Platform Resilience & AI Customer Mode Enhancements — June 8, 2026

It's been a long day, but I accomplished a lot when it comes to building out system resilience of the AI customer mode for the Tavus agent. I ensured that the deployment process is more resilient for failures and rollbacks. One of the more important things I did is to implement the functionality to retain a rollback snapshot of the last good build. If a new build fails during deployment or runs out of memory, the system will automatically roll back to the last good build. This is a game change because it removes the risk of a system being half built that will crash on startup.

I also addressed a few other customer experience problems. I resolved a bug where the light line on the dark Portal Details panel line was causing a visual problem. I improved the visibility of the border by selecting a new color that provides better contrast to the background. The improvements provide a more refined look to the user interface.

One of the most incredible features I released today is the AI customer mode trigger for the Tavus agent. Now, when users say the phrases, ‘customer mode’ or ‘let’s go into customer mode,’ the Tavus agent instantly begins its full customer interaction flow. This entails stating goals, asking for the user’s name, and driving toward a single goal. This is a major improvement that will help users guide through their interactions in a more effective manner and will help to improve the overall experience.

I also looked at the escalation follow-up and made sure when a purchase is made that the agent is able to adequately capture the buyer's information. This is vital for tracking conversions as it allows us to see which visitors have successfully completed a transaction. I relocated the AI call escalation throttle per visitor to ensure that repeat visitors are treated differently with regards to the call duration allowing for a more seamless experience as they interact with the system.

I made a lot of progress, but it wasn't without its fair share of challenges. One such bug occurred in relation to the product catalog being truncated in the Tavus conversational context. I spent a lot of time diagnosing this issue to check if endpoints were returning data correctly, and then I moved on to check how the catalog was being passed in the call context. I was able to resolve this by moving the product catalog to the front of the context and increasing the downstream cap for context size. This was a good reminder that small tweaks can have big effects on the system as a whole.

Another hurdle was figuring out how the AI agent would communicate to users how much time they had left during calls. I incorporated a feature that will warn users 30 seconds prior to the call ending, and I think that it adds a more professional touch to the call. This also allows users to stay engaged during the entire call because they will be prompted to wrap things up.

Looking back on the work completed today, I am proud of the progress that I made, and I am aware of the time that was needed to overcome a lot of the obstacles that I faced. Building this platform myself while also utilizing AI tools like Claude Code in VS Code, has taught me to be more resilient and adaptable, and I have learned a lot because of it. Every commit I make is a feature, and it brings me that much closer to reaching my goal of creating a one-man-show business that is valued at a billion dollars. The road is long, but every little bit gets me closer to that goal.