Automating babysitting of multi-step AI conversations across platforms

Automating babysitting of multi-step AI conversations across platforms targets a $24.0B = 5M teams x $4,800 ACV. Rationale: target is teams and power-user groups across SMB and mid-market that would pay for a team-level productivity orchestration seat (~$400/month) to automate recurring AI workflows used in product, marketing, research, and ops. total addressable market with medium saturation and a year-over-year growth rate of 25-40% annual growth in tools enabling AI orchestration and agent workflows as enterprise adoption increases and more products add agent features.

Key trends driving demand: Multi-model usage -- teams increasingly use multiple public model UIs and vendors instead of a single API, increasing need for cross-platform orchestration.; Agentification of workflows -- more workflows are decomposed into multi-step chains that require continuation and monitoring, creating demand for automation of the orchestration layer.; Browser-level automation -- improved browser extension APIs and headless automation make it feasible to orchestrate across UIs without deep API integrations.; Open-source adoption -- community-maintained tools lower onboarding friction and accelerate testing cycles for niche productivity add-ons..