Executive summary

Full Auto is the destination state where eligible workflows run autonomously within agreed reliability, quality and cost envelopes. We operate with explicit SLOs, hardened rollback paths and an instant kill-switch. Observability and budget controls are built-in so you can scale safely and predictably.

1) Objectives & scope

• Deliver autonomous execution on the happy path with strict SLO/SLA adherence.

• Enforce fast and reversible changes: feature flags, canary routes, instant rollback and kill-switch.

• Maintain deep observability (tracing/metrics/logs) and cost telemetry with hard budgets.

• Keep humans in the loop only for policy-sensitive or out-of-scope exceptions.

2) Operating model — autonomy by design

• Policies as code; routes and prompts versioned; approvals required for policy-impacting changes.

• Canary then promote: every change ships behind a flag, promoted only after gates pass.

• Exception queues exist but are low-volume; escalations follow incident runbooks.

• Auditability: every action is traceable with input/output hashes and rationale when applicable.

3) SLOs & SLAs — reliability, quality, cost

Metric

SLO (target)

SLA (guarantee)

Measurement

Notes

Quality (evaluator median)

≥ 0.88

≥ 0.85

Task-specific evaluators on ≥5% sample

Tighter gates than Co‑pilot

Latency (p95)

≤ 2.5s/step

≤ 3.0s/step

Per step during business hours

Includes retrieval/cache

Uptime (workflow)

≥ 99.7%

≥ 99.5%

Synthetics + traces

Excludes planned maint.

Exception rate

≤ 8–10%

≤ 12%

Dashboards

Eligible scope only

Cost per item

−25–35% vs baseline

Within budget cap

Cost telemetry

Alert at 80% of cap

4) Rollback & kill-switch — instant reversibility

Every deployment includes a pre-validated rollback plan and a kill-switch for rapid containment.

Trigger

Action

Permission

Downtime target

Post-action

Sev1 incident

Kill-switch to safe mode

Supervisor or higher

< 5 min

Notify, RCA < 24h, change freeze

Quality regression

Rollback route/policy

MLE/On-call

< 15 min

Open defect; add test

Cost spike

Throttle or switch model

Ops lead

Immediate

Budget review; prompt compression

Policy violation

Revert to last compliant policy

Security

< 15 min

Audit sample; update guardrail

5) Observability — tracing, metrics, logs

We instrument end-to-end tracing, business metrics and detailed logs for audits.

Signal

Definition

Target/Alert

Retention

Evaluator median

Quality per task

Alert if < 0.85

12–24 months

Latency p95

Time per step

Alert if > 3.0s

12 months

Exceptions %

% requiring human review

Alert if > 12%

12 months

Error rate

Failures per 100 items

Alert if +50% vs baseline

24 months

Drift

Input/quality/cost drift

Alert on threshold

12 months

Spend & tokens

Cost/item, daily spend

Alert at 80/90% of cap

24 months

6) Budget control — tokens and spend

Budgets are enforced per workflow with route-level caps and anomaly detection.

Budget item

Cap

Early warning

Auto-response

Owner

Tokens/item (p95)

≤ 3.0k

80% of cap

Compress prompts; increase cache; smaller model

MLE

Cost/item

≤ $0.08

$0.06

Route to cheaper model; truncate contexts

Ops lead

Daily spend (workflow)

$X/day

85% of cap

Throttle; delay non-urgent sends

Finance + Ops

Cache hit rate

≥ 40%

< 30%

Review retrieval; warm cache

MLE

7) Change management — safe promotions

• All changes behind feature flags; canary exposure 5–20% before promotion.

• Promotion requires gates: tests pass, evaluators stable, spend within policy, no new violations.

• Automatic rollback on gate failure; change logs and approvals stored with artifacts.

8) Incident management — respond, recover, learn

Severity and response targets:

Severity

Example

Initial response

MTTR target

Postmortem

Sev1

Customer impact/incorrect external send

Kill-switch; page on-call

< 2 hours

Within 24h w/ actions

Sev2

Internal impact/quality drop

Rollback; notify stakeholders

< 6 hours

Within 48h

Sev3

Degraded KPIs/cost drift

Throttle; route change

< 24 hours

Weekly review

9) Security & compliance

• RBAC with least privilege; policy-based approvals for irreversible/external actions.

• Data residency honored per region/VPC; logs and backups pinned to region.

• PII handling: masking/redaction; purpose limitation; retention and audit access.

• Compliance pack: MSA/DPA; audit log schema; evidence for vendor assessments.

10) Data lifecycle — retention, deletion, backups

• Retention: business metrics 12–24 months, audit logs 24–36 months, raw inputs as per policy.

• Deletion: subject requests honored; verified via audit trail.

• Backups: encrypted, tested via monthly restore drill; RPO ≤ 24h.

11) KPIs — continuous improvement in Full Auto

KPI

Definition

Quarterly target

Owner

Throughput

Items per week

+15–30% QoQ

Ops

Cost per item

All-in

−10–15% QoQ

Finance + MLE

Defects

Per 100 items

−20–30% QoQ

Ops + QA

Uptime

Workflow availability

≥ 99.7%

Ops

Exception rate

% requiring review

≤ 8–10%

Ops

12) RACI — who owns what in Full Auto

Role

Responsibilities

R

A

C

I

Ops Lead

SLOs, incidents, promotions

R

A

C

I

MLE/Engineer

Routes, evaluators, telemetry

R

C

I

Security/Legal

Policies, audits, DPA

A

R

I

Finance

Budgets, anomaly review

A

C

I

Supervisor

Approvals for risky actions

R

A

C

I

Product Owner

Priorities, scope changes

A

C

I

13) Runbooks — day/week/month

Daily: check SLO dashboards, exceptions %, latency p95, spend; triage alerts; sample outputs.

Weekly: review incidents; tune routes; update evaluator datasets; policy review; change log.

Monthly: budget rebase; DR drill; audit sample; KPIs review; capacity planning.

14) Risks & mitigations

• Silent drift → detectors + gates; freeze promotions on signal; roll back routes.

• Cost creep → stricter budgets; prompt compression; cache strategy; cheaper routes.

• Policy regression → mandatory reviews; tests on policy; change tickets.

• Over-automation → keep exception sampling; periodic human QA; keep HITL path ready.

15) FAQ

Q: How do we decide what is safe for Full Auto?
A: Use the graduation gates from Co‑pilot and only include steps with stable quality, low risk and controllable cost.

Q: Can we run Full Auto on‑prem or in our VPC?
A: Yes. We support sovereign deployments with open‑source stacks and regional residency.

Q: What happens if a regulation changes?
A: Policies are versioned; updates are rolled out behind flags with red‑team tests and audits before promotion.

Book a 30’ Full Auto review

Email: contact@smartonsteroids.com — we’ll validate SLOs, budgets and rollback plans for safe autonomy.

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