Unique Research · Insight / Unique Friend Q&A · January 19, 2024 · Guest: Yang Jinsong, founder & CEO, Future-Form / AutoAgents.ai (未来式智能)
Inventory type remains insight (Unique Friend series — not partner welcome).
Guest
Yang Jinsong — founder & CEO, Future-Form (AutoAgents.ai / 未来式智能). Former Feishu AI & Search product lead at ByteDance; previously led AWS aPaaS (~$200M annual revenue); SAP senior architect; Accenture consulting manager — clients include Sinopec, CNOOC, State Grid, Mengniu, New Hope, Xiaomi, Lenovo, FAW, BAIC, CRRC, TCL, Gree and peers.
Q&A
1. Product and core scenes?
AutoAgents.ai’s flagship is the enterprise Agent app builder Lingda (灵搭) — an LLM app tool for business users. It aims to overturn rigid workflows, help firms build intelligent generic business flows, and create a human–machine co-creation paradigm — toward 10× productivity for 1B knowledge workers worldwide. As an enterprise tech builder, AutoAgents.ai serves government, power/energy, finance, and internet leaders with Agents that reshape business flows. Live scenes: sales assist, itinerary booking, contract review, customer ops, vertical knowledge-base Agents.
2. Opportunities vs. past waves?
When Agents are mainstream and best practices are highly SOPized, firms that need top-tier domain know-how may simply buy it for an extra fee. Language-model-centric apps will also deliver more scenes and better experience, overturning classical software’s accumulated debt.
3. Competing with giants?
Many AI startups sit on foundation-model tech; if a feature or scene can be covered after a few model-vendor iterations, the risk is high. AutoAgents.ai stays alert: product and service start from customer efficiency and experience, and deposit vertical-scene depth — so whatever the underlying model does, the response stays tied to customer pain.
4. Human–machine collaboration?
Agents build a “human–machine hybrid super pipeline.” Hybrid intelligence means people and machines finish a complex task together via workflows: hard work stays human; automated subtasks go to optimized Agents. Orchestrate hundreds of subtasks, SOPs, reviews, and QA into a mixed-intelligence line — like Ford’s assembly line (presses plus people tightening bolts machines could not yet do). Knowledge work becomes a knowledge-era assembly line of human + Agent collaboration — not dogmatic full automation.
1 CN image; attach on ingest. Signup CTA in CN omitted.
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