OpenAI Frontier: New Enterprise Platform to Build and Deploy Agents
OpenAI Frontier — the new enterprise platform announced this week for building, deploying, and managing AI agents that do real work.
8 min read
Archive page 467 of 1224
AI Voice Agent Insights & Guides
Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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AI Agent M&A Activity 2026: Aircall–Vogent, Meta–PlayAI, OpenAI's Six Deals
Q1 2026 saw a record acquisition wave: Aircall bought Vogent (May), Meta acquired Manus and PlayAI, OpenAI closed six deals. The voice AI consolidation phase has begun.
10 min read
IT Helpdesk Stack 2026: CallSphere Tier-1 + Project Arc Tier-2
ServiceNow Project Arc handles desktop tickets for Tier-2 engineers. CallSphere handles Tier-1 voice. Here is how to layer them for a real-world helpdesk.
8 min read
SWE-bench in 2026: How to Evaluate Your Coding Agent Like Anthropic and OpenAI Do
A practical guide to running SWE-bench (and it Verified / Lite) on your own coding agent, plus the cheaper internal benchmarks that actually move the needle.
13 min read
Building OpenAI Realtime Voice Agents with an Eval Pipeline (2026)
Build a working voice agent with the OpenAI Realtime API + Agents SDK, then bolt on an eval pipeline that catches barge-in failures, hallucinated grounding, and latency regressions.
13 min read
Token-Level Evaluation of Streaming Agents: TTFT, Stream Smoothness, and Mid-Stream Hallucination Detection
Streaming changes the eval game — final-answer correctness isn't enough when users perceive the answer one token at a time. Here's the metric set that matters.
13 min read
Online vs Offline Agent Evaluation: The Pre-Deploy / Post-Deploy Split
Offline evals catch regressions before deploy on a fixed dataset. Online evals catch real-world drift on live traffic. You need both — here is how we run them.
13 min read
LLM-as-Judge: Why Pairwise Evaluation Beats Reference-Based Scoring for Agents
Pairwise (A vs B) LLM-as-judge evaluation produces sharper, more reliable signal than absolute scoring for non-deterministic agent outputs. Here is why and how.
12 min read
Evaluating Agent Reasoning Traces: Measuring Thought Quality Beyond Final Answers
Final-answer accuracy hides broken reasoning. Build an eval pipeline that scores the reasoning trace itself — coherence, faithfulness to tools, dead-end detection.
13 min read
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