ILLUSTRATIVE WALKTHROUGH

A request, with room for judgment.

Follow a monthly report from a request to human review. This illustrative example uses synthetic data.

01 04 Request

Start with a clear request

Example request

Prepare September’s client report. Compare it with August, keep the writing clear and direct, and flag anything the reviewer needs to check.

A report gives the specialist agent a specific task, a reporting period and a person to prepare it for.

02 04 Client context

Keep the source context visible

Reporting period
September 1–30, 2026
Comparison period
August 1–31, 2026
Brand voice
Clear, direct and specific
Analytics & Search Console
Not supplied in this example

Missing data stays missing. It never becomes a zero or a performance claim.

03 04 Draft

Make the gaps part of the draft

Specialist agent · September reportDraft for review

September’s reporting period is complete. Analytics figures have not been supplied for this example, so a comparison with August cannot yet be made.

Search ConsoleData unavailable · add source data before review

This sample draft is written for the walkthrough. It is not generated live.

04 04 Human review

Leave the final decision with a person

  • Check source figures and the true previous period.
  • Confirm the “as of” date reflects the oldest source data.
  • Review the writing before approving the report.
Awaiting source data and human approval

The missing data keeps this example at draft. Nothing is sent.

The routine work behind every client

Marketing agencies repeat the same work for every client: pulling numbers from Google Analytics and Klaviyo, drafting emails, building monthly reports, and chasing approvals. Cobar is a web app I built at Wallaroo Media to help with that work.

From a request to a reviewed draft

Cobar sends each request to a specialized AI agent for SEO, email, ads, content, or analytics. The agent uses the client’s data and brand voice to produce a finished draft. A person reviews and approves it before it goes out.

Account managers and specialists use Cobar day to day. Clients see their results through a client portal.

What I designed and built

Since February 2026, I’ve designed and built Cobar across product direction, the visual design system, the React interface, and the Python backend with a Postgres database. I built the setup that lets one agency manage many client accounts, and an AI layer that switches between model providers if one fails.

I also led a team of engineers and user testers who helped add features and fixes under my direction.

Every number is a claim

When I audited the agents, the data was correct when it was fetched. Errors crept in afterward, in totals, comparisons, and labels. A missing value became zero. A “vs. last month” comparison included the current month. A date label implied the data was newer than it was.

I made three rules the code enforces:

  • Missing data is marked as missing, never shown as zero.
  • Comparisons use the true previous period.
  • Every “as of” label gives the date of the oldest data on the screen.

Search Console reports with a three-day delay, so this period’s figures stop at Sep 17.

The date note in the demo report shown above.

Where it stands

Cobar is in daily use at Wallaroo Media. Paid early access for outside businesses is planned for December 2026.