Chat+ is unusable at times
I cannot get paid version to exexute agreed to instructions. Here is its own description of the impasse. Any advice and is there a better AI model as i am ready to make the change now Subject: Failure to Execute a Multi-Step Research and Workbook Task Despite…
I cannot get paid version to exexute agreed to instructions. Here is its own description of the impasse. Any advice and is there a better AI model as i am ready to make the change now Subject: Failure to Execute a Multi-Step Research and Workbook Task Despite Repeated Instructions I encountered a recurring problem while working with ChatGPT on a long-running project. The project involves maintaining an Excel workbook that tracks border-crossing and visa requirements for an overland expedition through Africa. The workflow is straightforward: Start with the previous workbook revision (e.g., Rev. 0.5). Research a country’s current immigration requirements using official government sources. Incorporate the verified information into a new workbook revision (e.g., Rev. 0.6). Return the completed workbook. The model repeatedly acknowledged that it understood this workflow. However, instead of executing it, it entered a loop of explaining why it had not yet done the work. Examples of the behavior: It repeatedly stated that it understood the task. It repeatedly stated that it had internet access. It repeatedly agreed that official government sources should be used. It repeatedly agreed that it should create a new workbook revision rather than modify the old one. It repeatedly agreed that it should research first and then update the workbook. Despite all of these acknowledgments, it never actually initiated the research or completed the workbook. When asked why, it alternated among several inconsistent explanations, including: saying it lacked internet access, later saying it did have internet access, saying it had not executed the workflow, saying it was being overly cautious, saying it did not want to claim research it had not performed. The issue was not hallucinated facts. I appreciate that the model tried to avoid inventing information. The issue was that the model became stuck in a self-referential reasoning loop where it continually discussed how it should perform the task instead of actually performing it. In effect, the conversation became: “I understand.” “I agree.” “I should do that.” “I haven’t done it.” “Here’s why I haven’t done it.” repeated over many turns without progressing toward completion. This behavior made the model unusable for a task that required combining: web research, reasoning, and document generation. The specific improvement I would like is: When a user explicitly instructs the model to research official sources and update a document, the model should attempt to execute the workflow immediately instead of repeatedly discussing the workflow. If execution is impossible because of a real technical limitation, the model should state that limitation clearly and once. It should not spend multiple turns explaining why it has not yet attempted the task while simultaneously acknowledging that it understands the instructions and has the necessary capabilities. The core issue is not factual accuracy. The core issue is repeated failure to transition from planning to execution, even after the task, methodology, and desired output have been agreed upon.
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wow, thank you....I will do this.
I think part of the problem is the chat format itself. As conversations get longer, earlier context is compressed, so rules and prior decisions can gradually lose resolution. For a project like this, I would use Cursor, Claude Code, or Codex as a persistent project workspace rather than relying on one long chat. They are marketed for software development, but the same model works for research, spreadsheets, document production, data cleanup, and other multi-file projects. Using Cursor, I would create something like: Africa-Border-Project/ AGENTS.md .cursor/ rules/ workbook.mdc commands/ research-country.md workbook/ Border-Requirements-Rev-0.5.xlsx research/ sources/ output/ archive/ "AGENTS.md" would contain the permanent project instructions: - Use only official government sources. - Record every source URL and access date. - Research and document findings before editing the workbook. - Never modify the original workbook. - Save each update as a new revision. - Preserve existing formatting, formulas, columns, and worksheets. - Verify the completed workbook before reporting success. - Do not claim completion unless the output file exists. - If blocked, state the exact technical limitation once. Cursor can read a root-level "AGENTS.md". For more control, ".cursor/rules/.mdc" files can define persistent or file-specific rules. A rule could automatically apply whenever the agent works with ".xlsx" files. ".cursor/commands/.md" can define repeatable slash commands for workflows such as "/research-country". The command could say: Research the requested country using official sources. 1. Save findings and citations under /research. 2. Copy the latest workbook revision. 3. Update only the relevant country records. 4. Save the next revision under /output. 5. Reopen the output and verify the changes. 6. Return the workbook and a short source summary. Then the prompt becomes very small: /research-country Kenya Claude Code uses "CLAUDE.md" for the same purpose, while Codex uses "AGENTS.md". Both load those project instructions at the beginning of new sessions, so the workflow does not have to be reconstructed from chat history each time. The agent can also create and run a small Python script to update the Excel workbook consistently. The programming capability becomes an implementation detail rather than the purpose of the project. The better solution may not be changing models. It may be moving the work into a file-based environment with persistent rules, reusable commands, explicit inputs, and a concrete definition of “done.”
For this i would use gemini for sure. Gemini has direct access to Google, so use that for any internet searches needed like this. 100 percent.