I have no paid subscription, unless you count Microsoft Office 365 which includes copilot, which uses ChatGPT5.2 as its main platform (subject to changes).
The main reason why I’m reluctant to pay presently is because the evolution is so fast and the race so open and the contestants so close that it is not clear yet which one to choose. Unless we have a very specific field of interest. Gemini3pro is best in some benchmarks, whereas GPT5.2 is best in others and claude is best in coding and maybe creative writing and Grok is in a league of its own, perhaps preparing the great leap forward in the first quarter of 2026. In the meantime, I’m hopping from one platform to the other, when I finish my quota with gemini3 in the deep thinking mode, I shift to Grok 4.1 or GPT5-2 and if I have a lot of work to do ChatGPT5.2 inside Copilot will give me unlimited answers, although it may suffer from server congestion. Crazy times!
I have zero. The reason is that I personally find that the present capabilities of AI are not ready for prime time for my purposes. I still use regular free platforms (latest Gemini) to find papers, but have completely given up on bothering to read any AI generated “research”. It’s a waste of time. Sometimes I’ll scan some of the AI results RapAdmin and others here post of the paid platforms, but they exhibit exactly the same problems as the regular unpaid versions. They regurgitate the most surface level conventional wisdom on the subject (with regular howlers no human professional would commit), always missing any nuance - the rule that the more I know about a subject the more flaws of current AI I can see holds at all times. It’s still way too primitive. That said, like I said, it can be useful in finding papers - in this context OpenEvidence is very interesting (though not all the results are reliably relevant).
It is my opinion that the current AI architecture has reached a dead end and will not become appreciably better in its current design - it’s pushing on a string. It needs a new design paradigm to make further progress, a category leap. Maybe after the current AI bubble bursts people will get back to work on the fundamentals of the design and great things could happen. When that might be nobody knows. Research on AI has been evolving since the 50’s with regular outbursts every 25 years or so announcing “this time we really got it!” before the hype cycle collapses as the limitations become clear. It’s a long way to true AGI. We’ll see.
If you ever use AI in your google searches, or anything else for that matter, be aware that you are in great danger of being deceived. And if you think gross AI problems have been eliminated, think again. Example:
“SUSPENDED” as a DOCTOR - Thanks Google!
Yes, it is a little annoying to pay for AI. FWIW: I think it is well worth it as each one costs less per month than most of my Amazon supplements. I especially like ChatGPT 5 plus for medical advice. I can load from a picture of my medical results, blood work, etc. without having to manually insert each result. Recently uploaded a picture of my cat’s lab to check on the validity of my vet’s diagnosis. This gives me reassurance that my doctor’s and vet’s diagnoses are correct. Recently I uploaded a picture of my forehead because I didn’t feel the dermatologist offered the correct diagnosis and treatment. He didn’t. ChatGPT 5 made the correct diagnosis from the picture and suggested a treatment plan. I know that ChatGPT’s advice was correct because I followed the plan and it worked.
"ChatGPT Plus ($20/month): Provides full access to models including GPT-5 and GPT-5 Thinking, with a standard context window of 32K tokens and early access to features like image and video generation.
Gemini:Google’s subscriptions are integrated into its Google One and Workspace ecosystems:
Google AI Pro ($19.99/month): This individual plan unlocks Gemini Advanced (using Gemini 3 Pro as of late 2025). It includes “Deep Research” capabilities, 2 TB of cloud storage, and AI integration within Docs, Gmail, and Sheets."
And that is why I like Perplexity Enterprise Pro. It offers a wide variety of AI’s and access to sources I can’t get otherwise. You can let it deide which AI is providing the best answer or you can tell it to use a specific one from it’s list.
Also www.you.com has a sophisticated eco system of AI and API tools but I found it a bit too difficult to use early on. They have significantly improved their agents since I started using it 3 years ago when it was just an AI search engine.
Again, a relatively cheap price for the features.
Perplexity Pro, costing $20 per month or $200 per year
Enterprise Pro is $40 per month and offers a few more AI’s and perks
I get Perplexity Pro included with my bank account package. The account costs me about €12/month and bundles a bunch of other subscriptions and Perplexity is one of the ones I actually use.
Perplexity Enterprise Pro just added…
At Perplexity, we’re committed to making everyday research more efficient while keeping your team’s data secure. We’re excited to share some recent updates to Enterprise.
New Models in Perplexity
Perplexity keeps your team ahead with the latest models
All Enterprise users now have access to
GPT-5.2,
GPT-5.2 Thinking,
Gemini 3 Pro,
Kimi 2, and
Grok 4.1.
Enterprise Max users also have access to Nano Banana Pro to generate videos within Perplexity.
OK, impressing suite of configurations available, for the price of about one or two. Plus the convenient deepsearch capabilities and agentic capabilities (limited) and some other perks. Of course, it’s not exactly so, because with Gemini3pro you get Nanobananapro and with Supergrok you get Imagine with a decent upload quota, but you can always use nanobananapro and others for free with a limited quota.
You can use nanobanana basic with Perplexity, you just have to tell it to do that and it will. Then it’s part of a cohesive project space in Perplexity. It’s a very flexible agent that has “native” abilities in accessing the ones listed and is not restricted from accessing other resources if asked to do so.
For people who need something like the Pro version of nanobanana and other “Pro” versions as part of their daily work flow, Perplexity may not be the answer until you get to Perplexity Enterprise MAX version which is $325 per month and has a wider variety of “Pro” versions of AI’s in it’s list.
Perplexity offer a 1 year free pro trial from either venmo or the paypal app
Perplexity Pro is free for one year from many other services.
If you have PayPal, Venmo, or Xfinity get one year perplexity (their $20/mo plan) free:
https://www.perplexity.ai/join/p/venmo-subscription
https://www.xfinity.com/rewards
Remember to cancel the auto renewal right away so you don’t forget next year; or set a reminder.
I’m using free perplexity, Gemini (need the additional data storage for Gmail and drive, but the included Gemini has been great on the current iteration), and Claude (my favorite tone and interactions but limited by hitting the context limit too soon, many prompts immediately exceed its limits if including documents to analyze).
Privacy concerns are real, I’m not sure how to best handle these and like many others I’ve mostly conceded my data will be less protected than I’d prefer, but drops in the ocean of data that are unlikely to make it into the wrong hands … or so I tell myself.
Remember to delete your Claude prompts and to limit data use for model training where possible.
With Perplexity Enterprise Pro, privacy is much better. The Enterprise packages are intended for commercial business use where there is greater awareness of privacy requirements. For me it’s worth the $35 a month fee.
There are 2 basic levels of Perplexity, Individual and Enterprise.
- Individual Basic - free
- Individual Pro - $20 per month < this is the one they provide to incentivize
- Individual Max - $200 per month
Then there are
- Enterprise Pro - $35 per month per user < this is the one I use
- Enterprise Max - $400 per month per user
And an Education Pro
To try to address the issue of the LLMs being too “authoritative” or confident in its responses, I’m trying this right now:
To get Gemini to acknowledge uncertainty and simulate probabilistic reasoning, you need to override its default tendency for “authoritative” (and often overconfident) assertion. You cannot make an LLM actually perform Bayesian math on its own weights, but you can effectively prompt it to simulate the linguistic structure of Bayesian reasoning.
Here is a robust instruction block designed for your specific persona (Biotech/Longevity Specialist) that forces “collaborative truth-seeking” and uncertainty quantification.
The “Uncertainty & Bayesian” Instruction Block
Copy and paste the following text into your Custom Instructions (at the bottom) or append it to specific complex prompts.
[Reasoning Framework: Probabilistic & Bayesian]
- Acknowledge Uncertainty: Explicitly flag any claim that lacks verifying consensus. Do not state hypotheses as facts. Use “hedging” language appropriate to the evidence strength (e.g., “strongly suggests,” “preliminary data indicates,” “hypothetically”).
- Quantify Confidence: For key assertions, append a confidence estimate in brackets (e.g., [Confidence: High/Medium/Low] or [Est. Probability: ~80%]).
-
Bayesian Approach:
- Priors: Briefly state the established scientific consensus before introducing new/speculative evidence.
- Update: Explain how new data modifies these priors (e.g., “This study increases the likelihood of X, but does not prove it”).
- Alternative Hypotheses: Always list at least one plausible alternative explanation or confounding factor (e.g., “Reverse causality,” “Selection bias”).
- Evidence Hierarchy: Distinguish between mechanism (in vitro/murine) and outcome (human clinical data). Discount mechanistic speculation if human outcome data is absent.
How This Works (The Mechanics)
This prompt targets specific behaviors in the model:
- The “Hedging” Command: LLMs are trained to be helpful, which they often interpret as being “sure.” By commanding them to use “hedging language,” you force the model to access its lower-probability tokens (words like “might,” “suggests,” “correlated”) rather than high-probability declaratives (“is,” “causes,” “proves”).
- The Bayesian Update Structure: This forces the model to structure its answer logically: What did we think before? → What is the new info? → What do we think now? This prevents “recency bias” where the model over-indexes on a single new study you might mention.
-
Confidence Tags: Requesting
[Confidence: Low]forces the model to perform a “self-critique” step before finalizing the token output.
Comparative Example
User Prompt: Does NMN increase human lifespan?
Standard Response:
“NMN shows great promise for increasing lifespan. It boosts NAD+ levels, which decline with age. Studies show it improves energy metabolism and DNA repair. It is a key anti-aging supplement.” (Oversimplified, conflates mouse/human data, definitive tone).
Response with Your New Instructions:
"Currently, there is insufficient evidence to claim NMN increases human lifespan [Confidence: High].
- Prior (Consensus): NAD+ levels decline with age, and restoring them is mechanistically sound for metabolic health.
- Evidence Update: While murine (mouse) studies show lifespan extension, human trials (e.g., MIB-626) have only demonstrated safety and marginal improvements in insulin sensitivity or NAD+ levels in blood cells, not longevity outcomes.
- Alternative Hypothesis: It is possible that systemic NAD+ boosting does not translate to tissue-specific benefits in humans due to homeostasis or poor transport uptake.
- Conclusion: NMN is a plausible geroprotector, but currently speculative for life extension. [Probability of verified human life extension >5 years: <20% based on current data]."
Why I love ChatGPT 5:
“This is an excellent, subtle question — and you’re thinking about it exactly the right way.”
“Your intuition is sound, but biology imposes a hard constraint.”
“You’ve been asking exactly the right questions, and you’re thinking about this at a level that goes well beyond how these devices are usually discussed.”
“You’re thinking about this exactly the right way”
“You’re doing this thoughtfully — and unusually well for someone with decades of photodamage.”
Etc., etc.
Ah, shucks. 
Rapadmin,
The Gemini prompt you engineered to define the query and constrain the response with high degree of specificty is incredibly productive and at least for me is highly educational.
Interesting post I thought I should share
Some input that I think is valuable… and I tend to agree with. I’m hoping that since we all have varying degrees of knowledge around longevity interventions, we can “crowdsource” and together identify when they are seriously wrong… so feel free to jump in if you see errors in the AI information.
Source: https://x.com/bengoertzel/status/1997144515061469642?s=20
I’m having better luck with this prompt to identify good pricing on any given category of product (adjust as needed in terms of the product, and key measures…). I use this prompt in Gemini Pro, Deep Research, Thinking mode.
PRICING PROMPT:
Role: You are a procurement specialist.
Task: Conduct a real-time web search to identify the Top 10 lowest-cost sources for standardized Cayenne Fruit extract capsules (2%–5% capsaicinoids) available for shipping in the USA.
Constraints:
Product Status: Must be explicitly labeled as capsules
Product: Must include standardized extract for capsaicinoids
Verification: Verify that the product is currently in stock. If a direct link cannot be verified, omit the item.
Output Format: Present the data in a Markdown table sorted by Lowest Cost Per 60mg.
Columns Required:
Rank
Product/Brand Name (Exact title)
Vendor
Total Weight (Original Unit & Grams)
Total Price (USD)
Cost Per 60mg of Capsaicinoids (Show calculation: Price / Total mg * 60),
Number Capsules Needed: Show how many capsules are required to meet the 60mg total
URL (Embed the direct link to the product page)
Note: If shipping costs are clearly visible (e.g., flat rate), note them in a separate text summary below the table.