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Securing AI agents at the scale of the internet
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Travis Muhlestein PRO
TravisMuhlestein
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posted an update 9 days ago
What if a “team” is just a set of agents?
We tend to think of agents as tools that help engineers.
But this example flips that model.
A set of prompt-native agents is handling security workflows that would normally involve multiple roles — without relying on traditional codebases.
Instead of: engineer → tool → output
It becomes: agent → execution → continuous operation
That changes how you think about systems:
No explicit task queues
No role-based handoffs
Minimal code as the coordination layer
The system is defined more by prompts and interactions than by code structure.
This raises interesting questions:
Where do you enforce correctness in a system like this?
How do you debug behavior without traditional code paths?
What replaces “ownership” when the work is distributed across agents?
🔗 https://www.godaddy.com/resources/news/the-zero-code-security-team-shifting-left-with-prompt-native-ai-agents posted an update 15 days ago
From AI Outputs to AI Execution: Why Identity Comes First
AI agents are moving beyond the “safe zone” of generating drafts, recommendations, and insights that require human action.
With systems like Salesforce Agent Fabric and MuleSoft, agents can now execute directly inside enterprise environments — calling APIs, updating records, and triggering workflows.
This shift changes the problem.
It’s no longer about evaluating outputs.
It’s about controlling execution.
Once agents can act, identity becomes critical — not just to verify who an agent is, but to determine what it is allowed to do before any action takes place.
This is where Agent Name Service (ANS) comes into play.
ANS moves identity to the front of the decision layer, enabling systems to establish permissions and trust boundaries prior to execution.
In an agentic architecture, trust is not something you validate after the fact — it’s a prerequisite to action.
More details on how this integrates with MuleSoft:
https://blogs.mulesoft.com/news/verify-agent-identity-mulesoft-godaddy-ans/ posted an update 23 days ago
What happens after agent deployment becomes easy?
As platforms like Salesforce’s Agent Fabric reduce the friction of building and orchestrating agents, a new pattern starts to emerge.
The complexity doesn’t stop at creation. It starts after deployment.
Once agents are distributed across systems, APIs, and workflows, they effectively become part of a larger system.
That introduces new challenges:
- Tracking where agents are operating
- Understanding behavior across environments
- Managing interactions between agents and systems
Maintaining consistency at scale
In that sense, agent pipelines don’t just create agents.
They create distributed systems.
And those systems require a different level of visibility and coordination than isolated tools.
Open questions:
- How do we observe agents once they’re deployed?
- How do we manage behavior across systems?
- What does control look like post-deployment?
🔗 https://www.salesforce.com/news/stories/agent-fabric-control-plane-announcement/ Organizations
published an article 7 months ago