Agentic Workflows Outpace Legacy Vendors

The winners in AI support are being determined by architecture, not just features. Older vendors were built around scripted flows, intent trees, and agent assist layers that assume a human stays in the loop, while newer products are built to read docs, reason through open ended requests, and take actions like refunds or cancellations inside connected systems. That makes it much harder for legacy products to match speed, setup simplicity, and autonomous resolution in one rewrite cycle.

• There have been three clear product generations. First came phone tree bots, then intent based bots that needed heavy manual rules, then LLM agents like Fin, Sierra, and Decagon that can answer natural language questions and resolve around 60% to 80% of conversations with far less workflow authoring.
  2 sacra 4 sacra 5 sacra
• Legacy vendors still carry the weight of their old product shape. Forethought built Autoflows on top of an earlier automation stack, Ada evolved from second generation chatbot software, and Zendesk bought Ultimate in March 2024 instead of building everything in house, a sign that incumbents often need M&A to close the architecture gap fast enough.
  1 sacra 2 sacra 3 sacra 6 sacra 7 zendesk 8 forethought
• The practical difference shows up in implementation. Newer agent vendors win by plugging into the help desk, ingesting knowledge, writing custom integrations, and going live in weeks, while older platforms often ask customers to map intents, tune rules, and manage more technical workflow setup before the agent can act reliably.
  2 sacra 3 sacra 4 sacra

From here, the market keeps moving toward full agents that both answer and act. That favors companies built around orchestration, testing, and system actions from day one, and pushes legacy vendors toward consolidation, deeper rewrites, and narrower enterprise niches where existing relationships can still outweigh product speed.