For GenAI, we can tolerate some level of probabilistic behavior because there's usually a human in the loop and an opportunity to correct mistakes. But when AI is taking actions autonomously through agents, even a 0.1% error rate can create significant friction. How are you solving this reliability problem in your workflows?

Still your agent can deflect from the purpose for which it was built, you can not stop, lets be honest LLMs are yet black boxes and their models rely on hyper data training, but what you can do is to track real time your agent behavior and for that use db.zizka.ai , many are using it already

zizka.ai - AI that executes tasks (not just suggests)

Thread on why this matters:

Hello Founders,

We are launching Zizka.ai, a product that is the antithesis of the autonomous AI buzz. The product is built with EU-grade privacy and follows an API-led approach no MCPs, just API-driven actions.

Any suggestions from experts here who have already launched similar products?

LLMs are perfect for content generation but hallucination is inbuilt so how to trust it for execution?

In my opinion hardcoded, built with purpose and guardrailed llms can perform better ! what you think?

There s so much hype around agentic AI right now, but how many of you are actually using it in your daily workflows?If yes, what s the one platform or execution system you fully trust with your real work, especially one that offers true industrial-grade privacy and security?

Now imagine something new that seamlessly connects all your productivity tools (Gmail, Calendar, Notion, Asana, Jira, ClickUp, HubSpot, etc.) and lets you run complex operations through simple natural language, all from one unified window .