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Defending Against Bots At Scale

Defending Against Bots At Scale

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About this listen

Stu Solomon, CEO of HUMAN, joins Amir to unpack a blind spot most teams underestimate: a huge share of online activity is not people at all, it is automated traffic. They break down how verification really works at internet scale, why agentic workflows change the rules, and what it will take to build trust when bots transact with bots.


If you have ever wondered how fraud, fake clicks, account abuse, and synthetic behavior get caught in real time, this episode is a clear, practical look behind the curtain.


Key takeaways

• Most of the internet is machine traffic now, the goal is no longer spotting bots, it is separating good machines from bad ones

• Trust is built by combining behavior, infrastructure signals, and identity or credential history into fast decisions at scale

• Agentic systems lower the barrier to entry for attackers, less skilled actors can now create outsized impact

• The hard part is accountability, when a machine acts with your authority, who owns the outcome

• Adoption follows convenience, but visibility matters, if it feels like a black box, people will not trust it


Timestamped highlights

00:33 HUMAN in plain English, making split second decisions about who is human, and whether they are safe

03:59 The trust stack, behavior signals, infrastructure clues, and identity or credential history

10:19 The real shift with AI, lower barriers for attackers, plus the rise of agentic autonomy

14:37 The cake story, an agent completes the task, then surprises you with a 750 dollar bill

17:22 Bots talking to bots, where accountability and liability get messy fast

24:18 Security builds trust, trust unlocks adoption, and society is already closer than it thinks


A line you will remember

“We have always operated on the notion that if you are human, you are good, and if you are a machine, you are bad. That is simply not the case anymore.”


Practical ideas you can use

• Add guardrails when you delegate to tools, especially budgets, limits, and approval steps

• Watch for trust signals, not just identity checks, behavior plus infrastructure plus history beats any single data point

• Design for visibility, show users what the system did and why, so trust can compound over time


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