Insights into the core challenges and opportunities of artificial intelligence.
At Parloa, our AI agents handle these long conversations every day, i.e., tool-heavy dialogues where context grows fast and ambiguity grows faster. And we wanted to know: does performance actually degrade when conversations get that long or do today’s models hold steady?
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At Parloa, our AI agents handle these long conversations every day, i.e., tool-heavy dialogues where context grows fast and ambiguity grows faster. And we wanted to know: does performance actually degrade when conversations get that long or do today’s models hold steady?
We’ve been quietly testing OpenAI’s GPT-5.1. We’ve been running it through a series of internal real-world benchmarks, especially for tool calling and instruction following, which are foundational to how customer service agents operate inside Parloa’s AI agent management platform.
We’re introducing a hierarchical Bayesian model for A/B testing AI agents. It combines deterministic binary metrics and LLM-judge scores into a single framework that accounts for variation across different groups.