Latest news, guides, and best practices for AI workflow automation

Alexandr Chibilyaev on the A2A (Google) and MCP (Anthropic) protocols in AACFlow — open standards that let agents delegate tasks and connect to any external tool.

Alexandr Chibilyaev on long-term memory for AI agents: Leveraging Mem0, Zep, and RAG on pgvector to ensure your agents retain context, learn from every interaction, and drive real business value.

Alexandr Chibilyaev on multi-agent orchestration in AACFlow: the A2A protocol, parallel execution, and Mothership architecture for managing teams of AI agents.

Alexandr Chibilyaev explains why an AI agent in AACFlow is a first-class entity with memory, tools, and protocols — not just an API call to ChatGPT.

Alexandr Chibilyaev shares how personal frustration with broken automation led to the creation of AACFlow — the robust infrastructure where 60,000+ developers run production-grade autonomous AI agents.

AACFlow launches real-time multiplayer collaboration powered by Socket.IO and Redis. Multiple team members on the same canvas simultaneously — with cursor presence, conflict resolution, and live sync. Alexandr Chibilyaev on why AI agents are a team sport.

AACFlow launches a ReactFlow-based visual DAG editor. Drag, drop, connect, configure — and compile directly to an optimized execution plan. Alexandr Chibilyaev on building the no-code agent builder that runs 10M+ executions per month.

AACFlow now offers 300+ AI agent tools spanning communication, CRM, e-commerce, payments, AI models, infrastructure, marketing, HR, and logistics. Alexandr Chibilyaev on the tool registry architecture and what it unlocks.

AACFlow crosses two major milestones: 60,000+ developers on the platform and 10 million agent executions every month. Alexandr Chibilyaev shares the metrics, the engineering lessons, and what comes next.