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Manage a coding agent as a bounded contributor, not an autonomous maintainer. Give it a small, testable task; restrict its repository, tools, credentials, network, and workspace; require a structured report; inspect the complete diff; run relevant checks; and stop for human approval before any ambiguous, destructive, sensitive, or externally visible action.
This workflow lets an agent accelerate implementation without transferring ownership of design, security, or release decisions. The agent may propose and edit code, but a responsible engineer remains accountable for what enters the repository and what runs against real systems.
What “bounded contributor” means
A coding agent can interpret requirements, inspect a codebase, edit files, run commands, and sometimes call external tools. Those capabilities are useful only when the assignment has a clear boundary. The boundary should answer five questions before work starts:
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- What does done mean? Define acceptance criteria that another person can check.
- What context is relevant? Identify the repository, services, files, interfaces, tests, and constraints the agent needs.
- What may the agent touch? Specify tools, directories, credentials, data, network destinations, and environments.
- When must it stop? List conditions that require a person to clarify, approve, or take over.
The agent’s output is a proposed change. The team’s process still owns design decisions, code review, testing, security assessment, merge, and deployment.
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1. Scope a task that can be tested
Write a concrete task brief
A useful brief combines the problem, boundaries, and validation in one place. GitHub’s guidance recommends a clear description, complete acceptance criteria, and hints about likely files. Include enough context to prevent guesswork, but do not dump unrelated repository history into the prompt.
Problem: Requests to /invoices return HTTP 500 when the account has no billing contact. They should return the normal validation response used for other missing required fields.Acceptance criteria:
- Add a regression test for an account with no billing contact.
- Preserve the existing response schema and status code for valid accounts.
- Do not change database migrations, authentication, or unrelated invoice behavior.
- Run the invoice unit and integration tests and report the exact commands and results.Add likely locations and constraints when known: src/invoices/, tests/invoices/, the API version, supported runtime, style rules, and compatibility requirements. If the location is uncertain, say that the agent may search but must report which files it selected and why.
Make acceptance criteria observable
Prefer statements that produce a test, diff inspection, or command result. “Improve error handling” is not verifiable. “For a missing billing contact, return status 422, error code missing_billing_contact, and a response matching the existing schema” is.
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- Describe normal behavior that must remain unchanged.
- Specify edge cases, error handling, and backward-compatibility expectations.
- State non-functional constraints such as performance budgets, logging rules, accessibility, or data-retention policy when they matter.
- Identify files or subsystems that are explicitly out of scope.
- Define the checks required before the agent reports completion.
Break broad requests into reviewable slices
“Modernize the billing service” is a program of work, not one safe agent task. Split it into independently reviewable changes such as adding characterization tests, introducing an adapter, migrating one endpoint, and removing an obsolete path. Ask a human to reset the scope when a slice reveals a larger redesign. Scope expansion should never happen silently because an agent found a convenient adjacent fix.
Require a completion report
Make the final response part of the interface. Require the agent to list:
- Files created, changed, or deleted.
- Behavior changed and behavior intentionally left unchanged.
- Assumptions made and requirements that remained ambiguous.
- Commands run, their exit status, and material warnings.
- Tests not run, with the reason.
- Known limitations, follow-up work, and any requested permission or network access.
A concise report makes omissions visible. It is not a substitute for reading the patch.
2. Match access to the task
Use least privilege as a task setting
Grant only the repository paths, tools, identities, and data required for the assigned change. A documentation edit may need read access and a text editor; a local unit-test fix may need a build tool and a disposable test database; neither normally needs production credentials or unrestricted internet access.
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| Capability | Default for a coding task | Allow only when |
|---|---|---|
| Repository read | Relevant repository and history | The task requires broader dependency or ownership context. |
| Repository write | Isolated branch or workspace | The agent must create the proposed patch. |
| File deletion or bulk rewrite | Blocked or approval-gated | The brief names the exact paths and a reviewer accepts the risk. |
| Command execution | Allowlisted development and test commands | The command is inspected and its effects are understood. |
| Secrets and credentials | Unavailable | A specific approved integration needs a narrowly scoped, short-lived identity. |
| Network access | Disabled or restricted to trusted destinations | Dependency retrieval, documentation, or a required service has been approved. |
| Production systems or data | Out of scope | A separately authorized operational procedure names the target, identity, change, and rollback. |
Isolate the workspace
Prefer a disposable container, virtual machine, sandbox, or separate working directory and branch. Keep generated files, test databases, and downloaded dependencies away from a developer’s personal files. Record the commit or snapshot from which the agent started so the diff can be reproduced.
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Isolation reduces blast radius; it does not make unsafe instructions safe. OpenAI’s GPT-5.3-Codex system card describes default isolation and warns that enabling internet access can introduce prompt-injection, credential-leakage, and license risks. Controls differ by interface and deployment, so document what your chosen environment actually enforces rather than assuming a product label guarantees containment.
Control the network deliberately
Network access can expose source code or credentials, retrieve malicious instructions, introduce incompatible or unlicensed dependencies, and create unreviewed side effects. If access is necessary, restrict destinations, methods, and data types. Prefer a curated package mirror, read-only documentation hosts, or a test service over unrestricted outbound traffic. Log requests where your policy permits and remove access after the task.
3. Run the agent, then review the patch
Start with a clean baseline
- Confirm the starting commit, branch, runtime, and dependency lockfile.
- Verify that the baseline test command passes, or record existing failures before delegation.
- Provide the task brief and the allowed paths and commands.
- Tell the agent to stop when requirements conflict or the requested change needs broader architecture work.
Baseline information prevents a pre-existing failure from being attributed to the patch and makes later comparison possible.
Read the diff, not just the agent’s summary
Inspect every changed file, including generated configuration, lockfiles, scripts, and deleted tests. Compare each hunk with an acceptance criterion. Look for accidental API changes, altered defaults, weakened validation, hidden fallback behavior, debug logging, and changes outside the stated scope.
Review security- and data-sensitive paths separately. Authentication, authorization, payment, personal data, cryptography, deserialization, file handling, tenancy boundaries, and deployment configuration deserve a reviewer who understands the threat model. Check that logs do not expose secrets or personal data and that errors do not reveal internal details.
GitHub states: “You should always review and test the content generated by the cloud agent to ensure it is free of errors or security concerns prior to merging.” Automated review can identify patterns, but it does not transfer accountability to the tool.
Run the relevant checks yourself
Run the smallest complete set that exercises the changed behavior, then broader checks required by repository policy. Typical layers are:
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- Unit tests for changed modules.
- Integration or contract tests for changed interfaces.
- Security scanning and dependency checks where applicable.
- Build, packaging, migration, or type checks required for release.
Record the exact commands and results. Never claim a test passed because the agent said it ran; verify the output in the controlled workspace. If a check cannot run, mark the gap explicitly and decide whether a human must close it before merge.
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Verify commands before allowing effects
Generated commands can modify or delete files, alter databases, publish artifacts, or send data. Read the command, expand aliases and scripts when necessary, confirm the working directory and target, and use a dry-run or disposable target where available. A command that looks like a test may execute migration, cleanup, or upload steps through a project script.
Handle an unsuitable patch
Reject a patch when it fails an acceptance criterion, introduces unexplained scope, relies on unverified behavior, or cannot be tested safely. Give a focused correction request or reset the task with a narrower brief. Do not ask the agent to “fix everything” after a failed review; that usually increases the unexamined surface area.
4. Escalate at the point of side effect
Predefine stop conditions
The agent must pause and request a human decision when any of these conditions occurs:
- The requirement is ambiguous, contradictory, or materially different from the current implementation.
- The proposed change expands beyond named files, interfaces, or acceptance criteria.
- A command would delete, overwrite, migrate, publish, deploy, or irreversibly alter data.
- The agent requests credentials, private data, production access, or a new identity.
- Network access is needed beyond the approved destinations.
- A third party, customer, regulator, or external system would be contacted or affected.
- The change touches security controls, authorization, cryptography, payment, safety-critical behavior, or compliance evidence.
- Tests fail for an unexplained reason or the agent cannot establish a safe rollback.
- Required approval, logging, or policy enforcement is unavailable.
Approve the exact action, not a vague intention
Before execution, a reviewer should validate the proposed tool, target, arguments, identity, data, and scope. “Proceed with the migration” is insufficient. “Run migration 2026-10-14-accounts on the disposable staging database using the migration identity; no production targets; rollback script is available” is reviewable.
| Action | Typical handling | Information to approve |
|---|---|---|
| Read source and run deterministic unit tests | May proceed within the sandbox | Repository, command, and resource limits |
| Add a dependency | Review before installation or lockfile update | Package, version, source, license, and required network destination |
| Delete files or rewrite history | Human approval required | Exact paths or commits, backup, and recovery plan |
| Access a secret or private dataset | Human approval and narrowly scoped identity | Purpose, fields, duration, storage, and revocation |
| Change production or contact a third party | Separate operational change process | Target, timing, owner, monitoring, rollback, and customer impact |
Put enforcement beside the tool
Approval that exists only in a prompt is easy to bypass accidentally. In an agent application, place a guardrail around the function that causes the side effect. The guardrail should inspect arguments, apply policy, interrupt execution when approval is needed, and resume only from recorded state after approval. OpenAI’s Agents SDK guidance says: “Pause ambiguous or high-risk actions for explicit human approval before the tool runs.” Treat that as an implementation pattern, not evidence that every platform supplies identical controls.
Fail closed when review is unavailable
If the approver, policy service, audit sink, or identity check is unavailable, do not execute the gated action. Preserve the proposed call and context so a reviewer can resume or reject it later. A timeout should not silently become permission. Record who approved, what was approved, when it occurred, and whether the executed arguments matched the approved ones.
5. Use monitoring as defense in depth
Monitoring can reveal suspicious behavior, unexpected tool use, and activity inconsistent with the assigned intent. It cannot guarantee that every failure will be detected, especially when behavior is novel, traffic is open-ended, or telemetry is incomplete.
OpenAI describes an internal asynchronous monitor that reviewed tens of millions of coding-agent trajectories over five months. Its report says approximately 1,000 conversations triggered moderate-severity alerts and were escalated for human review; many involved deliberate internal red-teaming. It also reports that less than 0.1% of traffic, primarily from bespoke or local setups, was outside that monitoring coverage. These are operational figures from that internal deployment, not industry-wide incident or quality rates.
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The same report acknowledges difficulty quantifying false-negative rates on open-ended real-world traffic. Use monitoring alongside preventative controls:
- Least-privilege permissions and isolated workspaces.
- Allowlisted tools, destinations, and identities.
- Pre-merge human review and test evidence.
- Adversarial evaluations and regression tests.
- Audit logs that connect requests, tool calls, approvals, and outcomes.
- Incident response and credential-revocation procedures.
Do not treat a clean monitoring result as authorization to merge or deploy.
6. Compare agent setups on controls, not marketing claims
When choosing among agents or deployment configurations, compare the controls that affect your workflow. The following axes synthesize capabilities described in GitHub and OpenAI documentation; they are not a third-party benchmark.
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| Permission granularity and isolation | Can access be limited by repository, directory, command, identity, and environment? | Policy configuration, sandbox behavior, and an example denied action |
| Approval and interruption | Can high-risk tool calls pause before execution and resume safely after a decision? | Approval event, rejected call, timeout behavior, and resumable state |
| Context and instructions | Can teams provide task-specific files, constraints, and acceptance criteria without exposing unrelated data? | Context boundaries and instruction precedence |
| Review and test visibility | Can reviewers inspect the complete diff, commands, output, and failures? | Patch, execution log, test evidence, and changed-file list |
| Network controls and audit | Can destinations be restricted and tool calls recorded? | Allowlist, request logs, retention, and export controls |
| Deployment and data policy | Where does processing occur, what data is retained, and who administers access? | Deployment documentation, administrative policy, and deletion process |
A setup that writes excellent code but cannot show what it ran, restrict where it can connect, or interrupt a dangerous call is unsuitable for sensitive repositories.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.7. Establish team ownership and operating rules
Assign clear roles
- Task owner: defines the problem, acceptance criteria, scope, and escalation policy.
- Agent operator: configures the workspace and permissions, starts the run, and preserves logs.
- Code reviewer: evaluates the diff, security implications, and test evidence.
- Approver: authorizes high-risk side effects or rejects them.
- Release owner: decides whether a reviewed change may enter a shared or production environment.
One person may hold several roles for low-risk work, but the decision to merge or deploy should remain explicit. For sensitive changes, use a second reviewer or the repository’s normal change-control policy.
Define repository-level defaults
Document allowed commands, protected branches, required checks, secret-handling rules, network policy, data classification, and escalation contacts. A task brief can be short because these defaults supply the baseline. Update them when a near miss exposes a missing control.
Measure process quality without inventing success rates
Track operational signals that your team can verify: percentage of tasks with acceptance criteria, changed-file scope violations, unrun required tests, approval denials, repeated escalation causes, rollback events, and time from alert to human decision. These measures describe your process; they do not prove that one agent is universally better than another.
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8. Connect the workflow to secure-development practice
NIST SP 800-218A, Secure Software Development Practices for Generative AI and Dual-Use Foundation Models: An SSDF Community Profile, was published July 26, 2024. NIST describes it as augmenting Secure Software Development Framework (SSDF) version 1.1 with AI-specific practices, tasks, recommendations, considerations, notes, and informative references across the software development life cycle.
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Use it as background for integrating AI-related risks into an existing secure-development program: requirements, design, implementation, verification, release, and maintenance. It is not a complete coding-agent delegation manual. Your task briefs, permission policies, review gates, and incident procedures still need to reflect the codebase and threat model you operate.
9. Troubleshoot common delegation failures
The agent changes too much
Stop the run, preserve the diff, and identify the first point where scope expanded. Restore the last acceptable state, narrow the brief to named files and behavior, and require a report of any requested expansion before more edits.
The agent claims tests passed, but evidence is missing
Run the commands independently in the controlled workspace. Compare the environment and commit with the agent’s report. Treat absent output, a different working tree, or a skipped test as unverified rather than successful.
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Do not paste credentials into the prompt. Ask why the access is needed, what exact endpoint and data are involved, and whether a fixture, mock, read-only token, or curated mirror will work. Escalate if the requirement cannot be reduced to the approved scope.
A dependency or generated file appears unexpectedly
Pause before installation or commit. Inspect provenance, version, license, transitive dependencies, generated content, and lockfile changes. Remove it unless the task owner approves the addition and the project’s normal dependency checks pass.
Requirements conflict during implementation
Stop rather than choosing silently. Present the conflicting interpretations, affected files, behavioral consequences, and a recommended option. Resume only after the owner records the decision in the task context.
An approval service or audit trail is down
Fail closed for the gated action. Keep read-only analysis or safe local work separate if policy permits, but do not bypass the approval path or reconstruct approval after the side effect.
10. Reusable checklists
Task-owner checklist
- Problem and desired behavior are stated.
- Acceptance criteria are testable and complete.
- Relevant files, interfaces, versions, and constraints are identified.
- Out-of-scope areas are named.
- Required tests and reporting format are specified.
- Stop conditions and approvers are listed.
Operator checklist
- Starting commit and baseline checks are recorded.
- Workspace, branch, tools, credentials, and network are limited.
- Production systems and sensitive data are excluded by default.
- Commands and tool calls are logged.
- Unexpected requests are paused, not improvised.
Reviewer checklist
- Every changed file and deletion has a reason.
- Acceptance criteria map to code and tests.
- Security, privacy, authorization, and data-handling paths were inspected.
- Relevant checks were run independently and results recorded.
- Unverified claims, skipped tests, and remaining risks are documented.
- Merge, deployment, or follow-up ownership is explicit.
The practical standard is simple: the agent may work quickly inside a boundary, but people define that boundary, inspect what crossed it, and decide when an action is consequential enough to require approval.
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