? Does it actually streamline your tool-calling, or is it more trouble than it's worth?
Would love to hear what's working (and what's breaking) in your current workflow. Drop your thoughts below!
There's never been a better time to build. AI tools, smaller teams, faster product cycles.
Last year, @Supabase surveyed over 2,000 startup founders and builders to uncover what's powering modern startups: tech stacks, GTM, and approach to AI. [1]
Many things have changed since then, and they want to know what building at startups looks like in 2026.
Someone told me: "Just be consistent. Post every day. The algorithm rewards consistency."
So I did.
For six months, I posted every single day. Sometimes at 7am. Sometimes at 10pm. Weekends included. I wrote about our product, our features, our roadmap. I followed all the "best practices" hook in the first line, three takeaways, call to action at the end.
Let me start from the creator s perspective: I personally don t have a product (apart from hiring people for creative work or offering personal consultations).
But as a creator, I constantly share content, insights, and information, value that helps me build trust (for free). Based on that perceived expertise, people eventually decide to work with me (a paid service).
