Just-in-time secrets for agentic development are now the default

At a glance

What this is: This on-demand demo argues that just-in-time secrets, runtime injection, and per-environment targeting are becoming the practical default for secure AI-powered development.

Why it matters: It matters because IAM teams now have to govern machine access patterns that move faster than traditional secret handling, without creating friction for developers or weakening enterprise control.

👉 Watch 1Password's demo on just-in-time secrets for secure agentic development

Context

Coding agents change the secret-handling problem because they need live credentials to run code, call APIs, and interact with production-like systems. That means copying secrets into files, syncing environment variables, or relying on long-lived credentials creates a wider exposure window than most teams designed for. The primary keyword here is just-in-time secrets, and the underlying issue is whether enterprise governance can keep pace with agent-driven execution.

For IAM and security teams, the central question is not whether developers should move faster, but how access is issued, scoped, and removed at the moment of use. This is a non-human identity problem first, because the workflow is being driven by software rather than a person, and the controls need to match that runtime behaviour. The relevant governance lens is least privilege at execution time, not secret storage after the fact.

Key questions

Q: How should security teams handle secrets for coding agents?

A: Security teams should move from static secret placement to runtime delivery, using just-in-time injection, narrow scoping, and task-specific access. Coding agents should receive only the credentials they need for the current execution path, with separate handling for each environment. That approach reduces persistence, limits reuse, and makes least privilege operational instead of theoretical.

Q: When do long-lived secrets become a governance problem for AI-powered development?

A: Long-lived secrets become a governance problem as soon as they are used in workflows where software can request, reuse, or spread credentials faster than a human can review them. In AI-powered development, that often happens immediately because the agent can access APIs and systems during active execution. The control gap is persistence, not just theft.

Q: What do teams get wrong about least privilege for coding agents?

A: Teams often treat least privilege as a provisioning exercise instead of an execution property. For coding agents, the real question is whether access is constrained to one environment, one task, and one runtime session. If the credential can be reused elsewhere, least privilege has not been demonstrated, only documented.

Q: How can organisations tell whether runtime secrets controls are working?

A: They should look for evidence that secrets are not stored locally, not reused across environments, and not available outside the agent’s execution window. A working model produces narrow access paths, observable delivery, and minimal residual credential exposure after the task ends. If developers still depend on copied secrets, the control is incomplete.

Background and context

Just-in-time secrets and runtime injection for coding agents

Just-in-time secrets means credentials are delivered only when a task actually needs them, then withdrawn rather than left sitting in files, shells, or shared environment variables. Runtime injection pushes the secret into the execution context at the point of use, which reduces persistence but does not remove the need for tight scoping. For coding agents, this matters because the tool may touch APIs, repositories, and test environments in a single workflow. The real architectural shift is that secret exposure becomes an execution event, not a storage state.

Practical implication: move secrets into runtime-controlled delivery paths instead of copying them into developer workspaces.

Per-environment targeting and read-only access in agent workflows

Per-environment targeting limits an agent to the specific system it needs, such as dev, staging, or a constrained production-like environment. Read-only access narrows the blast radius further by allowing observation and validation without write privileges. In practice, this is how teams demonstrate least privilege when the actor is a coding agent that may act quickly and repeatedly across tools. The key is to make entitlement boundaries explicit enough that the workflow cannot silently drift into broader access.

Practical implication: bind agent credentials to a single environment and default them to read-only where possible.

Why long-lived secrets are a poor fit for AI-powered development

Long-lived secrets assume a stable human workflow, where credentials can sit in a workstation, be reviewed later, and be rotated on a schedule. AI-powered development breaks that assumption because access is often created and consumed inside the same runtime sequence. Once a secret is copied locally, it becomes hard to trace, hard to constrain, and easy to reuse outside the intended task. That makes secret persistence the core governance problem, not just secret theft.

Practical implication: treat secret persistence as a design flaw and redesign developer access around ephemeral delivery.

NHI Mgmt Group analysis

Just-in-time secrets is becoming the operational baseline for AI-assisted development. Coding agents need credentials in motion, not credentials parked in developer files or long-lived environment stores. That shifts secrets handling from static provisioning to execution-scoped access, which is exactly where conventional secret sprawl starts to create governance debt. The implication is that teams must treat runtime delivery as the normal control plane, not an exception.

Runtime injection changes the control boundary, but it does not eliminate identity risk. The risk moves from where the secret is stored to when and how the secret is materialised for the agent. That is a meaningful governance improvement only if the entitlement is tightly scoped to a single environment and a narrow task. Practitioners should recognise that the security question is now about controlled exposure at execution time.

Ephemeral credential trust debt: This is the gap created when development teams assume temporary access is automatically safe simply because it is short-lived. The article points to the opposite problem: speed and governance only align when the runtime access model is deliberate, observable, and environment-specific. That means secrets strategy now sits inside developer workflow design, not beside it.

Agentic development forces IAM and developer experience to converge. The old pattern of security adding friction after developers have already built the workflow no longer scales when the actor is software that can request and consume secrets repeatedly. Governance has to be encoded into the path the agent already uses. Practitioners should expect secrets policy, environment targeting, and execution controls to become part of the same operating model.

Least privilege must be proven at execution time, not asserted in policy documents. The article’s framework shows why read-only access and per-environment targeting matter: they turn least privilege into a runtime property that can be inspected. That is a more durable pattern for AI-powered development than relying on local secret handling conventions. Teams should measure whether privilege is actually constrained where the code runs.

From our research:

• The average estimated time to remediate a leaked secret is 27 days, despite 75% of organisations expressing strong confidence in their secrets management capabilities, according to The State of Secrets in AppSec.
• Only 44% of developers are reported to follow security best practices for secrets management, exposing a significant developer behaviour gap.
• The governance next step is to pair execution-scoped access with lifecycle discipline, as shown in Ultimate Guide to NHIs , 2025 Outlook and Predictions.

What this signals

Ephemeral credential trust debt: organisations adopting coding agents need to treat short-lived access as a governance debt category, not a comfort signal. The more often secrets are injected at runtime, the more important it becomes to verify where they are cached, reused, or copied downstream. For teams aligned to zero trust, this is a practical extension of NIST AI Risk Management Framework thinking into developer execution paths.

The operational signal to watch is whether developers still depend on local files, shared environment variables, or manually copied credentials after agent workflows are introduced. If those habits remain, the security model has not shifted with the development model. Runtime control only works when access is bounded by environment, session, and purpose, and that expectation now needs to be visible in programme reviews.

The broader programme implication is that NHI governance is moving closer to software delivery governance. That is where access reviews, entitlement scoping, and secret handling stop being separate disciplines and become one control surface. Teams that can connect those controls will have a more defensible posture as agentic development becomes routine.

For practitioners

• Move secrets delivery to runtime injection Replace local secret copies and synced environment variables with runtime-controlled injection so credentials exist only for the execution window. This reduces persistence, makes access easier to scope, and keeps developer workflows closer to least privilege.
• Bind agents to per-environment credentials Issue separate credentials for dev, staging, and production-like systems so a coding agent cannot drift across boundaries. Per-environment targeting makes governance visible and limits the blast radius if the workflow is misused.
• Default coding agents to read-only access Use read-only permissions until a task truly requires write access, then escalate only for that specific execution path. This is the clearest way to demonstrate least privilege in an AI-powered development workflow.
• Eliminate long-lived secrets from developer workflows Remove persistent credentials from files, shells, and shared workspace patterns so secrets are not available outside the task that needs them. The aim is to reduce the time secrets remain recoverable after use.
• Review where agent access outlives the task Map any step where a coding agent can retain access beyond the immediate execution sequence, including cached tokens and reusable environment bindings. Those are the points where governance assumptions break down first.

Key takeaways

• AI-powered development turns secrets handling into a runtime governance problem, not a storage problem.
• Long-lived credentials and copied environment variables create exposure that is wider than most traditional secret controls were designed to absorb.
• The practical response is to enforce just-in-time delivery, per-environment scoping, and read-only defaults wherever agents touch real systems.

Key terms

• Just-in-time secrets: Just-in-time secrets are credentials delivered only when a task needs them and removed once the task is complete. They reduce persistence and reuse risk by turning secret access into a short-lived execution event rather than a standing condition in a developer environment.
• Runtime injection: Runtime injection is the practice of supplying credentials or tokens directly into an application or agent at execution time instead of storing them locally. It keeps secrets out of files and shared environment variables, but only works well when the runtime boundary is tightly controlled and observable.
• Per-environment targeting: Per-environment targeting means a credential or access path is bound to one specific environment such as development, staging, or production-like systems. It prevents broad reuse, limits accidental drift across systems, and helps prove that machine access stays within a defined operational boundary.
• Read-only access: Read-only access allows a machine or agent to inspect data or systems without changing them. In AI-assisted development, it is a practical least-privilege default because it lets teams validate behaviour and gather context while reducing the chance of unintended modification or privilege escalation.

Deepen your knowledge

Just-in-time secrets, runtime injection, and least privilege for AI-powered development are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building controls for coding agents and production-like workflows, it is worth exploring.

This post draws on content published by 1Password: Demo On Demand Secure agentic development: Just-in-time secrets as the new default. Read the original.