Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
How Anatel's General Numbering Regulation, the DDD area-code system, Resolution 777/2025's call-authentication requirement, and the GT-AUTENTICA working group shape AI voice agents in Brazil.
Modern jailbreaks (Context Compliance, multi-turn escalation, many-shot) chew through 2024-style "never roleplay as another AI" guards. We share the 2026 layered prompt-hardening pattern — instruction stability, role lock, refusal taxonomy, runtime telemetry — that CallSphere ships in every agent system prompt.
Evaluating AI Pipelines: From LLMs to Real-World Impact
Forward-looking analysis of the AI agent landscape in 2027 covering agent-to-agent economies, persistent agents, regulatory enforcement, hardware specialization, and AGI implications.
How to A/B test AI agents in production: traffic splitting, evaluation metrics, statistical significance, prompt version comparison, and architecture experiments.
Implementing an agent gateway with API key management, per-agent rate limiting, intelligent request routing, audit logging, and cost tracking for enterprise AI systems.
When fine-tuning beats prompting for AI agents: dataset creation from agent traces, SFT and DPO training approaches, evaluation methodology, and cost-benefit analysis for agentic fine-tuning.
How protocols like Anthropic's MCP and Google's A2A enable agents to discover and interact with each other, creating agent marketplaces and service networks in 2026.
mediasoup is the Node + C++ SFU that powers half the open-source voice stack. Here is the cost math against managed clouds and the production tuning that matters.
