Rigid tools held back 5,000 staff. Now, bottom-up experimentation lets designers build functional prototypes without developer support.
A leading design and collaboration platform with over 5,000 employees sought to scale generative AI adoption across its technical and creative workforce.
Rapid advancements in AI models meant a single-vendor strategy could not adequately support diverse needs ranging from engineering code to design...
“We knew it was up to us to give our team the space and time to test, learn and discover what good prompting looks like.”
Canva's Product development is part of this use case:
Graphic design platform for visual communication and collaborative content creation.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Related implementations across industries and use cases
Static designs required manual coding. Now, teams turn pixels into working apps in 5 minutes, testing interactive flows instantly.
Isolated tools bottlenecked remote work. Now, Slack emojis trigger code merges and prototypes launch live in customer calls.
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
Isolated AI tools fragmented engineering workflows. Now, embedded agents run dozens of concurrent tasks, routing outputs for human review.
Static spreadsheets bottlenecked approvals. Now, non-technical staff use AI to build guided, interactive workflows in minutes.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Rigid tools held back 5,000 staff. Now, bottom-up experimentation lets designers build functional prototypes without developer support.
A leading design and collaboration platform with over 5,000 employees sought to scale generative AI adoption across its technical and creative workforce.
Rapid advancements in AI models meant a single-vendor strategy could not adequately support diverse needs ranging from engineering code to design...
“We knew it was up to us to give our team the space and time to test, learn and discover what good prompting looks like.”
Canva's Product development is part of this use case:
Graphic design platform for visual communication and collaborative content creation.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Related implementations across industries and use cases
Static designs required manual coding. Now, teams turn pixels into working apps in 5 minutes, testing interactive flows instantly.
Isolated tools bottlenecked remote work. Now, Slack emojis trigger code merges and prototypes launch live in customer calls.
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
Isolated AI tools fragmented engineering workflows. Now, embedded agents run dozens of concurrent tasks, routing outputs for human review.
Static spreadsheets bottlenecked approvals. Now, non-technical staff use AI to build guided, interactive workflows in minutes.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.