This roadmap is for a team that already has agentic AI running in production, or is close to launching it, and knows the current security posture isn't where it needs to be, without knowing exactly where to start fixing it. It's not written for a team starting from zero, and it's not a claim that 90 days produces a mature program. It's a sequence that takes a team from partial visibility to a working baseline: inventory and understand what's actually running, close the specific gaps that matter most, and then build the operational muscle to detect and respond when something goes wrong anyway. Each phase builds on the one before it, so resist the urge to skip straight to incident response runbooks before you actually know what agents exist and what they can do.

Days 1-30: build real visibility

The first month is about knowing what you're actually securing, since it's common for teams to discover during this phase that they have more agents and tool integrations than anyone had tracked.

  1. List every agent currently in production or near launch, including internal tools that don't feel like "real" AI features yet.
  2. For each agent, list the specific tools it can call and the specific data it can access, not a general description of its purpose.
  3. Identify the single highest-impact action each agent is capable of taking, the one that would cause the most damage if triggered by mistake or by an attacker.
  4. Establish baseline audit logging anywhere it's missing, capturing identity, decision, and tool-call outcome at minimum.
  5. Flag any agent whose access clearly exceeds what its actual function requires, even without fixing it yet.

Days 31-60: close the biggest gaps

With visibility in place, the second month focuses on the specific gaps that carry the most risk, not on a comprehensive rebuild of every control at once.

  1. Narrow the worst over-broad tool permissions identified in the first phase, starting with the highest-impact agents flagged earlier.
  2. Add an authorization check at the tool-call boundary that runs independently of what the model claims it intends to do, so a manipulated or mistaken model can't talk its way past the check.
  3. Add fail-closed behavior to any security-critical dependency that currently fails open, particularly anything sitting between the agent and a sensitive action.
  4. Introduce an approval requirement for the highest-impact actions identified in phase one, even a lightweight one, if none currently exists.
  5. Re-run the phase one inventory against any changes made so far to confirm the fixes actually reduced the flagged exposure.

Days 61-90: operationalize response and detection

The third month shifts from fixing static gaps to building the operational capability to notice and respond when something happens anyway, since no set of controls eliminates incidents entirely.

  1. Build or refine incident response runbooks for the two or three most likely scenarios given what phase one and two surfaced, rather than a generic all-purpose runbook.
  2. Establish monitoring for specific abuse signals: unusual tool-call patterns, deviations from an agent's normal behavioral baseline, repeated policy denials from the same identity.
  3. Confirm evidence preservation and communication procedures exist and are known to whoever would actually respond, not just documented somewhere unread.
  4. Run a tabletop exercise against one of the runbooks, using a realistic scenario based on the highest-impact action identified back in phase one.
  5. Capture what the tabletop exposed as gaps and feed those directly back into the runbook and, if needed, back into phase two's permission and authorization work.

What happens after day 90

Ninety days in, you should have real visibility into what your agents can do, the worst permission gaps closed, and a tested response process for the scenarios that matter most. That's a genuine baseline, not a finish line. Agent capabilities expand, new tools get integrated, usage scales, and each of those changes can reopen risk that this roadmap closed. Treat day 90 as the point where you shift from a fixed sprint to an ongoing cadence: revisit the inventory when a significant new capability ships, re-test the runbooks periodically, and keep checking whether permission scope has quietly crept back outward since the last review.

Where TELEON fits

Several steps in this roadmap map directly onto what a gateway deployed between agents and model providers or tools can provide out of the box: an audit trail that gives phase one its visibility without custom logging work, runtime policy enforcement at the tool-call boundary for the independent authorization check in phase two, and a consistent record for the monitoring and evidence work in phase three. That infrastructure shortens the distance between deciding to close a gap and actually having it closed.

The inventory work, the judgment calls about which gaps matter most, the runbook content, and the tabletop exercise itself all still depend on the team running this roadmap directly. TELEON's enforcement and audit capabilities support each phase; they don't substitute for doing the phase.

A short checklist

  1. Inventory every agent, its tools, its data access, and its highest-impact action.
  2. Establish baseline audit logging wherever it's missing.
  3. Narrow the worst over-broad permissions and add independent authorization checks.
  4. Make security-critical dependencies fail closed by default.
  5. Build runbooks and monitoring for the most likely incident scenarios.
  6. Run a tabletop exercise and feed its findings back into the roadmap.
  7. Treat day 90 as a baseline to revisit, not a completed project.

Teams that treat this roadmap as a one-time project tend to see the posture they built quietly erode within a few months, as new agents launch without going through the same inventory and permission review. The version of this plan that actually holds up is the one where day 91 starts a recurring cadence rather than a return to business as usual.