Start with where the work begins.

Make the work easier to move forward.

ChatGPT offers a broad workspace for questions, research, and creating things. OpenAI's current documentation also describes ChatGPT Work for multi-step tasks, connected apps, finished deliverables, and scheduled or supported event-triggered work. Jared's focus is an AI coworker in Slack: following team conversations and preparing useful next steps for review. The useful comparison is how each fits your team's habits.

A client update is due. The latest decision lives in a thread, the status has changed, and someone still needs to turn those pieces into a clear report. Either product deserves a test with the context and tools it actually supports. A comparison that gives one product current evidence and the other a vague prompt tells you very little.

What to bring to the task

• One real reporting task, with an agreed definition of a finished draft.
• The same approved source material, including a recent correction and an unresolved question.
• A named reviewer, a draft-only boundary, and a record of setup time.

From context to a useful result.

1. Explore ChatGPT for a broad workbench

   If people regularly move between research, writing, analysis, and open-ended problem solving, evaluate that breadth. Projects can group related chats, files, and instructions. Test the available Work experience and connected apps with your actual account; record which features, permissions, and configuration the task requires.

2. Explore Jared for work discussed in Slack

   If useful tasks emerge while teammates talk, test Jared's conversation-led approach. Its demos show briefings, client updates, and follow-up drafts returned for review. Look for a helpful intervention at the right moment, a usable artifact, and a clear path for the team to correct the work.

3. Compare the second run

   Repeat the task after changing a deadline and adding a conflicting update. Measure factual corrections, manual context gathering, review effort, and unwanted interruptions. Check who owns the final result and whether a teammate can understand the evidence without asking the original requester to explain everything again.

Before you make it a routine

• Can reviewers trace important statements to current source material?
• How much prompting, connection setup, and manual checking does each run need?
• Does an unavailable source produce an honest gap rather than a guessed answer?
• What happens when a draft changes after it has been approved?