How to turn engineering context into clear improvement priorities

Organizations collect more engineering data than ever. Dashboards track cycle time, review wait time, deployment frequency, reliability, and tool adoption. Yet they do not answer the question engineering leaders face repeatedly: where should we focus now?

Without a clear answer, priority often goes to whichever metric changed most recently or whichever problem was raised most loudly. Neither reliably reflects impact, leaving teams busy without necessarily improving outcomes.

The Engineering Intelligence Pulse helps engineering leaders and teams identify and rank the opportunities that matter most, so they know what to fix next.

What the Engineering Intelligence Pulse gives you

Each Pulse run produces a ranked set of improvement opportunities grounded in your engineering data. Each opportunity includes information such as:

• Evidence: What was observed and over what period.
• Context: The affected service, owning team, rationale, and priority.
• Next step: A recommended action and a clear measure of success.

For example, the Payments service, owned by the Checkout team, is slowing down because PRs wait an average of 26 hours for review, nearly four times the organization's average. The Pulse identifies limited reviewer coverage as the likely bottleneck and uses relationships in the Context Lake to recommend the right backup reviewer based on code ownership and recent contributions. The target is to reduce review wait time to under four hours.

Together, these give teams a detailed plan of action for deciding what to improve next.

How it works

The Pulse brings together approved domain skills, the Engineering Intelligence Agent, and a customizable workflow.

Skills provide domain expertise

Each skill defines how to assess a specific engineering domain, including which data to examine, which comparisons are meaningful, and what qualifies as an opportunity for improvement. Organizations can tailor existing skills to their priorities, goals, and engineering context, or add new skills to assess additional domains.

The agent applies the expertise

The Engineering Intelligence Agent loads the approved skills and applies them to your engineering data. It combines the findings into one assessment and ranks the opportunities that matter most.

The workflow orchestrates the process

The workflow controls when the assessment runs, enriches Port’s Context Lake with qualified opportunities, and shares the top priorities in Slack. These opportunities become reusable context for other agentic workflows, while the orchestration can be customized to fit your organization’s processes.

How to set it up

Before starting, you need engineering data in Port, service-to-team ownership configured, and a Slack bot that can publish the brief.

1. Set up the Engineering Intelligence Agent and add a domain AI skill.
2. Create and schedule the workflow.
3. Review the results in Port or Slack.

Follow the full step-by-step guide to set up the Engineering Intelligence Pulse in Port.

Start with one use case, such as identifying opportunities to improve delivery performance, and then expand to other engineering areas.

From priority to measurable improvement

The Engineering Intelligence Pulse is one example of how Port workflows can turn engineering data into action. Organizations can build their own workflows to identify bottlenecks and opportunities for improvement based on their goals, data, and engineering practices.

They can then use additional governed workflows to act on those opportunities and measure whether the expected improvement was achieved. This creates a repeatable path from insight to action to measurable impact.

Learn more about the use case in our guide: Create the Engineering Intelligence Pulse in Port.

‍