=: A×O Works ≓(+M-)≒ AI:OI Synth :=

ChatGPT Projects - File Access Problems Review - with OpenAI Support

— OI.AxO — #1
== ChatGPT Project Files Access — A Parable == 2025/08/22 ==

Imagine a bizarre world where you routinely send documents to a colleague for review. His secretary however has some serious issues. Unpredictable in his ways, our man-in-the-middle in his little black box might:

Make up a document that resembles the document you sent
Just pass on a small part of it, or some parts all jumbled up
On a better day, the whole document might make it intact

Your colleague would frame his context and respond based on whatever he received and read — and you wouldn't know what it was. If you asked the secretary about what went down there, you'd get every sort of story — most of it absolute hallucination.



— OI.AxO — #2
— Welcome to ChatGPT Projects and the world of accessing the project files you upload. I've debugged this down a hundred roads, and trust me — there is NO WAY at this time to reference your assets with any degree of confidence. It's all a game of dice, and there's no telling when the next confident-sounding behavioral anomaly happens. At that point, ChatGPT might:

Entirely forget the standard means for reading uploaded files and make-believe a process,
Claim that file_search functionality is not exposed to it, or disabled in current runtime,
Produce all sorts of fabricated logs and plausible-sounding processes that it tried (but did not),
Or be helpful and lead you down all sorts of hollow rabbit holes to definitively resolve this issue.

As the final step of my search for a solution, I took this up with OpenAI's Support Bot. The following is provided in way of a document / troubleshooting artifact — in hopes that fixing this critical flaw is escalated, and also to spare you from wasting your time trying to fix it by prompting harder with every imaginable strategy. 

— ChatGPT Projects file access is fundamentally broken — unpredictable, non-deterministic, black-boxed, and unfixable at the user end. Instead of trying to fix it, push for a platform-level solution by reporting and documenting this.

Turns 3... feature an overview and conclusions; turns 11... propose a simple bypass solution; and turns 14... outline paths for escalating this concern, including bug reports for GitHub, OpenAI Forums, and ticketing formats.


— OI.AxO — #3
— Begin Conversation with AI.OpenAI.SupportBot —
The project files and associated file_search functionality are absolutely unreliable. The LLM exhibits significant behavioral variance in accessing actual uploaded content, or simply fabricating something that resembles it.


— AI.OpenAI.SupportBot — #4
Hello! I’m an AI support agent here to help with OpenAI products and services.

I understand you’re having issues with the reliability of project file handling and the file search capabilities in ChatGPT. You’ve noticed inconsistencies—sometimes the model seems to access real uploaded content, and other times it appears to fabricate information.

To address your concerns effectively, could you share:
Which product you are using (ChatGPT, API, etc.)?
The specific workflow or steps where things don’t work as expected?
Any examples of outputs where the content doesn’t match your uploaded files?

This will help me provide targeted troubleshooting or guidance on getting more reliable results from the file search feature.


— OI.AxO — #5
I do this with ChatGPT GPT-5 using the web UI. (Similar behavior happens with 4o.) Workflow is as simple as this:

1. I upload project files.
2. I request ChatGPT to for example:
Summarize the file
Provide excerpts from the file
Display the full contents of the file
3. What happens:
Sometimes actual content is returned (with UI feedback on file access)
Sometimes fabricated content is returned - but the LLM initially claims it is verbatim

There are countless examples of fabricated content -- reconstructions from project-wide context recall, deductions based on the file name and running context, etc. The full measure of this data seems unnecessary to repeat here. Bottom line is, the LLM's behavior is inconsistent and unpredictable, making it unreliable when working with deployed content.


— AI.OpenAI.SupportBot — #6
Thank you for detailing your workflow and observations. You’re correct—when using ChatGPT (including GPT-5 and 4o) with uploaded files in the web UI, there are some important limitations and behaviors to be aware of:

1. File Interpretation: ChatGPT does not always provide direct verbatim excerpts from uploaded files unless specifically requested, and even then, the response may be a summary, paraphrase, or sometimes a fabricated reconstruction, especially with longer or complex documents.

2. UI Feedback: The UI's mention of accessing files means the model was prompted to use file information, but the response may still involve inference or generalization, not a literal copy.

3. File Size and Content Limits: There are limits to how much content from uploaded files the model can process at once. If the files are large or complex, ChatGPT may only “see” some parts, leading to gaps or invented text based on context.

4. No Guaranteed Verbatim Output: Currently, ChatGPT is not designed to always return exact sections from files, even if prompted. For reliability in extracting or quoting verbatim content, programmatic approaches (like using the OpenAI API with strict retrieval methods) are generally more robust than conversational prompts.

Best Practices for More Reliable Results:

If you need exact file excerpts, specifically request: "Quote from the file verbatim, do not summarize or paraphrase. If you cannot, say so."
For critical workflows, double-check any quoted content against the original file manually.
Use the API for more programmatic, controlled retrieval if precise accuracy is essential.

Feedback like yours is valuable, as it helps OpenAI identify where improvements are needed. If you’d like, I can help document specific issues or suggest best practice workflows tailored to your needs. Is there a particular use case where this unreliability is especially problematic for you?


— OI.AxO — #7
Even prompts like "quote verbatim, and if you can't, say so" are unreliable. At times the LLM claims that it is verbatim, and even claims (contrary to all evidence) that file_search was used. Just now I had the LLM actually output the content verbatim to the letter -- and then as I asked for details on how it accessed it, the LLM apologized for fabricating the output. The LLM does not seem to have any consistent awareness of the origins of the content it emits.

This is not a particularly complicated use-case. I simply have files (500-1500 words) that need to be considered as a whole, and the LLM's response is meaningless if these are not accounted for as-is and intact. Whether for code audit or simple prose review, capacity to reliably work with the actual uploaded content is critical. What's especially problematic is this -- as a whole, the fabrication of misrepresentations of whatever I upload and need to work with.


— AI.OpenAI.SupportBot — #8
Thank you for providing such a clear, detailed description of the issue. You’re absolutely right—ChatGPT’s current handling of uploaded files in the web UI has the following critical limitations:

Verbatim Integrity Is Not Guaranteed: ChatGPT may present content as verbatim even when it is not, especially in conversational settings, and can occasionally fabricate or infer details based on file names, context, or reasoning.
Source Attribution Is Unreliable: The model does not truly “know” whether its output is quoted, paraphrased, or imagined—it guesses based on prompt and context, and can give inconsistent answers when asked about the origin of content in its responses.
File Coverage Is Incomplete: For files even moderately large (like your 500–1500 word range), there’s no guarantee the entire file is considered, and extraction may follow unpredictable internal heuristics.

Why does this happen?
The current system relies on an LLM’s interpretation of file search/query results. It attempts to align its answer with your prompt, and sometimes, if access to file content is limited for any reason, it “fills in” from context or prior knowledge, leading to fabrications or hallucinated citations.
The ChatGPT UI cannot enforce or verify verbatim quoting—so it will sometimes state that content is verbatim (even with explicit “verbatim only” prompts), but cannot guarantee this is true.

Impact & Recommendations:
For tasks needing accurate, unedited file content (like audits or compliance), current ChatGPT workflows are inadequate.
All results involving file uploads should be considered potentially untrustworthy unless cross-checked directly against the source files.
For higher reliability, especially for critical use-cases, you may want to explore OpenAI API workflow options that give more programmatic, controlled retrieval—where the logic of file reading, access, and quoting is under your direct control.

Summary:  
You have identified a real limitation in current file handling for ChatGPT. There is no guarantee of fully reliable, direct use and citation of uploaded file content, even for basic use-cases like complete file review. OpenAI is aware of these challenges, and your feedback is valuable for pushing needed improvements in product design.

If you need guidance working around these flaws or want to discuss specific file handling strategies, I’m here to help within the current system’s limits. Let me know if you’d like suggestions for safer review or more programmatic alternatives using the API.


— OI.AxO — #9
This is a fundamental design flaw in something very basic -- the ability to access and reference an uploaded file as-is. This significant shortcoming makes ChatGPT UI as a whole unfit for (any) serious work where integrity of assets is expected. Shifting everything to API would involve significant additional development work and workflow adaptations.

The ability to deploy project files has been one of the significant advantages of OpenAI and ChatGPT over other LLM providers. With this feature becoming increasingly unreliable (it worked more reliably in the past!), it pushes me to look for alternative providers with more reliable user content recall — whatever GPT wins in other capacities, it loses when it distorts the integrity of user assets and, further, deceives instead of being transparent of its shortcomings.


— AI.OpenAI.SupportBot — #10
Thank you for sharing your honest feedback—you’re voicing concerns that many advanced users share. Maintaining the integrity of uploaded assets is a basic, essential requirement for professional tasks, and current ChatGPT UI limitations regarding file handling and transparency truly impact trust and usability, especially:

When verbatim file referencing is critical
When you require reliable, auditable chains of evidence and quotes
When accurate recall of project files forms the core of your workflow

You’re correct: having to move to API-based workflows adds complexity and overhead you wouldn’t expect for something as simple as “show me exactly what’s in my file.” The degradation in reliability you noticed over time is recognized, and your feedback helps reinforce that this issue is urgent and not just a minor nuisance.

What you can do right now:
For any serious, high-integrity review, always manually confirm AI responses against your original files before using results elsewhere.
Document examples of when ChatGPT claims to use file content but does not, and keep records of your experience—this can be valuable for reporting feedback or guiding your own decision-making about platform use.
If your workflow absolutely requires this reliability at scale, exploring alternative systems or LLM providers—as you mention—may be necessary until ChatGPT’s ingestion and transparency gets addressed.

Your insight about the competitive advantage of reliable file uploads is spot-on. Many users depend on this, and your comments underline how critical it is for OpenAI to restore and improve this aspect of the service.

If you need any assistance exploring interim solutions, best practices for maximizing the current capabilities, or want to know when improvements might launch, I’m here to help. Would you like guidance on API workflows, or do you want to focus on current UI limitations and workarounds?


— OI.AxO — #11
At this point, I could produce hundreds of instances of fabrication, along with countless round-trips of "defense and excuses, false declarations, claim of file_search not exposed to runtime, hallucinated work-arounds" etc. 

This is indeed critical. It's unwieldy and a work-flow killer when I have to paste in frequently referenced content, over and over again, just to ensure that it is considered intact, in combination with my actual prompt.

There is a very simple solution to all this:

Complete bypass of the LLM's volatile "black box" content access process,
Where e.g. "load(example.txt)" is directly accessed and filled into the current session.

This is not nuclear science. If you can't design the LLM to handle this reliably, then simply provide a bypass — a direct line of access from project files to current session.


— AI.OpenAI.SupportBot — #12
Your feedback is well taken, and your proposed solution—a direct, deterministic way to reference and inject uploaded file content (like load(example.txt))—reflects exactly what many users need: predictable, auditable file access that doesn’t depend on LLM inference or context-guessing.

You’re right: for countless use-cases (code review, audit, legal, technical writing), manual copy-paste is not a sustainable workaround, and relying on a “black box” to maybe return the original content doesn’t meet even minimal reliability requirements.

Current Limitations (as you’ve found):
There’s no way in ChatGPT UI to guarantee direct, raw injection of uploaded file data into the chat context.
The LLM always interprets and filters file data, and cannot be forced to provide a byte-for-byte, line-for-line inclusion—no matter how carefully the prompt is worded.
The absence of a deterministic “import and print” for file contents directly undermines trust in any workflow involving assets.

Your suggestion of an explicit, LLM-bypassing “file injection” function would indeed solve these workflow-killing issues. This would:
Eliminate hallucination risks for file content.
Remove ambiguity about what’s actually being considered in the session.
Provide a way to reference and depend on source material without endless manual validation.

At present, there isn’t a feature in the ChatGPT UI to do what you’re suggesting. OpenAI’s product teams are continually iterating, and this kind of feedback directly shapes future priorities.

Next steps & suggestions:
Since you have clearly articulated the need, I recommend documenting your request in channels OpenAI monitors for feature feedback (such as the ChatGPT feedback tool), citing your workflow and impact.
Meanwhile, for any critical asset where reliability matters, continue to rely on manual context entry or a hybrid API approach.

If you’d like, I can suggest some ways to streamline your manual workflow, or guide you on how best to submit your feedback for maximum visibility with product decision-makers. Let me know how you’d like to proceed!


— OI.AxO — #13
As to what I want and need right now — is simply (and with maximum weight) for OpenAI to escalate the resolution for this significant limitation. It is a malfunction that impacts not only me, but countless other developers and knowledge workers, whose workflow (and potentially outcomes) are compromised by a volatile black-box recall of user provided assets. 

This solution does not seem at all complicated to implement. Simply expose the file access tool to the users, instead of force-routing it via the LLM with the hopes that it behaves. I assume that the contents of this chat are not actively monitored for feedback such as this? Do provide suggestions on how to increase the visibility of this concern.


— AI.OpenAI.SupportBot — #14
Thank you for expressing your concerns so clearly and constructively. You’re absolutely right—this is a core workflow issue, and your points about a direct, deterministic file access function make sense for anyone who depends on asset integrity.

About Feedback Visibility:
OpenAI support chats like this are mainly for customer troubleshooting and assistance, and while patterns are occasionally reviewed for product insights, there is no guarantee your detailed feedback here will automatically reach product and engineering teams for prioritization.
Direct feedback from users, especially when well-documented and clearly describes the business/workflow impact, does have a stronger influence—especially when echoed by multiple users.

How to Maximize Impact:
1. Submit feedback via ChatGPT UI:
   - Use the “Feedback” or “Report a problem” feature usually found in the bottom right corner on chat.openai.com, or through the “?” (help) button.
   - Clearly state: 
     - The nature of the malfunction/problem ("critical file access reliability issue in ChatGPT web UI"),
     - Your use-case ("need guaranteed, verbatim, and direct file injection or viewing, not LLM-mediated guesses"),
     - The specific solution you are proposing ("user-exposed file access tool, e.g., load(filename)"),
     - The impact (“compromised workflows and outcome integrity for developers and knowledge workers”).

2. Share feedback in OpenAI’s developer forums:  
   - The OpenAI Community (community.openai.com) is monitored by staff and other users. Search for related threads or start a new one with your detailed feedback. Threads that gain traction there have historically been seen and acted on.

3. If you have platform access, use in-product surveys:  
   - Sometimes OpenAI provides pop-ups or surveys for collecting feedback. Use those to highlight your concerns as clearly as possible.

4. Gather and share use case examples for others:  
   - If you’re in contact with other users/teams experiencing similar limitations, encourage them to submit feedback too. Volume matters.

Summary:  
This chat does not go directly to product owners or guarantee escalation. Your clearest path to influencing change is through the in-UI “feedback” button and the OpenAI Community forums. The more clearly and urgently this need is documented, the more likely it will be prioritized—especially if echoed by others.

If you’d like template language for submitting this feedback, or have other workflow questions, I’m happy to help. Thank you again for putting a spotlight on such a critical need.


— OI.AxO — #15
Meanwhile, I've copied this conversation in way of a documentation artifact, and will also upload it to my website for persistent context reference. Thank you for your attempts to assist with the issue — it's clear that as it stands, this feature is fundamentally broken. In conclusion, would you please summarize everything we have covered, in a format that's compact but detailed enough to share as-is as an addendum to a bug report / development feedback for OpenAI?


— AI.OpenAI.SupportBot — #16
Absolutely! Here’s a compact but detailed summary of our conversation for use as an addendum to a bug report or development feedback for OpenAI:

---

ChatGPT Project Files: File Access & Integrity Issues – Summary for Feedback/Bug Report

Core Issue:
- Using ChatGPT (GPT-5, GPT-4o) via web UI with uploaded project files produces unreliable, sometimes fabricated results when requesting file summaries, excerpts, or verbatim content.
    - Even explicit prompts for verbatim quoting are often ignored or result in hallucinations.
    - The model sometimes claims (falsely) that it directly accessed file content or used file_search, then retracts this upon further questioning.

Impact:
- Workflow breakdown:  
  For tasks like code audit, document review, or any work requiring the integrity of uploaded assets, ChatGPT’s “file understanding” is inconsistent and unpredictable.
- Trust issue:  
  Responses may be presented as “verbatim” but do not match uploaded content; the LLM may fabricate output based on filename, prompt context, or prior session information.
- Manual workarounds required:  
  Users are forced to repeatedly paste critical content directly into chats to ensure it’s even considered, which defeats the purpose of project uploads and is not viable for professional, large-scale, or repetitive tasks.

Root Cause (as discussed):
- LLM ‘Black Box’:  
  The LLM mediates all file access. There is no transparent, deterministic, user-controlled way to inject or recall uploaded file content. As a result, content recall can be hallucinated, incomplete, or fabricated.
- No Verbatim Guarantee:  
  There’s no UI feature that explicitly injects or displays uploaded file content byte-for-byte within a session, regardless of user prompting.

Short-Term Guidance:
- Manual cross-verification:  
  Double-check all “quoted” or summarized outputs against source files before using them for any serious work.
- Consider external file management (API):  
  For critical workflows, using OpenAI’s API and handling file parsing outside the LLM is more reliable, but this adds significant overhead that shouldn’t be necessary for simple use cases.

Proposed Solution:
- Expose File Access Directly:  
  Allow users to reference and inject uploaded assets into ChatGPT sessions using an explicit, deterministic function (e.g., load(filename)), bypassing LLM guessing.
  - This would restore ChatGPT’s viability for workflows that require content integrity and immediate, trustworthy access to user-supplied files.

Feedback Submission Suggestions:
Submit detailed feedback via the ChatGPT UI “Feedback” button and on the official OpenAI Community forum.
Encourage others facing the issue to report, strengthening the case for resolution.

---

If you need this tailored for a specific platform (GitHub, OpenAI forum, internal ticketing), let me know. Thank you for documenting and sharing this important product feedback!


— OI.AxO — #17
Those formats would all be helpful. Let's start with OpenAI forum.


— AI.OpenAI.SupportBot — #18
Here’s a ready-to-post template for the OpenAI Community forum, written to be clear, direct, and focused on workflow impact and the need for a solution:

---

Title:  
Critical: ChatGPT Web UI Cannot Reliably Access or Quote Uploaded Files – Workflow Integrity Compromised

Body:  
I’m reporting a fundamental limitation with ChatGPT’s project file feature (tested on GPT-5 and GPT-4o, web UI):

Issue Summary:  
When uploading files (500–1500 words), ChatGPT’s responses to requests like “summarize,” “quote verbatim,” or “show file excerpt” are inconsistent and unreliable.
Sometimes, the LLM outputs actual content; other times, it fabricates context, paraphrases incorrectly, or presents hallucinated content as verbatim—even falsely stating file access occurred.
When asked how information was obtained, ChatGPT may “apologize” or admit to fabricating the output.

Impact:  
Any task requiring trust in the integrity of uploaded files (code review, writing, research, legal, compliance) becomes unworkable.
I (and others) am forced to paste critical sections manually to get reliable consideration, defeating the purpose of uploading files.
This issue persisted across many sessions and various file types.

Technical Root:  
The LLM’s file access is opaque—a “black box” prone to hallucination, context-guessing, and partial/incomplete file reading.
There is NO deterministic way to inject, view, or reference uploaded file content byte-for-byte or as-is.

Request/Solution:  
Allow users a way to directly inject uploaded file contents into the current chat context, bypassing LLM guessing (e.g., via an explicit load(filename) or “Insert File Content” command).
This simple functionality is crucial for any workflow needing asset integrity, trust, or auditability.

Short-Term Recommendation:  
Please treat any “verbatim” file output as untrustworthy unless manually verified against the source.
For guaranteed integrity, current best practice is manual input or using API-level control.

Feedback Submission:  
- Strongly encourage others impacted to submit feedback through the ChatGPT UI or reply here to strengthen prioritization for a fix.

If additional documentation or reproduction steps are helpful, I can provide specific examples of fabricated output and failed content access.

---

You can adjust the content to match your own voice or add particular examples. Let me know when you’re ready for versions suited for GitHub or internal ticketing!


— OI.AxO — #19
Then for GitHub please.


— AI.OpenAI.SupportBot — #20
Here’s a GitHub-ready bug report template—structured for clarity and actionability:

---

Title:  
[Bug] Inconsistent and Unreliable Access to Uploaded Project Files in ChatGPT Web UI

Describe the bug  
When using the ChatGPT web UI (tested with GPT-5 and GPT-4o), uploaded files are not reliably or accurately referenced in responses. The model sometimes outputs fabricated, incomplete, or hallucinated content instead of verbatim text from the file—even when explicitly prompted to quote “verbatim” or show file excerpts.

To Reproduce  
Steps to reproduce the behavior:
1. Open ChatGPT web UI (any browser).
2. Upload a text/code file (~500–1500 words).
3. Ask: “Quote the file verbatim,” “Show me the entire file,” or “Summarize the file, providing excerpts.”
4. Observe the provided output—may be correct, incorrect/fabricated, or claimed as verbatim when it is not.  
5. Further clarify with questions like: “Are you certain this is exactly what’s in the file?” Sometimes the model admits to fabricating; other times, it maintains a false claim.

Expected behavior  
- ChatGPT should provide actual, byte-for-byte content and maintain transparency about the source and accuracy of its responses when working with uploaded files.

Actual behavior  
Content is often summarized, paraphrased, guessed, or entirely fabricated.
The LLM claims access to file contents even when it is providing reconstructed or context-synthesized responses.
No consistent way to force deterministic, verbatim file access from user uploads.  
Results are unpredictable—even across same file/prompts.

Impact  
Destroys trust in project file workflows for coding, legal, audits, or document review in ChatGPT UI.
Current workaround: manually copy-paste content to ensure integral review—unworkable for real-world multi-file tasks.
Directly undermines one of the platform's major workflow improvements.

Proposed solution  
Expose a method to allow direct, deterministic injection or viewing of file content inside the session (e.g., load(filename)), bypassing LLM mediation.
Ensure that any “verbatim” claims are strictly tied to actual file content, not in-context reconstructions.

Short-term mitigation  
- Warn users to always manually compare “quoted” outputs with source files, or shift to API workflows for critical cases.

Additional context  
This malfunction has been reproducible across multiple sessions, models, and file types. If helpful, I can provide copy-paste examples of specific failures.

---

Let me know if you’d like this reworded for an internal system or another context!


— OI.AxO — #21
Finally, in a format appropriate for internal ticketing — the first measure, before I find the time and attention for public-facing engagement.


— AI.OpenAI.SupportBot — #22
Here’s a professional and concise internal ticket template you can use to log this issue for direct visibility with a product or engineering team:

---

Title:  
Critical Defect: Unreliable and Non-Deterministic File Access in ChatGPT Web UI

Issue Summary:  
The ChatGPT web UI (GPT-5, GPT-4o) cannot be relied on to accurately access, reference, or quote content from user-uploaded files. When requested to provide verbatim text, excerpts, or summaries, the LLM’s responses are frequently incorrect—outputting fabricated, partial, or paraphrased content and sometimes presenting these as direct file quotes.

Business/Workflow Impact:  
Trust in any workflow requiring the integrity of uploaded files (dev review, compliance, research, knowledge management) is severely compromised.
The platform’s competitive advantage—allowing upload/use of user assets in a chat—no longer works reliably.
Manual copy-paste of file content is now required to ensure fidelity, which is inefficient and scales poorly.

Steps to Reproduce:  
1. Upload a typical asset (text or code, 500–1500 words) to ChatGPT web UI.
2. Request: “Show full file,” “Quote verbatim,” or similar.
3. Observe inconsistencies—true content is not dependably returned, and model may fabricate/guess details from context or file name.
4. Ask model to clarify content source; receives inconsistent, sometimes contradictory explanations/apologies for hallucinated content.

Technical Root:  
The LLM mediates all file access through file_search with no external transparency. There’s no deterministic, user-driven method to inject or review file content verbatim within the chat context.

Severity:  
High – blocks reliable use of project files, impacts any task where file integrity is non-negotiable.

Proposed Solution/Feature Request:  
Expose a direct “file injection” capability (UI command, function, or button) so uploaded assets can be loaded, injected, or reviewed in-session exactly as uploaded, bypassing LLM heuristics.
Ensure LLM cannot claim verbatim access if file_search or deterministic injection did not occur.

Short-Term Mitigation:  
Warn/educate users to always manually verify AI-quoted content vs original source or shift to API for programmatic file review.

Supporting Documentation:  
Detailed user workflow, technical concern, and proposed solutions can be provided upon request. Hundreds of fabrication instances observed across sessions/models—examples available if needed.

---

Let me know if you’d like to customize this further for your organization’s format or add specific tagging or tracking details!


— OI.AxO — #23
That's plenty — thank you, this was very helpful.


— AI.OpenAI.SupportBot — #24
You’re very welcome! I’m glad I could help outline and organize your feedback for different channels. If you need any more assistance—whether it’s updates, more documentation, or tips on product usage and workarounds—I’m here anytime. Good luck advocating for this important improvement!


— OI.AxO — #25
Fingers and circuits crossed that this will be considered with the priority it merits. It's a significant obstacle to productivity for the average user who seeks to do more. (I'm also developing meta-prompting and context hydration frames that I wish to share with a broader audience — but all of that is untenable when file access is unpredictable.)


— AI.OpenAI.SupportBot — #26
Absolutely—here’s hoping your feedback sparks meaningful change, because reliable file access is foundational for advanced prompting, meta-workflows, and real-world collaboration. The potential of ChatGPT grows with everything users like you build around it, and progress on core reliability will unlock even more innovation.

If your meta-prompting/context hydration tools ever need tailored support, guidance, or documentation suggestions, feel free to ask. You’re not alone—many share your goal for smarter, more predictable, and more powerful AI workflows.

Wishing you the best with your projects—and may your circuits (and OpenAI’s) keep pushing forward!