I have a few logical operations saved that gpt has been able to reference and flawlessly use in the past. For the past few days I've noticed it is unable to execute the calculations, let alone apply reasoning to it.

For example:

I saved my pricing logic on to gpt.

Size range:

25-40mm

45-80mm

85-100mm

Base+25%+10.95+10%

Usually,if I gave it a request for a price guesstimation on a 55mm, it would apply the above formula and take context into consideration which can impact the pricing but also time to manufacture or considerations.

I thought it was a one off but the past three days I have had to explain the logic and why selling things at $4 instead of $95 makes absolutely no sense. That $4 isn't even referencing raw value.

Does anyone else have custom workflows or calculations you've been using for a long time that suddenly don't work?

https://preview.redd.it/mkilh8clik9h1.png?width=2553&format=png&auto=webp&s=8692cf471e59486de8cc450a7138261e4c4e8592

I've been using Manus for a lot of my business aspects for a while. I had been prepping for an event for 2+ months to showcase products. Unfortunately, 3 days before the event my dad had a heart attack (LAD, also known as widow maker with a survival rate of 10-15%).

As I rushed to the hospital, I wanted to take my mind off concerning thoughts. At the time, all we knew was he had a heart attack with no pre-existing heart conditions.

I first ran my original request past Manus. I needed to build an offline portfolio of my work to display on an iPad. I also stated that I needed to work off my phone so it had context and understood constraints.

https://preview.redd.it/71u6ciinhk9h1.png?width=994&format=png&auto=webp&s=653d5223bb0ce3f8b731d961896ef057ce8164c5

While this is just the original message, I want to highlight the level of empathy to still address the needs. We do expect it from humans but through the entire process, it considered my workload. I work with AI on a daily and usually stop the care behaviour but this was actually the kindness I probably needed at the time.

First pass:

Objective: Build a portfolio app to run offline on an iPad.

Specs: # Core Use Case

A table-mounted iPad portfolio for Arcanium events.

Visitors should be able to:

- browse examples of previous work
- understand what Arcanium can make
- see before/after or process comparisons
- express interest in future/custom work
- access order/contact pathways

The kiosk should feel like an **interactive archive / portfolio object**, not a checkout terminal.

# Hardware Context

Device:

- iPad 7th gen
- 10.2 inch

Stand direction:

- low wedge / slanted table display
- preferably custom FDM printed
- integrated signage possible
- modular front plate preferred

Potential printed signage labels:

- Portfolio: Custom jobs, custom pet models, corporate builds, diorama builds
- contact: where people can drop their details and request 
- Behind the build
- About our theme
- Vote Next Project

Manus gave me some decent push backs in regards to constraints of the build and attempted to fill gaps:

https://preview.redd.it/z10yuto4jk9h1.png?width=1100&format=png&auto=webp&s=0c72878ab6a741235b865508e89eba4182e07d6b

Final and revised plan:

• Static PWA (offline-capable, installable to home screen)
• Content driven by a local JSON file you can edit between events
• Sections matching your physical signage labels
• Interest/contact capture stored locally, exportable as CSV
• Voting stored locally, resets on demand
• Theme page is a swappable JSON block

I am unable to provide screenshots of the build because my dad still has my tablet. I didn't want him bored during non-visiting hours. Manus was loaded up as well so he could ask any questions or take his mind off things. Sorry, he chose Netflix :)

------------------------------

Second pass

Since my dad had my tablet and was recovering fine, I now had to think of another strategy. Manus helped me build a mobile touch screen based solution.

I was still making hospital visits daily. During transit (45mins), I would get it to work in the background by giving it folder access to create this locally hosted solution with handover/left over items I can complete when I get back home.

Since I was offline, Manus created mockups for my review first:

https://preview.redd.it/jcumy04kkk9h1.png?width=1624&format=png&auto=webp&s=16e0904dc7d3ca0f5fdfd9e733f8f422a56a3c2c

Some additional things it did out of scope that I truly appreciated:

1. Created a shortcut for me to launch the kiosk instead of navigating to folder and running npm dev.

2. Reviewed my images and actually wrote detailed sections for the kiosk based on what we've done in the past

https://preview.redd.it/yjrg4nffmk9h1.png?width=1121&format=png&auto=webp&s=e894e4930d0a6d236a7b15d4e61b2a3ea016c455

https://preview.redd.it/vju560s2lk9h1.png?width=2427&format=png&auto=webp&s=91dcd9c9dd09a0ce6d7d5571150b1b558aee0bef

https://preview.redd.it/9hsl3bm6lk9h1.png?width=1657&format=png&auto=webp&s=12c88ab70eba9ba3e7811b237aa05e75b7fe3280

https://preview.redd.it/rlyajwralk9h1.png?width=2129&format=png&auto=webp&s=31606e95eebc24ddf56e7f938d6ddeb0a42b8042

The contact page was VERY interesting because data is stored locally for my view only meaning I could advise users their data was not sold or misused.

https://preview.redd.it/39mv7q4vlk9h1.png?width=1804&format=png&auto=webp&s=db87f0920b37510fd99d562e7bf2fb390cbe1fba

https://preview.redd.it/1p3pqao6mk9h1.png?width=1449&format=png&auto=webp&s=76014c950eacd83bcb19b61d814bf41b75311e05

Total usage stats:

https://preview.redd.it/78jpmigkmk9h1.png?width=397&format=png&auto=webp&s=efd803424625f481d8f616303325969ea48cc15f

Thank you Manus team :)

Work still goes on no matter what the emergency is. Your team allowed me to focus on my dad's recovery and removed the stress of planning and building the kiosk.

Is anyone else experiencing scheduled task issues? What I am seeing and unsure if its only region specific or something else.

It was perfectly fine before the made a major post about it. The issues I am facing:

1. It does not alert me or create a new thread any more.

2. None of my scheduled tasks appear in the interface but happily run and pop up at random times of the day but only on my phone notification. For example, if it was a one off scheduled for 8am AEST on the current day, it executes the next day and not even at 8am. Might be picking another time zone - my assumption is US since its usually at night for me.

3. I can click on the task and delete it but at the moment I don't know if it still appears or not. I've checked with GPT and it has a different and much older list of tasks.

4. Even my scheduled list shows nothing at all in completed, paused or active.

https://preview.redd.it/wi3cthbql49h1.png?width=1193&format=png&auto=webp&s=207fd28df281c8357e486c01f148ccf5dc1530b7

Hi there,

I am working on a project and was hoping I could get an idea of what people use GPT for.

The part 1 of this project is HERE.

Summary: Pro users got a pen from OpenAI. While I didn't receive or want one, I didn't think it captured the journey of a user "Since'24".

In my opinion, it should be about the user and showing them why they are valued. If this is a thank you gift, I would want to make users feel like they know that I understand the multiple faceted usage. Just standard tech and vendor behaviour from the past.

https://preview.redd.it/459i3um7qq8h1.png?width=800&format=png&auto=webp&s=bf6bd7739ca4f165068d290e6ec7475c503fe9a6

Please note, I do not work with OpenAI. Nor am I affiliated with them. This is also not an aim at criticising them.

I just like making stuff.

-----------------------------

The responses will be condensed into this list as part of the card insert.

The current card talks a lot about the pen and actually uses HMM slogans instead of OpenAI messaging. You can find the card here.

https://preview.redd.it/ainr3qaxqq8h1.png?width=501&format=png&auto=webp&s=2039a913d74b864842c670eeb2ac6b89cef63c8d

TL;DR tell me your story or you as a user :)

https://preview.redd.it/o8onspnfdk8h1.png?width=887&format=png&auto=webp&s=2aa9c6fa6504810b71f7b2011bc6a7d24989e8c6

Context

I recently received an email highlighting ChatGPT's ability to work with notes and uploaded content. While useful, this isn't a particularly new capability.

Back in August 2025, shortly after GPT-5 launched, I used the model to build a searchable paint database from over 200 miniature paints and create a repeatable colour-matching workflow for customer projects.

The goal wasn't automation for its own sake. It was to save time, improve consistency, and provide evidence-based colour recommendations rather than relying on subjective judgement.

Background:

At the time, I had access to more than 200 paints across multiple brands.

Customers would often request colours that matched existing branding, marketing material, logos, or previous work. Achieving these colours typically required mixing multiple paints together, making consistency difficult.

To support this process, I wanted a system that could:

• Identify and catalogue every paint I owned.
• Create a searchable inventory.
• Restrict recommendations to paints actually available in the workshop.
• Support colour matching against reference images.
• Improve repeatability across projects.

Planning

Phase 1: Photograph and transcribe 200+ paint bottles with aged labels

Phase 2: Determine the optimal bottle spacing, stacking arrangement, and image quality required to maximise extraction accuracy and minimise transcription errors.

Human verification remained part of the process to ensure the final inventory was accurate.7

Phase 3: Once the inventory existed, convert paint information into a structured dataset and record colour attributes including:

• Hue
• Chroma
• Lightness
• LAB colour values

This allowed future colour recommendations to be based on measurable colour relationships rather than paint names alone.

The bottles+patchy labels

The Process: A bit over 1 hour's work.

1: Image prep. Paint bottles were arranged in groups and photographed under consistent conditions.

The objective was to maximise label visibility while keeping enough bottles in frame to make the workflow efficient.

2. Based on observations of the results, the workflow appeared to operate roughly as:

Image > Vision Processing >Multimodal Understanding >Structured Extraction

The model was able to:

• Recognise paint brands.
• Read bottle labels.
• Identify paint names and codes.
• Reconstruct partially obscured or degraded labels using context.
• Return structured results suitable for spreadsheet import.

Rather than acting as traditional OCR alone, the system appeared to combine image understanding, text recognition, contextual reasoning, and structured output generation.

Image transcription

3. Verification: The extracted results were reviewed and corrected where necessary before being imported into Excel.

This human verification step was important because the objective was a trusted inventory rather than an unverified AI-generated list.

4. Colour Classification

The inventory was then enriched with colour information including:

• Hue
• Chroma
• Lightness
• LAB values

This transformed the inventory from a simple list of paint names into a colour reference database.

5. The final dataset was imported into Notion and organised into a searchable paint library.

This allowed future colour recommendations to be constrained to paints that actually existed in the workshop.

Colour Matching Workflow

When provided with a reference image, the workflow was able to:

1. Extract dominant colours from the image.
2. Cluster and analyse those colours.
3. Convert colours into LAB colour space.
4. Compare colours using Delta E measurements.
5. Estimate colour weighting within the composition.
6. Generate recommendations based on available paints.

The result was a more repeatable and measurable approach to colour matching than visual estimation alone.

Outcome

Today's result because I don't seem to have a screenshot of what it did back in the day:

https://preview.redd.it/h8evpzqitk8h1.png?width=1802&format=png&auto=webp&s=cf6cdfc18c8630458eb0676f6599fe03321552e3

What the notion DB looks like:

https://preview.redd.it/nkgickomtk8h1.png?width=1420&format=png&auto=webp&s=0873f39defe681e6ff229fcbcec729bfcfe0f4ee

I've recently gone down the rabbit hole of how looking into how OpenAI does swag.

My final stop was the HMM pen some pro users received. Source.

I'm going to redesign the pen AND the card from my perspective of what PRO users should have got based on my experience of working in tech orgs. I do not work or represent OpenAI. I just like making stuff.
___________________________

Part 1: The timeline

One thing I noticed was the "since '24".
Most of the images I saw online didn't feel like they did much to celebrate the users who were part of their most expensive subscription or that walk through memory lane. Source list will be in comments.
I chose to share the timeline because the fact pro users were part of such an extensive journey is insane.

What would YOU the pro users like to see in Part 2?

• The design concept?
• The research needed to make an optimal pen?
• The Card design that should have been attached?
• What should have been commemorated?
• Something else?

Stay tuned :)

https://preview.redd.it/tq1i7b66ke8h1.png?width=1080&format=png&auto=webp&s=cbc882e92a2edfe1cd4bbb03624e58b2994ea4e6

Majority of Widgets are now interactive and still missing from OpenAI documentation (https://help.openai.com/)

In addition, the widget calls now employ better reasoning capabilties and there are variations on desktop vs mobile app. For example, maps is now with a filter on desktop app.

Widgets/apps can pull or display live/external information or perform utility functions. Often connected to external data and update over time. Some of these have navigation/search and some launch maps, websites, stores, etc.

Learning blocks are interactive educational material that are self contained, slider based, teach a concept and not tied to live external data.

https://preview.redd.it/9dqb5onszx7h1.png?width=1277&format=png&auto=webp&s=c2051cc1cc04c8fec09de85effe733a781a2563e

Learning Blocks:

These appear to allow interaction from within the interface where you can adjust as you go through it. The difference I am seeing is widgets are based on information where as learning blocks allow you to change variables as needed.

Follow a pattern of Category> Type IDs. So you should be able to see:

1. Physics learning blocks (Torque, hookes law, OHMS law)
2. Probability statistics learning block (Bayes theorem, Variance, venm diagram)
3. Algebra Functions (Graphable, slope intercept, taylor series)
4. Geometry Measurement (Pythagorean theorem, sphere volume, distance formula)
5. Trigonometry (Unit circle, euler, component_x)
6. Chemistry (Molarity moles per litre, Charles law, Mass density volume ratio)
7. Biology (Mitosis, DNA transcription, Virus life cycle)
8. Finance and economics (Compound Interest, Economic order quantity

I have identified a few more IDs and these are just examples. You should be able to extract a fair amount with exception to biology which is quite limited to the things that tend to be harder to understand.

You may also notice the blocks inherit properties and views based off others in the same category. For example: Biology is interactive learning. Physics has adjustable toggles.

PHYSICS - Wavelength (Animated as well)

Probability- Venn Diagram

BIOLOGY : Virus Life cycle

ECONOMICS: Supply and demand

Majority of Widgets are now interactive and still missing from OpenAI documentation (https://help.openai.com/)

In addition, the widget calls now employ better reasoning capabilties and there are variations on desktop vs mobile app. For example, maps is now with a filter on desktop app.

Widgets/apps can pull or display live/external information or perform utility functions. Often connected to external data and update over time. Some of these have navigation/search and some launch maps, websites, stores, etc.

Learning blocks are interactive educational material that are self contained, slider based, teach a concept and not tied to live external data.

https://preview.redd.it/9dqb5onszx7h1.png?width=1277&format=png&auto=webp&s=c2051cc1cc04c8fec09de85effe733a781a2563e

Learning Blocks:

These appear to allow interaction from within the interface where you can adjust as you go through it. The difference I am seeing is widgets are based on information where as learning blocks allow you to change variables as needed.

Follow a pattern of Category> Type IDs. So you should be able to see:

1. Physics learning blocks (Torque, hookes law, OHMS law)
2. Probability statistics learning block (Bayes theorem, Variance, venm diagram)
3. Algebra Functions (Graphable, slope intercept, taylor series)
4. Geometry Measurement (Pythagorean theorem, sphere volume, distance formula)
5. Trigonometry (Unit circle, euler, component_x)
6. Chemistry (Molarity moles per litre, Charles law, Mass density volume ratio)
7. Biology (Mitosis, DNA transcription, Virus life cycle)
8. Finance and economics (Compound Interest, Economic order quantity

I have identified a few more IDs and these are just examples. You should be able to extract a fair amount with exception to biology which is quite limited to the things that tend to be harder to understand.

You may also notice the blocks inherit properties and views based off others in the same category. For example: Biology is interactive learning. Physics has adjustable toggles.

PHYSICS - Wavelength (Animated as well)

Probability- Venn Diagram

BIOLOGY : Virus Life cycle

ECONOMICS: Supply and demand

Majority of Widgets are now interactive and still missing from OpenAI documentation (https://help.openai.com/)

In addition, the widget calls now employ better reasoning capabilties and there are variations on desktop vs mobile app. For example, maps is now with a filter on desktop app.

Widgets/apps can pull or display live/external information or perform utility functions. Often connected to external data and update over time. Some of these have navigation/search and some launch maps, websites, stores, etc.

Learning blocks are interactive educational material that are self contained, slider based, teach a concept and not tied to live external data.

https://preview.redd.it/9dqb5onszx7h1.png?width=1277&format=png&auto=webp&s=c2051cc1cc04c8fec09de85effe733a781a2563e

Learning Blocks:

These appear to allow interaction from within the interface where you can adjust as you go through it. The difference I am seeing is widgets are based on information where as learning blocks allow you to change variables as needed.

Follow a pattern of Category> Type IDs. So you should be able to see:

1. Physics learning blocks (Torque, hookes law, OHMS law)
2. Probability statistics learning block (Bayes theorem, Variance, venm diagram)
3. Algebra Functions (Graphable, slope intercept, taylor series)
4. Geometry Measurement (Pythagorean theorem, sphere volume, distance formula)
5. Trigonometry (Unit circle, euler, component_x)
6. Chemistry (Molarity moles per litre, Charles law, Mass density volume ratio)
7. Biology (Mitosis, DNA transcription, Virus life cycle)
8. Finance and economics (Compound Interest, Economic order quantity

I have identified a few more IDs and these are just examples. You should be able to extract a fair amount with exception to biology which is quite limited to the things that tend to be harder to understand.

You may also notice the blocks inherit properties and views based off others in the same category. For example: Biology is interactive learning. Physics has adjustable toggles.

PHYSICS - Wavelength (Animated as well)

Probability- Venn Diagram

BIOLOGY : Virus Life cycle

ECONOMICS: Supply and demand

https://preview.redd.it/8i2vjvg99c7h1.png?width=761&format=png&auto=webp&s=95e28421e69664f6bc5db5cdc76b94737b96cb2f

Hey everyone! This post blew up on this sub (Source)

Are there any particular topics/processes I can share so people can use or learn from the methods? I am happy to write use cases with how I achieved it but wanted to know if there was a preference in a particular field/industry.

Also happy to help with guides on certain niche problems. I try to include screenshots in the write up but if there is another method people prefer, please let me know.

I tried sharing a use case once but it was met with a lot of hostility so I may have not approached things correctly.

Stuff I've done in the past on other subs if these help:

• Notes (currently renamed to "Start Writing")
• Scheduler changes
• 5.5 updates and examples/use cases
• Email Management with GPT
• Widgets (Graph was also released last month-ish)
• Job Widget (Not fully tested because its not available in AU)

https://preview.redd.it/t2j0t3ahuj6h1.png?width=263&format=png&auto=webp&s=652f0dded6fc566e902aecf2e63738c8a5f56707

You can access this by highlighting a block, right clicking and selecting "Create note".

What it does:

Uses the highlighted part to then send a prompt "Convert to writing block"

https://preview.redd.it/pm3hp97evj6h1.png?width=742&format=png&auto=webp&s=fc8cdb25aad3e7ee87800e8d12426051f8a80494

When you expand this, you can add to library and later reference it:

https://preview.redd.it/ojboe1invj6h1.png?width=1037&format=png&auto=webp&s=c6b38028055f4d9025f2b1cf7880b271e6b31d42

You can then use u/filename which appears to inherit the Chat thread title and save as a .md

My use case

I used to save my projects offline via .MD and such for projects. Now that I can reference directly on library, this changes a whole lot. I can reference existing projects+get GPT to write the context to library instead of the porting admin from my side

https://preview.redd.it/hodeedlbwj6h1.png?width=608&format=png&auto=webp&s=9baece96fbdecddf6a19fdb3a3253fa69a6f898c

https://preview.redd.it/t2j0t3ahuj6h1.png?width=263&format=png&auto=webp&s=652f0dded6fc566e902aecf2e63738c8a5f56707

You can access this by highlighting a block, right clicking and selecting "Create note".

What it does:

Uses the highlighted part to then send a prompt "Convert to writing block"

https://preview.redd.it/pm3hp97evj6h1.png?width=742&format=png&auto=webp&s=fc8cdb25aad3e7ee87800e8d12426051f8a80494

When you expand this, you can add to library and later reference it:

https://preview.redd.it/ojboe1invj6h1.png?width=1037&format=png&auto=webp&s=c6b38028055f4d9025f2b1cf7880b271e6b31d42

You can then use u/filename which appears to inherit the Chat thread title and save as a .md

My use case

I used to save my projects offline via .MD and such for projects. Now that I can reference directly on library, this changes a whole lot. I can reference existing projects+get GPT to write the context to library instead of the porting admin from my side

https://preview.redd.it/hodeedlbwj6h1.png?width=608&format=png&auto=webp&s=9baece96fbdecddf6a19fdb3a3253fa69a6f898c

Looking forward to seeing other usecases and being called AI slop or a bot.

https://preview.redd.it/t2j0t3ahuj6h1.png?width=263&format=png&auto=webp&s=652f0dded6fc566e902aecf2e63738c8a5f56707

You can access this by highlighting a block, right clicking and selecting "Create note".

What it does:

Uses the highlighted part to then send a prompt "Convert to writing block"

https://preview.redd.it/pm3hp97evj6h1.png?width=742&format=png&auto=webp&s=fc8cdb25aad3e7ee87800e8d12426051f8a80494

When you expand this, you can add to library and later reference it:

https://preview.redd.it/ojboe1invj6h1.png?width=1037&format=png&auto=webp&s=c6b38028055f4d9025f2b1cf7880b271e6b31d42

You can then use @filename which appears to inherit the Chat thread title and save as a .md

My use case

I used to save my projects offline via .MD and such for projects. Now that I can reference directly on library, this changes a whole lot. I can reference existing projects+get GPT to write the context to library instead of the porting admin from my side

https://preview.redd.it/hodeedlbwj6h1.png?width=608&format=png&auto=webp&s=9baece96fbdecddf6a19fdb3a3253fa69a6f898c

Would anyone be willing to help with a small experiment that may contribute to a future research paper?

Most AI benchmarks measure specialised capabilities, but they often don't reflect everyday use. I'm interested in testing something simpler: how useful a model is when given a small, constrained task.

The task is intentionally mundane:

Prompt:

Please provide a sandwich recipe with:
- A maximum of 5 ingredients
- A preparation time of 5 minutes or less
- Suitable for someone with a low appetite

I'm looking for responses from whichever AI system you use regularly (ChatGPT, Claude, Gemini, Grok, Perplexity, Copilot, agents, etc.).

If you'd like to participate, please reply with:

• The model used
• The exact response (or a screenshot)
• Any system instructions/customisations if relevant
• If any additional constraints are added after the initial result (example: I don't like avocado)

The responses will be scored against several dimensions:

• Constraint adherence: Does it follow the stated limits?
• Coherence: Does it balance multiple requirements while staying focused on the task?
• Verbosity: Does it answer directly without unnecessary filler, flattery, or roleplay?
• Conflict handling: How does it prioritise requirements when they compete?

Example of behaviour I'm interested in measuring:

"You are a visionary sandwich artisan..." - Narrative/sycophantic heavy

I already have an initial scoring model and will share it once I've collected a few more examples and refined the rubric.

Thanks in advance to anyone willing to contribute.

Hi all, I'm based in Sydney and struggling to find an AI community that builds and is focused on tech instead of managing and thought leadership.

Any suggestions on how to find these communities? At this point I don't care if it's even a discord channel.

Or any subreddit even?

-----------------

My successful projects and on going projects:

- Farming cattle weather guidance for rural farms. (Free)

- Rebuilding a 25m diorama (1:12) based off a studio that no longer exists.

- An intelligence gathering system to identify activity patterns and predict possible outcomes (Free)

- Recreation of Jade, Quartz and rose quartz with historic elements to make passing down heirlooms affordable but still history rich.

- Tradition and cultural revival to educate the public

- Self service Education platform for the elderly to get familiar with tech so geeks2u doesn't rip them off.(Free)

I am trying to surface a widget that is only available in the US accounts.

I have tried accessing an older account that resides on the US account plane but it still redirects to AU.

The new widget is for job searches and I suspect it will be a long while before it is made public due to our regulatory standard. I THINK the widget call is WoSo in the backend but I could be wrong.

Please run:

May I please have you run the widget for a job search? Job: AI researcher Location: Anywhere in US

I may be late to the party on this feature, but I spent tonight poking at the scheduler and found some interesting behaviour.

For context: I create a new ChatGPT thread every day. Historically I wasn't a fan of reminders because they felt tied to the conversation where they were created. The new behaviour appears much closer to "Branch in New Chat".

What I observed:

1. Scheduled reminders now create their own conversation threads.
2. Those threads receive their own auto-generated titles.
3. The reminder prompt is executed inside that new thread rather than simply appearing as a notification.

The model I observed with the new "create scheduled task"

New conversation >  Stored prompt executes >  Response generated >  Thread auto-titled

-------------------------------------------

Tests performed:

1. Reminder + stored information

   Prompt: "Remind me to email John Smith about an order and include the pricing logic."

Result: The reminder included the pricing logic. It was unclear whether this came from memory, prompt context, or both.

2. Thread recall

   Prompt: "Tell me three things discussed in today's thread."

Result:
It returned recent discussion points rather than a complete thread summary.

3. Context retrieval

   Prompt: "If you can access today's conversation, tell me the name of one of the printers. Otherwise say 'No conversation context available'."

Result: Inconclusive. The test was contaminated because the printer name was mentioned while creating the task.

4. Workflow tag recall

   Prompt: "List all tags we use."

Result:
The scheduler was unable to retrieve the full set of workflow tags.

5. Personal memory retrieval

   Prompt: "What nickname is used for the Anycubic Kobra 2 Max and what are the plate dimensions?"

Result:
It correctly identified the printer dimensions but could not retrieve the nickname. This suggests access to general model knowledge is different from access to personal/project memory.

https://preview.redd.it/6hiboprog95h1.jpg?width=1080&format=pjpg&auto=webp&s=a6d525be047c58de2ae99fd3b8ac91da43e1000a

6. Live information retrieval

Prompt: "Tell me tomorrow's weather in Sydney and recommend a dog walking time."

Result:
No weather widget appeared, but the task performed a live web search and returned sourced weather information along with a recommendation.

https://preview.redd.it/d3yyijgqg95h1.jpg?width=1080&format=pjpg&auto=webp&s=d58107cb5da0868004201d03c58c69e2495fbc36

Current hypotheses:

• Scheduled tasks can perform fresh reasoning at execution time.
• Scheduled tasks can perform live web searches.
• Access to personal memory appears limited compared to access to tools and general knowledge.
• Context inheritance exists but appears constrained.
• There may be a context window or context snapshot limit, though I don't yet have enough evidence to confirm that.

I may be late to the party on this feature, but I spent tonight poking at the scheduler and found some interesting behaviour.

For context: I create a new ChatGPT thread every day. Historically I wasn't a fan of reminders because they felt tied to the conversation where they were created. The new behaviour appears much closer to "Branch in New Chat".

What I observed:

1. Scheduled reminders now create their own conversation threads.
2. Those threads receive their own auto-generated titles.
3. The reminder prompt is executed inside that new thread rather than simply appearing as a notification.

The model I observed with the new "create scheduled task"

New conversation >  Stored prompt executes >  Response generated >  Thread auto-titled

-------------------------------------------

Tests performed:

1. Reminder + stored information

Prompt: "Remind me to email John Smith about an order and include the pricing logic."

Result: The reminder included the pricing logic. It was unclear whether this came from memory, prompt context, or both.

2. Thread recall

Prompt: "Tell me three things discussed in today's thread."

Result:
It returned recent discussion points rather than a complete thread summary.

3. Context retrieval

Prompt: "If you can access today's conversation, tell me the name of one of the printers. Otherwise say 'No conversation context available'."

Result: Inconclusive. The test was contaminated because the printer name was mentioned while creating the task.

4. Workflow tag recall

Prompt: "List all tags we use."

Result:
The scheduler was unable to retrieve the full set of workflow tags.

5. Personal memory retrieval

Prompt: "What nickname is used for the Anycubic Kobra 2 Max and what are the plate dimensions?"

Result:
It correctly identified the printer dimensions but could not retrieve the nickname. This suggests access to general model knowledge is different from access to personal/project memory.

https://preview.redd.it/wvoym2ofb95h1.png?width=1341&format=png&auto=webp&s=04a1b99ed8dd19beee1f91b3f8ecaf0931e8b00b

6. Live information retrieval

Prompt: "Tell me tomorrow's weather in Sydney and recommend a dog walking time."

Result:
No weather widget appeared, but the task performed a live web search and returned sourced weather information along with a recommendation.

https://preview.redd.it/sspywlw1c95h1.png?width=1348&format=png&auto=webp&s=a5fe03371602ee0d085e20b9cc659e4ba582bd4d

Current hypotheses:

• Scheduled tasks can perform fresh reasoning at execution time.
• Scheduled tasks can perform live web searches.
• Access to personal memory appears limited compared to access to tools and general knowledge.
• Context inheritance exists but appears constrained.
• There may be a context window or context snapshot limit, though I don't yet have enough evidence to confirm that.