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TRACK 3

🛠️ Practical application

Turn predictions into a verifiable triage console.

2 modules 12 topics 70–100 min with practice 12 exercises
Understand Try Verify LAYA / INEMA · conceptual flow
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Track map

3.1 35–50 min

🛠️ Portuguese triage console

Use the application and understand its boundaries.

3.2 35–50 min

🛠️ Integration with agents and processes

Connect decisions without confusing prediction with permission.

Detailed content

MODULE 3.1

Triage console in Portuguese

Use the application and understand its boundaries.

What it is

The command serve starts a server at 127.0.0.1, port 8765 by default.

Why learn

The published guide on GitHub Pages is static documentation; the inference interface runs on the machine that executes Python.

Key concepts

Loopback

local access

Server

Python process

Pages

static site

Form

controlled input

What it is

The screen shows department, SDK confidence, urgency, cancellation threat, and a refund request.

Why learn

Start from the original text, check the suggested department, and look for contradictory signals.

Key concepts

Contextual reading

full meaning

Signal

bounded prediction

Distribution

alternatives

Recommendation

reviewable decision

What it is

review_policy takes validated responses and builds the routing.

Why learn

Separating policy and inference lets you modify operating rules without rewriting the encoder.

Key concepts

Policy

operational rule

Authorization

external permission

learned signal

is not permission

Review

human responsibility

What it is

POST /api/triage receives only message and subject.

Why learn

A consumer must check the HTTP status before using answers.

Key concepts

HTTP 200

result

HTTP 422

invalid input

HTTP 503

unavailability

Health

service state

What it is

The application does not automatically save the text of tickets.

Why learn

Running locally prevents sending the ticket to an external inference API, but the weights must be obtained from the Hub initially.

Key concepts

Minimization

only what’s necessary

Export

user choice

Weights cache

initial download

Retention

retention time

What it is

Run the server, load an example, analyze, inspect the JSON, and download the result.

Why learn

This test reveals real behavior without requiring a large benchmark.

Key concepts

Minimum batch

controlled change

Negation

semantic change

Record

preserved evidence

Version

distinct experiment

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MODULE 3.2

Integration with agents and processes

Connect decisions without confusing prediction with permission.

What it is

An integration starts with the event: ticket received, document imported, or an agent run completed.

Why learn

Don’t send the entire history for convenience.

Key concepts

Event

occurrence

Normalization

common format

Identifier

link

Deduplication

avoids repetition

What it is

The SDK Router chooses a Laya checkpoint.

Why learn

Use clear names in contracts: checkpoint, executor, and destination should not mean the same thing.

Key concepts

Checkpoint

Laya model

Executor

tool or agent

Destination

operational queue

Budget

spending cap

What it is

N0 through N4, present in the provided material, are an organizational proposal to level up autonomy.

Why learn

The model may provide signals used in the autonomy assessment; the final attribution must come from verifiable rules.

Key concepts

Autonomy

allowed scope

Level

local convention

Promotion

permission change

Context

impact of the action

What it is

The guardrails and moderation presets ask questions about attacks or problematic content.

Why learn

Separate command data and keep tool permissions out of the classified text.

Key concepts

Untrusted data

external input

Guardrail

additional signal

False negative

not signaled risk

Permission

independent control

What it is

The material proposes using fast decisions in cycles of running, observing, evaluating, and correcting.

Why learn

Do not reuse the support/agent outcome as if it were a code evaluation or an incident.

Key concepts

Note

actual result

Evaluation

criterion

Rollback

controlled return

Domain

specific distribution

What it is

Outline the path between event, validation, inference, policy, human queue, and eventual executor.

Why learn

The integration should remain understandable when the model is unavailable.

Key concepts

Audit

traceability

Fallback

alternative path

Queue

pending work

explicit failure

is not a prediction

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