// Stratum Praxis · Agentic Operations
Before you give an AI agent more autonomy, decide exactly what it is allowed to do.
Coding agents, remote-control workflows and managed agents can compress real work. They can also amplify bad instructions, unsafe permissions, duplicate actions and unverified assumptions. This audit identifies the first workflow worth automating and defines the controls around it before production rollout.
$499
Buy the audit - $499
Estimate workflow ROI first
What we evaluate
Workflow economicsFrequency, labor cost, delay cost, error cost, expected savings and implementation effort.
Agent boundariesWhat the agent may read, draft, execute, change or never touch without explicit approval.
Human checkpointsApproval gates for spending, publishing, deleting, sending, deploying, changing credentials or touching production data.
Failure handlingRetry limits, stop conditions, rollback, duplicate-action protection and evidence required before declaring success.
Context designDurable instructions, project files, handoff state and the minimum context needed for repeatable execution.
MeasurementBaseline, target metric, event tracking and the evidence needed to prove the workflow created value.
Best-fit use cases
- Long-running coding or research tasks that need structured human review rather than constant supervision.
- Recurring operations where an agent can read, classify, draft, compare, summarize or prepare actions before approval.
- Internal content, analysis or reporting workflows with clear inputs and outputs.
- Teams experimenting with Codex, Claude Code, Antigravity, managed agents or similar tools and unsure where autonomy is economically justified.
What you receive
- A map of one selected workflow: trigger, steps, systems, owners, handoffs and failure points.
- 5-10 automation candidates ranked by expected value, implementation effort and operational risk.
- A permission matrix separating read, draft, execute, publish, delete and financial actions.
- Explicit human-approval gates, retry ceilings, stop rules and rollback checkpoints.
- ROI scenarios with transparent assumptions that can be replaced with your own numbers.
- A 30-day pilot plan and the minimum measurement events needed to evaluate it.
The operating pattern
Observe → choose → act → verify → keep. The agent first reads the current state, selects one reversible action tied to a target metric, executes within a constrained permission boundary, verifies the result from independent evidence, and only then persists the change. Failed verification stops the loop rather than triggering endless retries.
What we do not recommend
- Giving a general-purpose agent unrestricted access to production systems.
- Allowing autonomous spending, payouts, credential changes or irreversible deletion.
- Using unverified social-media claims as proof of ROI.
- Mass outreach, scraping or high-frequency automation that can trigger abuse controls or violate platform terms.
- Declaring deployment, purchase, delivery or conversion success without evidence.
Data safety
Do not send passwords, API keys, authentication tokens, payment-card data, raw customer PII, government IDs or other regulated data. Redacted or synthetic examples are enough for the audit.
Turn one agentic workflow into a controlled business system.
Start the workflow audit - $499 Review the sample firstThe audit provides workflow analysis and implementation planning, not security certification, legal advice or guaranteed financial results. Production permissions and controls must be independently validated before rollout.