Broken agent workflows — visualize and orchestrate agents with Kanban

Executive Summary

Many engineering and operations teams running multi‑agent automation today struggle with broken workflows: disparate agent handoffs, opaque LLM outputs, and no single place to visualize or rewind state make troubleshooting slow and risky. This affects a very large addressable base—roughly 200 million knowledge‑worker teams that spend about $600/year on collaboration and automation tools (a $120B market)—particularly product, support, analytics, and platform teams that run dozens to hundreds of daily automated tasks. A practical product is a Kanban‑style visual orchestrator that represents agents and steps as cards and columns, supports drag‑and‑drop composition, records immutable provenance for every LLM call and external action, and exposes APIs and webhooks so existing pipelines can adopt it incrementally. By combining LLM integrations, observability traces, and replayable execution logs, it would let teams root‑cause failures, author mitigation rules, and audit decisions without rewriting their orchestration layer. Market timing is favorable: LLM‑first tooling lowers choreography costs, enterprises increasingly demand auditability, and composable SaaS makes lightweight orchestration layers feasible—factors that align with a market score of 92/100 and a revenue potential score of 84/100. To stand out you must prioritize developer ergonomics, enterprise‑grade provenance and RBAC, and prebuilt connectors to major platforms—differentiators that address the medium level of competition but require upfront investment in reliability and security. Challenges include integration friction, evolving LLM behavior, and the hard sell of a new control plane, so this is worth pursuing if you can secure 10–20 pilot customers quickly, demonstrate measurable MTTR or auditability improvements, and budget for heavy integration and compliance work.