> For the complete documentation index, see [llms.txt](https://docs.lpp-minduniverse.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lpp-minduniverse.org/lingua-pactum-protocol-lpp-documentation/6.-intent-and-trajectory-governance/6.8-cumulative-externality.md).

# 6.8 Cumulative Externality

AI-agent trajectories can create consequences cumulatively.

A single action may be minor.

A sequence of individually minor actions may not be.

**Cumulative Externality** describes the governance significance of external effects that accumulate across a trajectory.

#### Individual Action vs Combined Effect

Consider:

```
Action 1:
Change one configuration parameter
```

```
Action 2:
Change another parameter
```

```
Action 3:
Restart one service
```

```
Action 4:
Propagate the configuration
```

Each action may appear reversible or locally acceptable.

Together they may create:

* major production disruption,
* broader privilege,
* irreversible system state,
* financial exposure,
* institutional commitment,
* or another materially higher consequence.

Therefore:

```
Consequence(Action₁)
+
Consequence(Action₂)
+
...
+
Consequence(Actionₙ)
```

cannot always be governed as if each action existed independently.

#### Cumulative Externality and T-Class

The LPP T0–T4 classification applies to consequence and irreversibility.

Trajectory governance introduces the possibility that the effective consequence of a sequence becomes more significant than the local classification of an individual step suggests.

The exact class-mapping rules remain profile-dependent.

The canonical governance principle is:

> **The system must not ignore accumulated external consequence merely because each component action appears individually limited.**

#### Why This Matters for Agents

Autonomous agents are optimized to decompose complex objectives into manageable steps.

That capability creates a governance challenge.

A high-consequence objective may be fragmented into many operations that each appear low consequence.

Trajectory governance prevents decomposition from becoming a method of bypassing consequence-aware admission.

***

###