Advertising judgment and AI production.

Keep the idea. Change how it gets made.

A client can like an idea and still have no workable way to produce it. The cost may be wrong. The next adaptation may require too much manual work. A promising output may fall apart when someone asks for a precise revision.

These are the kinds of problems Max Markovtsev works on through Purple Orange AI. His role combines advertising judgment with the ability to build the workflow behind the result. A useful first assignment has a defined output and someone who can decide whether it meets the brief.

The advertising background

At 19, Max helped launch Leo Burnett Moscow, working on P&G brands. His credits include the creative concept and initial production for the 1995 Myth campaign. He later worked in P&G account management at Leo Burnett Chicago, on Wrigley at BBDO, and in digital strategy and business intelligence at JWT.

The roles matter: account leadership, creative development, production and business intelligence are different responsibilities. Max's career history identifies those distinctions. The 2003 ThermaSilk WebAward record names him on the JWT team; that recognition was for a website.

That experience gives context for today's work: understanding the business behind a brief, making production choices and carrying a result through review. Historical brand work is part of Max's career; it does not imply that those brands are current Purple Orange AI clients.

The production test

A plausible image, script or workflow is a starting point. The test is what happens when the requirements get specific.

• Fit: Does the output communicate the intended idea to the intended audience?
• Revision: Can the requested detail change while the approved parts remain intact?
• Review: Can the owner see what changed and decide whether to accept it?
• Economics: What did production cost, including human review and rework?

For a recurring workflow, the same questions apply to the input, the draft and the approved action. A build should earn its place through the work it performs.

Systems support the review

Max also builds software for coordinating AI work. The work library shows public product surfaces and labels private systems and previews. These projects explore source retrieval, controlled tool use and evidence of execution.

A useful review separates a prepared action from an executed one. It identifies the source material and records the result. For a production asset, that means an inspectable revision. For a business workflow, it means knowing whether the intended change actually reached the source system.

See the workflow audit checklist for choosing a bounded job and the governance guide for defining review responsibilities.

What the evidence shows

An internal demonstration can establish that a particular output or control works under the conditions shown. It cannot establish client savings, sales or unattended delivery across an entire business.

Those claims require evidence from real use: accepted work, recorded costs, human time and confirmed outcomes. Public examples should identify which parts are demonstrated and which remain to be tested. Private client material needs permission before it becomes a public case study.

Start with a real piece of work

For an agency, start with a current client brief and one difficult part of making it. For an operating team, bring one recurring job with a clear owner. Agree the required result, available inputs and review conditions before committing to delivery.

The Reviewable Agent install covers a defined workflow. Larger implementation scopes are available for more involved work. Creative production is scoped against the actual brief; an internal sample is not a promise to meet any production requirement.