Two questions I couldn’t stop thinking about

2026-07-26 · Source: AI on Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, medium

Summary

The author's motivation for building "Otto," an agent-orchestration gate, stemmed from two critical challenges in multi-agent workflows. First, the author's personal pipeline, involving agents like Claude Code, Gemini, and Codex for research, design, and implementation, required manual context transfer between these disparate tools. Existing orchestration solutions, such as Emdash or Claude Squad, focused on parallel execution rather than sequential, human-steered relays, while team platforms like n8n or Copilot Studio lacked support for unstructured context. This made the author a "context courier" for cross-vendor handoffs, despite wanting to retain high-value human judgment. Second, there was no shared team workflow for this multi-agent process, hindering collaboration and making feedback costly once architectural decisions were locked in. These gaps highlighted the need for a system that automates cross-vendor sequencing and synthesis while preserving human steering and enabling team-wide participation.

Key takeaway

For AI Architects or ML Engineers designing multi-agent systems, recognize that current orchestration tools often fail to bridge diverse vendor agents or facilitate team collaboration in sequential workflows. If your team manually shuttles context between tools like Claude Code and Gemini, consider building or adopting a solution that automates these handoffs while preserving critical human steering. This approach prevents bottlenecks and enables genuine team participation throughout the development lifecycle, rather than just post-facto reviews.

Key insights

Manual context transfer between diverse AI agents hinders sequential workflows and team collaboration.

Principles

• Automate cross-vendor agent handoffs.
• Integrate human judgment into agent relays.
• Foster team collaboration in agent pipelines.

Topics

• Agent Orchestration
• Multi-Agent Systems
• AI Workflow Automation
• Human-in-the-Loop AI
• Cross-Vendor Integration
• Team Collaboration

Best for: AI Product Manager, Entrepreneur, AI Engineer, Machine Learning Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI on Medium.