Marketing meetings often leave a familiar trail of unfinished work: offers to compare, ideas to organize, and a next step that still needs agreement. Each task calls for a different way of looking at information. At La Fábrica, we see GPT-6 and Intelligent UI as a reason to test whether a conversation can become a more useful place to work through those decisions.

OpenAI introduced the update on October 7, 2026, describing ChatGPT responses that combine text, visuals, and interactive elements. The announcement also describes answers beginning while the model continues reasoning. See the official GPT-6 announcement.

What an explorable answer could change

The Intelligent UI guide says layouts depend on the question and may include buttons, forms, or charts. The feature works in Chat, excluding Work and Voice. Some components retain their state when a conversation refreshes, but state does not carry across conversations.

Our practical takeaway for marketers is to test interaction where a task involves alternatives or changing conditions. Editing a headline may call for a short answer. Exploring how a proposal changes when its requirements change may benefit from a different presentation. Start by naming the decision the experience should help you make.

“Help with our marketing” leaves the outcome open to interpretation. “Help us compare these proposals against the criteria our team agreed on” gives you something to inspect. The exercises below are La Fábrica’s suggested experiments. They still need testing against the tools available in your account and the requirements of your business.

Three experiments worth defining for a marketing team

Put competing proposals on equal footing

Imagine a service business choosing between creative directions. Ask for a comparison that gives each option the same fields: audience, message, required assets, dependencies, and unanswered questions. Use the result to discuss specific trade-offs before committing production time. A useful comparison should make missing information easier to spot.

Supply proposals you are authorized to share and require missing details to stay visibly unresolved. Agree on evaluation criteria with your team before asking for scores. If brand consistency matters more than production effort for this particular decision, document that priority and assign someone to validate the assessment.

Review a content plan from several angles

For a business with several services, try organizing your own content ideas by audience, stage of the customer relationship, and intended action. Request filters or grouped views where they help. Then ask your sales and customer support colleagues whether the plan covers the questions they actually hear.

Look for repetition, services that lack a clear explanation, and pieces without an obvious purpose. Keep the approved plan in your existing team system. Make it explicit that changes inside the experiment are proposals awaiting review, and nominate the person who will transfer approved decisions into the working calendar.

Turn a campaign brief into a better discussion

Try exploring a brief through fields for audience, customer problem, offer, supporting evidence, and brand constraints. Ask for unanswered questions beside the relevant field. The intended outcome is a better conversation with the people who know the business and can resolve those questions.

Require research-dependent statements to be labeled as hypotheses. An attractive description of a target customer needs support from interviews, real inquiries, or company materials. Use the exercise to surface assumptions and decide what to investigate. Keep a clear distinction between information supplied by the team and suggestions generated during the discussion.

Write a request your team can evaluate

Build the request around the decision, the materials available, the interactions you want, and the boundaries of the task. Here is a starting point you can adapt:

“Help me compare these content proposals so our team can choose one to develop. Use only the material I provide. Organize each proposal by audience, objective, message, available evidence, and open questions. If useful, create an interactive view to explore the options. Label missing information as unresolved. Show the comparison criteria and finish with questions for our team. Keep every change as a proposal for human review.”

Test the first response on a small task. Change one condition and inspect what changes elsewhere. Ask for the reasoning behind the comparison criteria. If the experience becomes hard to follow, narrow the request until each part can be checked. The person responsible for the decision should be able to understand how the result was produced.

Build review into the workflow

OpenAI explains that ChatGPT can produce incorrect information and fabricated references. We recommend opening original sources, checking product claims against approved material, and assigning a named reviewer before content leaves the conversation.

Review your account’s settings before introducing internal material. The ChatGPT data controls documentation explains controls for using conversations in training. OpenAI says Business and Enterprise content is excluded from model training by default. Your organization’s own information policies still apply.

For an initial experiment, use public material or examples prepared specifically for testing. Decide which information can be shared and where the approved version will live. Ask for supplied facts, assumptions, and generated suggestions to be identified separately. This gives the reviewer a practical way to focus on the parts that need confirmation.

Run a small pilot with a clear success question

Choose a recurring task and save an example completed through your usual process. Repeat the exercise with the proposed experience. Track time to a reviewed result, corrections required, and whether another team member can understand the decision. These are suggested evaluation criteria, with no assumed improvement attached.

• Name the decision and the person who will approve it.
• Prepare authorized inputs and flag missing information.
• Change one condition and check the consistency of the result.
• Save the approved output and record what needs adjustment.

The announcement scheduled rollout first to paid plans, then Free and Go the following day, with Enterprise access subject to administrator settings. An announced rollout does not establish availability in a specific account. Source: launch availability.

La Fábrica’s recommendation is to choose a real decision and design an experiment your team can assess. If you want to explore this approach for your business, start with a focused brief: what needs resolving, what evidence is available, and what a useful result would look like.