Ever since GPT-5 dropped, the AI world hasn’t stopped speaking in regards to the sheer vary of issues it may possibly do. Coding, writing help, picture technology, even performing as an autonomous agent, it’s like having all of the issues a chatbot can do at one place. However is GPT-5 truly good? Does it actually outperform earlier OpenAI fashions? Because the launch, I’ve been experimenting GPT-5 with various prompts. I’ve listed a few of them beneath so you possibly can strive them too and see how the mannequin truly performs.
Earlier than we leap into the prompts, take a look at this detailed article on what GPT-5 is and the way it’s totally different from earlier OpenAI fashions.
Let’s begin going although the duties one after the other:
Function: A shared instrument to trace day by day posting progress throughout platforms, rejoice completions, and keep consistency.
Customers & Roles:
- Nitika (Social Media Supervisor) – Oversees all platforms
- Harshit (LinkedIn Supervisor) – Posts: 4/day
- Riya (Instagram Supervisor) – Posts: 4/day
Key Options:
✅ Each day Aim Monitoring: Visible counter for deliberate vs. accomplished posts (4/day/platform).
✅ Confetti Celebration: Prompt animated confetti when a put up is logged as “finished.”
✅ Easy Interface: Shade-coded by platform (e.g., LinkedIn = blue, Instagram = purple).
✅ Collaboration: Notes part for every put up to share hyperlinks or feedback.Instance Workflow:
- Harshit logs a LinkedIn put up → counter updates → CONFETTI!
- Dashboard exhibits: *”3/4 posts finished for LinkedIn | 1/4 for Instagram”*.
Bonus: Weekly abstract report auto-generated each Friday.
Output:
Remark:
The social media tracker prototype completely executes all requested options—clear job assignments, correct put up monitoring (4/day/platform), and satisfying confetti animations upon completion. The inclusion of each day by day progress views and weekly summaries makes it sensible for staff coordination. With its clear interface and well-documented JSON construction (together with platform-specific colour codes and motivational prompts), this serves as a wonderful developer reference. Minor enhancements like post-type categorization might strengthen V2, however the present model already delivers a strong basis for manufacturing.
Process 2: Create a Guess the Phrase Sport
Create a cute and interactive UI for a “Guess the Phrase” recreation the place the participant is aware of a secret phrase and gives 3 quick clues (max 10 phrases every). The AI then has 3 makes an attempt to guess the phrase. If the AI guesses accurately, it wins; in any other case, the participant wins.
Output:
Remark:
Whereas the sport delivers a enjoyable expertise with its cute UI and clean gameplay, it presently lacks the core characteristic the place the participant can enter the key phrase for the AI to guess. Implementing this could make it totally align with the unique immediate. That mentioned, the confetti celebration, clear design, and responsive suggestions make it an interesting prototype. With the word-input mechanic added, this might be an ideal 10/10!
Process 3: Examination Prepration
I’m making ready for an examination on Agentic AI and have lined primary/intermediate subjects like:
- Definition and core rules of Agentic AI
- Variations between SLMs and LLMs in agentic programs
- Function of reinforcement studying in autonomous brokers
- Moral issues in agentic AI deployment
- NVIDIA’s analysis on SLMs for agentic workflows
Create a 10-question MCQ take a look at with:
- 4 choices per query (single appropriate reply)
- Closing rating report with % appropriate
- Detailed clarification for any incorrect solutions, citing sources
Output:
Remark:
Wow! Killer MCQ take a look at for Agentic AI prep! Brief however highly effective questions nail all key ideas – autonomy, instruments, ethics. Prompt suggestions explains each reply with actual examples (like how agentic AI books journeys otherwise than chatbots). Completely mimics exams with 60-second timed questions. Paste your syllabus to customise it. 10/10 for making research enjoyable AND efficient. Greatest examination hack ever!
Process 4: Operational Duties
I needed to fill some trackers for the weekly evaluation, as a substitute of doing it manually, I requested GPT-5 to get the data for me.
Give me record of all of the posts and their hyperlink posted on these channel on and afater 1st of august 2025 – https://www.instagram.com/analytics_vidhya/, https://www.linkedin.com/firm/analytics-vidhya/
Output format is a desk – Date | Post_url | platform
Output:

Remark:
I tried to automate knowledge assortment for weekly evaluation by asking GPT-5 to retrieve posts from Analytics Vidhya’s Instagram and LinkedIn (posted on or after August 1, 2025). The output was incomplete, whereas each platforms sometimes publish 4 posts per day (totaling ~25–32 posts per platform for the interval), GPT-5 returned far fewer entries.
Because the GPT-5 did not seize the complete dataset precisely, I went to Manus AI and obtained the duty finished!
Process 5: Reasoning and Picture Evaluation
I beforehand tried this job with OpenAI’s o3 and o4-mini and each failed at it. To know extra checkout my earlier weblog on – 6 o3 Prompts You Should Strive Immediately. Let’s see if GPT-5 is ready to remedy this!
Present a listing of all of the particular person within the drawing together with the colour they’re drawn with.

Output:

Incorrect reply. Additionally, as this was a reasoning query the GPT-5 considering mode ought to have answered to this, however the reply was given by the traditional GPT-5 model. I chosen the considering mode manually to see if it may possibly reply higher. Right here’s the output:

The response stays incorrect regardless of utilizing Pondering Mode. Primarily based on this efficiency, GPT-5’s reasoning capabilities don’t seem to satisfy OpenAI’s marketed benchmarks for the sort of complicated question. I anticipated extra correct outcomes.
Process 6: Picture Technology
Once more, I’m making an attempt to match the picture technology skills of GPT-5 vs GPT 4o. I beforehand tried the next immediate in my previous article on – 4o Picture Technology is SUPER COOL.
Create a 4-image story based mostly on the next sequence:
GPT-4o believes it’s the best mannequin on the market.
GPT-4.5 arrives and surpasses GPT-4o in efficiency.
GPT-4o places in exhausting work to enhance itself.
GPT-4o turns into smarter by mastering picture technology.
Output:

Remark:
It’s clear that GPT-5’s picture technology represents a big step backward from GPT-4o. The mannequin struggles with:
- Textual content Rendering – Fails to precisely incorporate or show textual content inside pictures
- Picture High quality – Produces noticeably lower-resolution outputs with extra artifacts
- Immediate Adherence – Steadily misunderstands or ignores particular requests
For a supposedly improved mannequin, these regressions in core performance are unacceptable.
Finish Be aware
Whereas GPT-5 performs properly on coding duties, its shortcomings in reasoning, picture technology, and basic help (beforehand ChatGPT’s strongest promoting factors) make it a downgrade for many sensible makes use of. The attraction of ChatGPT was its versatility as an AI assistant for on a regular basis duties, not simply coding (the place specialised instruments exist already).
Personally, I discovered the general expertise underwhelming, the mannequin did not ship the tangible worth I’d come to anticipate from earlier variations (like o3’s reasoning or GPT-4o’s picture technology). The shortage of mannequin transparency (no seen indicator of which model is producing responses) solely provides to the uncertainty.
Check out some prompts your self in GPT 5 and let me know your suggestions within the remark part beneath.
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