WORKSHOP
NOV 17
9AM PT / 12PM ET
9AM PT / 12PM ET
SEPT 16
Live Build
Live Build
Identifying agentic traffic without blocking real customers
Can your app tell which AI agents are acting for real customers?
Treating every bot as a threat stops working when AI agents sign in, browse, and buy on behalf of real customers, and some, like Meta's Muse, don't identify themselves. 95% of US financial services leaders say AI and bot traffic on their web properties grew over the past year, and 40% say the risk their leadership fears most is customer churn from blocking a legitimate AI assistant. Blocking everything breaks real experiences, and allowing everything invites abuse.
In this one-hour live build, Keshia Rose codes a server-side automation policy layer from scratch, then points a real Muse session at it alongside a bot script and a human visitor. Follow along with the starter repo and bring questions about your own setup.
Register
We're committed to your privacy. You may unsubscribe from our communications at any time.
What you'll build
How to retrieve the full identification event server-side and tell humans, AI agents, and automation tools apart
How signed, verified, unknown, and spoofed agent identities should change how much you trust each visitor
How to write policies that allow, limit, verify, or block each kind of visitor
How Suspect Score separates risky unknowns from the rest of your automated traffic
SPEAKER
Keshia Rose
Sr. Developer Evangelist @ Fingerprint
Keshia Rose is a Senior Developer Evangelist at Fingerprint, where she helps developers build more secure and seamless online experiences. Through hands-on demos, technical workshops, and developer-focused content, she breaks down complex fraud prevention concepts into practical solutions teams can put into action. Her work helps developers better understand how device intelligence, risk signals, and modern fraud detection techniques can be used to identify suspicious behavior, stop abuse, and protect legitimate users without adding unnecessary friction.
Speakers
Keshia Rose
Sr. Developer Evangelist
@ Fingerprint
WORKSHOP
NOV 17
9AM PT / 12PM ET
9AM PT / 12PM ET
SEPT 16
Live Build
Identifying agentic traffic without blocking real customers
Can your app tell which AI agents are acting for real customers?
Treating every bot as a threat stops working when AI agents sign in, browse, and buy on behalf of real customers, and some, like Meta's Muse, don't identify themselves. 95% of US financial services leaders say AI and bot traffic on their web properties grew over the past year, and 40% say the risk their leadership fears most is customer churn from blocking a legitimate AI assistant. Blocking everything breaks real experiences, and allowing everything invites abuse.
In this one-hour live build, Keshia Rose codes a server-side automation policy layer from scratch, then points a real Muse session at it alongside a bot script and a human visitor. Follow along with the starter repo and bring questions about your own setup.
Register
We're committed to your privacy. You may unsubscribe from our communications at any time.
What you'll build
How to retrieve the full identification event server-side and tell humans, AI agents, and automation tools apart
How signed, verified, unknown, and spoofed agent identities should change how much you trust each visitor
How to write policies that allow, limit, verify, or block each kind of visitor
How Suspect Score separates risky unknowns from the rest of your automated traffic
SPEAKER
Keshia Rose
Sr. Developer Evangelist @ Fingerprint
Keshia Rose is a Senior Developer Evangelist at Fingerprint, where she helps developers build more secure and seamless online experiences. Through hands-on demos, technical workshops, and developer-focused content, she breaks down complex fraud prevention concepts into practical solutions teams can put into action. Her work helps developers better understand how device intelligence, risk signals, and modern fraud detection techniques can be used to identify suspicious behavior, stop abuse, and protect legitimate users without adding unnecessary friction.
Speakers
Keshia Rose
Sr. Developer Evangelist
@ Fingerprint
WORKSHOP
NOV 17
9AM PT / 12PM ET
9AM PT / 12PM ET
SEPT 16
Live Build
Identifying agentic traffic without blocking real customers
Can your app tell which AI agents are acting for real customers?
Treating every bot as a threat stops working when AI agents sign in, browse, and buy on behalf of real customers, and some, like Meta's Muse, don't identify themselves. 95% of US financial services leaders say AI and bot traffic on their web properties grew over the past year, and 40% say the risk their leadership fears most is customer churn from blocking a legitimate AI assistant. Blocking everything breaks real experiences, and allowing everything invites abuse.
In this one-hour live build, Keshia Rose codes a server-side automation policy layer from scratch, then points a real Muse session at it alongside a bot script and a human visitor. Follow along with the starter repo and bring questions about your own setup.
Register
We're committed to your privacy. You may unsubscribe from our communications at any time.
What you'll build
How to retrieve the full identification event server-side and tell humans, AI agents, and automation tools apart
How signed, verified, unknown, and spoofed agent identities should change how much you trust each visitor
How to write policies that allow, limit, verify, or block each kind of visitor
How Suspect Score separates risky unknowns from the rest of your automated traffic
SPEAKER
Keshia Rose
Sr. Developer Evangelist @ Fingerprint
Keshia Rose is a Senior Developer Evangelist at Fingerprint, where she helps developers build more secure and seamless online experiences. Through hands-on demos, technical workshops, and developer-focused content, she breaks down complex fraud prevention concepts into practical solutions teams can put into action. Her work helps developers better understand how device intelligence, risk signals, and modern fraud detection techniques can be used to identify suspicious behavior, stop abuse, and protect legitimate users without adding unnecessary friction.
Speakers
Keshia Rose
Sr. Developer Evangelist
@ Fingerprint
WORKSHOP
NOV 17
9AM PT / 12PM ET
9AM PT / 12PM ET
SEPT 16
Live Build
Identifying agentic traffic without blocking real customers
Can your app tell which AI agents are acting for real customers?
Treating every bot as a threat stops working when AI agents sign in, browse, and buy on behalf of real customers, and some, like Meta's Muse, don't identify themselves. 95% of US financial services leaders say AI and bot traffic on their web properties grew over the past year, and 40% say the risk their leadership fears most is customer churn from blocking a legitimate AI assistant. Blocking everything breaks real experiences, and allowing everything invites abuse.
In this one-hour live build, Keshia Rose codes a server-side automation policy layer from scratch, then points a real Muse session at it alongside a bot script and a human visitor. Follow along with the starter repo and bring questions about your own setup.
Register
We're committed to your privacy. You may unsubscribe from our communications at any time.
What you'll build
How to retrieve the full identification event server-side and tell humans, AI agents, and automation tools apart
How signed, verified, unknown, and spoofed agent identities should change how much you trust each visitor
How to write policies that allow, limit, verify, or block each kind of visitor
How Suspect Score separates risky unknowns from the rest of your automated traffic
SPEAKER
Keshia Rose
Sr. Developer Evangelist @ Fingerprint
Keshia Rose is a Senior Developer Evangelist at Fingerprint, where she helps developers build more secure and seamless online experiences. Through hands-on demos, technical workshops, and developer-focused content, she breaks down complex fraud prevention concepts into practical solutions teams can put into action. Her work helps developers better understand how device intelligence, risk signals, and modern fraud detection techniques can be used to identify suspicious behavior, stop abuse, and protect legitimate users without adding unnecessary friction.
Speakers
Keshia Rose
Sr. Developer Evangelist
@ Fingerprint
Identify your web and mobile traffic in minutes
Identify your web and mobile traffic in minutes
Start to collect visitor IDs and signals instantly for free.
Start to collect visitor IDs and signals instantly for free.
