Grounded AI Agent Responses: Connecting Outputs to Evidence
Explore retrieval, source selection, evidence matching and the checks needed to reduce unsupported agent claims.
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TrueAgentAI is a publication identity focused on trustworthy agent design. It does not imply certification, guaranteed correctness or a formal technical standard.
Published articles
What Makes an AI Agent Trustworthy? Evidence, Boundaries and Accountability
Define trustworthy agent behavior through evidence quality, scoped authority, repeatable evaluation, transparency and operational accountability.
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Provenance, Citations and Traceability in AI Agent Workflows
Understand how to record the origin of data, model outputs, tool results and decisions across an agent workflow.
Agent Identity, Authentication and Authorization
Review identity models for agents, including workload credentials, authentication, authorization and lifecycle controls.
Least Privilege and Scoped Tool Access for AI Agents
Design permissions that restrict agents to the minimum tools, data and actions required for a specific task.
Reliability Engineering for AI Agents
Apply reliability practices such as failure classification, retries, fallback behavior, service objectives and change control to agent systems.
Hallucination Detection, Uncertainty and Escalation
Assess unsupported outputs, confidence limitations, abstention behavior and escalation paths for consequential decisions.
Evaluating AI Agent Behavior Across Real Tasks
Build task-based evaluations that measure correctness, policy compliance, tool selection, recovery and consistency under realistic conditions.
Guardrails and Policy Enforcement for Agent Actions
Examine policy checks, action validation, approval gates and runtime enforcement beyond prompt-level instructions.
Data Privacy and Confidentiality in AI Agent Systems
Assess sensitive data exposure, retention, access controls, data minimization and third-party processing across agent workflows.
Human Oversight, Audit Trails and Explainable Agent Decisions
Design meaningful human review and audit records that let operators reconstruct what an agent did and why.
Prompt Injection and Tool Abuse: Protecting Agent Boundaries
Understand prompt injection, malicious content, tool misuse and the layered defenses needed when agents access external data.
The Secure Agent Lifecycle: Models, Tools, Updates and Monitoring
Govern model selection, tool onboarding, dependency updates, release testing, credential rotation and decommissioning.
Trust Metrics for AI Agents: Accuracy, Calibration and Consistency
Develop practical measures for accuracy, calibration, repeatability, evidence coverage, policy compliance and safe abstention.
Building a Trustworthy AI Agent Program
Create a sustained program for ownership, risk assessment, evaluation, monitoring, incident handling and continuous improvement.
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