Compare

HELM vs AI Agents

AI agents can propose and attempt work. HELM checks whether the proposed side effect is allowed before it runs.

Where AI agents is useful

Use it when the work fits the category.

Planning, drafting, research, summarization, coding assistance, and proposing structured work.

Where it breaks

The agent has enough tool access to turn a proposal into a real side effect without a separate authority boundary.

HELM difference

HELM treats model output as a proposal. It checks policy, approval, connector scope, risk, and proof before execution.

Operating model comparison

Question	AI agents	HELM
Authority	Usually lives in prompt instructions, workflow configuration, or human habit.	Authority is checked before a side effect can reach a tool, connector, data store, release path, or customer channel.
Failure mode	The system may keep going if the model, workflow, or credential has enough access.	Missing policy, approval, scope, risk, or proof returns DENY or ESCALATE.
Evidence	Logs may exist, but the decision path is often scattered across tools.	Receipts, ProofGraph edges, and EvidencePacks make the decision reviewable.
Code reality	Engineering agents often rely on search, generated plans, comments, or stale docs.	Code Intelligence Graph evidence pins repo commit, impacted symbols, routes, affected tests, read_set, write_set, CodeIndexReceipt, and CodeImpact.
Hostile inputs	Tool outputs, MCP servers, webpages, docs, and comments can become hidden instructions.	Unknown or hostile sources are quarantined or denied before they can influence execution.
Real-world effects	Workflow tools may treat refunds, vendor dispatch, logistics, or device commands like ordinary digital actions.	Analog and kinetic gateway actions require bounded scope, approvals, safety contracts, telemetry, and EvidencePacks.
Review	Review often happens before configuration or after incident response.	The reviewable object is the governed action and its receipt.