Spotfire Copilot 2.3.5 Improvement Areas

Improvement Areas Identified in TIBCO Spotfire Copilot (Version 2.3.5)

Based on hands-on usage of Spotfire Copilot 2.3.5, the following limitations and improvement opportunities were identified. Addressing these would significantly enhance productivity for both end users and consultants, and would reduce the manual effort currently required in report development,maintenance and usage.

1. Inconsistent Behavior in Contextual Understanding

• Copilot provides inconsistent responses depending on context. For instance, when asked to "Explain Page" or work with IronPython scripts, it redirects by default to Data Function creation rather than addressing the actual request.

• This inconsistency reduces user confidence in the tool and increases the need for manual correction or rephrasing of prompts.

2. Inability to Generate and Bind IronPython Scripts to Action Controls

• Copilot currently lacks the capability to bind IronPython scripts directly to Action Controls.

• This requires users to manually copy the generated script and do the further steps, limiting the extent of automation Copilot can offer for interactive elements.

3. Inability to Modify Existing Data Functions

• Copilot is currently unable to modify or update previously created Data Functions.

• Users are required to manually copy generated Data Functions and paste in Copilot for iterative development.

4. Lack of Support for Automation Jobs

• Automation job creation and configuration is currently unsupported within Copilot.

• This limits Copilot's applicability in end-to-end report lifecycle management, particularly for scheduled or automated processes.

5. Generation of Static Tables Instead of Dynamic Objects

• When generating filtered results, Copilot creates static, non-refreshable tables rather than dynamic, linked data objects.

• This limits the usability of Copilot-generated outputs in live dashboards, as such tables do not update in line with underlying data changes.

6. Functions as a Guide Rather Than a Doer

• Copilot's current functionality is largely advisory, guiding users on how to perform actions rather than executing those actions directly.

• It is expected that Copilot be enhanced to execute authoring actions directly, wherever user permissions allow, thereby reducing manual effort.

7. Natural Language Understanding Requires Improvement

• Copilot's ability to accurately interpret natural language prompts is inconsistent, occasionally resulting in misinterpreted or incomplete responses.

• Improving natural language understanding would enhance the accuracy and reliability of Copilot-generated outputs.

8. Difficulty Handling Multi-Step Problems

• Copilot often struggles to resolve multi-step or sequential requests, tending to address only a portion of the overall task.

• Enhanced support for multi-step reasoning and task decomposition would enable Copilot to handle more complex authoring scenarios end-to-end.

Addressing the above limitations would considerably improve the overall effectiveness of Spotfire Copilot, reducing the manual effort required from both end users and consultants in building, maintaining, and automating reports.