Build Daily
Tinley Park · August 23, 2026How Toyota Uses Deep Agents to Speed Up R&D and Manufacturing Research
Ravi Chandhu from Toyota explains how deep agents accelerate R&D and manufacturing research by integrating institutional knowledge across various car systems. He highlights how tools like Langsmith help monitor agent performance and improve outcomes.
The outline
Tap a timestamp to jump there in the video.
Introduction to Toyota AI Research
Ravi Chandhu introduces his role in Toyota's AI and product research, focusing on R&D GPT as a key use case.
Importance of R&D in Car Quality
He explains how Toyota's extensive research efforts directly impact the quality of car features like paint and seats.
Deep Agents Concept
The concept of deep agents is described as a single command that creates an ecosystem of tools to enhance research capabilities.
Integrating Car Ecosystem Tools
Deep agents connect with various car systems like paint and corrosion to search for solutions in R&D data.
Enterprise AI Skills
Toyota has developed custom skills in branding, research, manufacturing, and supply chain to feed institutional knowledge into deep agents.
Langsmith Monitoring Tools
Langsmith's Poly and Insights features help monitor the end-to-end agent ecosystem and identify outliers for improvement.
Deep agents can compress years of manufacturing research into a single command, making institutional knowledge accessible rather than siloed. For solo builders, this suggests that integrating domain-specific context is often more valuable than adding complex features.