Agentic Engineering: Context, Guardrails, & Creativity

Platform engineering teams are being asked to bring AI into the SDLC. The problem is that most agents rely on scattered data, take actions without guardrails, and make decisions that are hard to trace or control. The engineering chaos that platform engineering was built to solve just got exponentially bigger.

What happens when you want AI agents to resolve tickets end to end? Or self-heal production incidents from alert to postmortem? That's where you need proper infrastructure: the right context fed to each agent, guardrails on what they can and can't do, and humans in the loop before anything ships.

Join Zac Law, Solutions Engineer, and Tomek Skora, Product Solutions Lead, on March TBD to see how this works in Port. Live demo, open Q&A throughout.

We'll walk through 3 Agentic Solutions built on Port:

• Autonomous Ticket Resolution: How a ticket moves from idea to PRD to tech spec to code to security review to deployment, with AI agents handling each step and developers approving, declining, or iterating before anything moves forward

• Self-Healing Incidents: How incidents go from alert to triage to remediation to postmortem with near-zero MTTR, with agents pulling affected services, business impact, and blast radius so they respond with full context

• Engineering Intelligence: How we track agent success rates, PR approval rates for AI-generated code, and agentic vs manual cycle times side by side, so you can measure whether AI is actually working for your teams

And, we’ll chat about:

• How Port's Context Lake feeds each agent the right context so they perform better and don't make destructive decisions, and how guardrails govern what each agent can do: scoped tools, role-based access that evaluates business criticality and risk before any action runs, with human approval at every step

Bring your questions. Let's enter the agentic era together.