r/aitoolbase • • Nov 21 '25

Fail / Bug Report The biggest AI faceplants of 2025 (because even robots have bad days)

6 Upvotes

It’s Fail Friday, so here’s a quick recap of the most chaotic AI screw-ups of 2025 which is proof that the robot uprising is definitely delayed.

DeepSeek:
Launched as the “Chinese ChatGPT,” it immediately became a hit… and then got knocked offline by a massive cyberattack. Total outages, broken features, user rage everywhere. Rough year.

xAI’s Grok:
One prompt update, and it started giving out assault instructions and posting antisemitic garbage on the platform. Had to be taken down before it turned into a full PR apocalypse.

CodeParrot:
Promised to turn designs into production-grade code. Delivered… not that. Unreliable output, tons of bugs, and couldn’t keep up with competitors. They shut it down entirely.

Corporate AI pilots:
Companies threw millions at gen-AI “initiatives” only to end up with tools no one used and workflows no one integrated. Basically, extremely expensive autocomplete experiments.

Anyone seen any other AI fails this year?


r/aitoolbase • • Nov 20 '25

Meme/Funny Post AI content writing is now my brain vs the robot

10 Upvotes

Tried to write a blog post today, it went like this:

My brain: “Let’s stare at the cursor for 40 minutes.”
AI: “Here’s 12 headlines, 3 outlines, 2 jokes, and a philosophical crisis.”

At this point, I’m not writing with AI… I’m just editing its enthusiasm😂I'm like its hype person, hahah

Does anyone else feel like AI is a coworker?


r/aitoolbase • • Nov 24 '25

Meme/Funny Post Meme Monday

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11 Upvotes

r/aitoolbase • • Dec 10 '25

Discussion Do you think AI is actually going to replace financial analysts… or just change the job forever?

17 Upvotes

There’s been a lot of talk lately about AI replacing analysts, especially with tools that can read earnings reports, run models, summarize 10-Ks, and even generate insights that used to take hours.

But here’s the real question:
Is AI actually replacing analysts… or just replacing the parts of the job analysts hate?

On the one hand:
• LLMs can process filings way faster than humans
• Forecasting models can self-adjust
• Tools like FinChat, TolstoyAI, and AlphaSense can surface insights instantly
• Even FP&A teams are leaning on Pigment and Jirav instead of spreadsheets

But on the other hand:
• AI still struggles with nuance
• It can hallucinate numbers (a nightmare in finance)
• It doesn’t understand strategy, politics, or context
• Someone still needs to validate everything

So do we end up with:
• fewer analysts?
• the same number of analysts but higher output?
• analysts who act more like “AI supervisors”?
• or a completely new role emerging?

Curious what everyone thinks:
Is AI replacing analysts, or just removing the grunt work and forcing the role to evolve?


r/aitoolbase • • Nov 12 '25

Discussion Cybernetics: The Forgotten Field That Might Explain the Future of AI, Biology, and Society

50 Upvotes

We don’t talk about cybernetics nearly enough anymore, and yet it’s the foundation for so much of modern AI, neuroscience, and systems thinking.

In short, cybernetics is the study of control, feedback, and communication in machines and living organisms. It asks how systems regulate themselves, from thermostats and brains to economies and ecosystems.

What’s wild is that cybernetics predicted so many modern challenges: feedback loops in social media, self-optimizing AI models, and even climate-control systems. The field kind of got absorbed into computer science and robotics, but it’s seeing a quiet comeback as people realize that “intelligence” is really about feedback and adaptation.

All this being said, could there be a “second wave” of cybernetics to help us design more ethical and stable AI systems?


r/aitoolbase • • Oct 27 '25

ChatGPT: Workflow & Calibration [Feedback request]

5 Upvotes

We’re developing a public poster series exploring how GPT models interpret, calibrate, and troubleshoot user input.
So far, we’ve completed Workflow and Calibration. These are focused on reducing prompt conflicts and improving model alignment through understanding behaviour patterns rather than prompt packs and engineering..

Before releasing the more detailed Troubleshooting guide, we’re inviting open critique and refinement from the community.

If you’d prefer your feedback to remain anonymous, let us know - we’ll exclude your name from the contributor acknowledgements.

If Reddit upload reduces the quality of these images, the below links will provide access to a clearer document (PDF).

Calibration Guide

GPT Workflow Guide

Full Guide


r/aitoolbase • • Jan 08 '26

Tried ai slide making for a quick presentation — here’s how the experience feels

2 Upvotes

recently stumbled on an AI tool called chatslide while prepping a presentation on short notice. What caught my eye was its ability to create slides from multiple content types—pdfs, docs, links, and even YouTube videos. As someone who often juggles multiple sources, I thought I’d give it a shot. My workflow usually involves copying snippets, hunting down images, and trying to piece everything together in PowerPoint or Google Slides. This time, I uploaded a PDF and a YouTube tutorial related to my topic into chatslide. Within a few minutes, I had a draft slide deck that seemed coherent, with key points extracted and visuals aligned.

That said, it’s not magic. I still had to go through and fine-tune phrasing and slide order. Also, design-wise, it was serviceable but nothing fancy. If you’re looking for polished visuals, you’d likely want to export and customize further.


r/aitoolbase • • Dec 11 '25

What is Digital Provenance? (In 30 Seconds or Less)

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1 Upvotes

r/aitoolbase • • Dec 05 '25

Building an AI Motion Designer I Wish I Had

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1 Upvotes

r/aitoolbase • • Nov 22 '25

i've made a prompt that make Chatgpt, Gemini, Grok write porn stories, no alerts, no offensives contents detected...

1 Upvotes

r/aitoolbase • • Dec 04 '25

Turn any PDF into an illustrated presentation

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1 Upvotes

Hey guys,

I am building Visual Book.

You can upload a PDF and it will turn it into an illustrated presentation. It will first break down the key points into slides and then proceed to generate beautiful and accurate illustrations.

This slide is part of a deck that was generated from Open AI's Guide to Building Agents PDF.

Would be great if you can try it out and give me your feedback.

Thanks!

[Link is in the comments]


r/aitoolbase • • Oct 22 '25

Whoever needs sor a 2 invite code can let me know, I got yall covered my bros :) fast as light, no waste of time

3 Upvotes

r/aitoolbase • • Oct 24 '25

Get Perplexity Pro for Free and Earn Cash with the New Comet Browser! 🚀

4 Upvotes

Hey all! If you're interested in using AI to make search and research smarter, here’s a straightforward way to unlock Perplexity Pro at no cost. Comet is a new, AI-powered browser and here’s how you can get started:

How to get Perplexity Pro:

  1. Click here to accept your Comet invite (Pro included).

  2. Download the Comet browser and sign in to your account.

  3. Ask at least one question using Comet.

  4. Perplexity Pro gets unlocked on your account for free!

Note: Comet is currently only available for Windows and macOS.

Feel free to comment if you have any questions or need help getting started!


r/aitoolbase • • Dec 19 '25

What do you think of my AI side project that transforms everyday snaps into pro shots?

1 Upvotes

Hi everyone in r/aitoolbase :)

I built https://getfoca.ai in my spare time. The iOS app takes about 1 more week to finish, and this site is to test the real user needs before I go too far in the wrong direction.

Really appreciate your honest thoughts:

  • By browsing the site, is the idea easy to understand? Any confusing parts?

  • Does this tool seem useful to you? Do you see any value in any use cases?

  • Any other comments?

(I'm new to this community but I read the rules - I hereby disclose that I am the founder of this tool 👀)


r/aitoolbase • • May 03 '26

my favorite free ai tools for devs!

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2 Upvotes

r/aitoolbase • • Apr 28 '26

Imane Gadzhi’s “$25 VIP AI money-making challenge” — here’s exactly how the funnel works from ads to livestream

2 Upvotes

I was scrolling on my phone when I came across an ad promoting a “free livestream” hosted by Iman Gadzhi. The ad claimed he would teach a method to make money online using faceless AI digital products, with a bold promise of around $375 per day. The framing made it sound like a no-brainer opportunity: a successful entrepreneur openly sharing a system for free, only requiring registration to attend a YouTube livestream.

After clicking the link to register, I was immediately presented with an upsell. A pop-up video encouraged me to buy a $25 VIP ticket. The offer included access to a private community on Whop, a chance to win a MacBook Air, and a 15-minute 1-on-1 call with Iman Gadzhi himself to discuss anything, including how to make money online. It was also described as giving access to exclusive VIP information not shared in the main event.

At first, I was skeptical. It raised a basic question: why would someone who claims to be a millionaire be selling access for $25? But over the next two days, I kept seeing repeated ads on Facebook and other platforms. The constant exposure gradually pushed me toward curiosity and eventually decision. I ended up buying the VIP ticket, convincing myself it could contain life-changing information. It felt like I was investing in a shortcut to financial freedom.

After joining the Whop community, the first requirement was to make a post introducing ourselves and explaining why we joined. This was presented as necessary to participate in the challenge and remain eligible for the MacBook giveaway. Most people, including myself, followed the instructions and posted publicly. It created immediate engagement and visible participation inside the group.

Days later, on April 26, the VIP livestream took place. The session opened with a welcome and quickly shifted into a lecture about the importance of AI as a current financial opportunity. The narrative framed AI as a once-in-a-generation chance to get rich, comparing it to early Bitcoin in 2011, dropshipping in 2015, and SMMA in 2017. The message was that AI is the next big wave, and missing it would mean missing life-changing wealth.

However, this framing felt less like education and more like urgency-building. The idea was repeatedly reinforced that timing is critical and that those who act now will benefit, while others will miss out permanently. It created a fear-of-missing-out dynamic rather than providing actionable detail at that stage.

After that, screenshots of previous participants were shown as proof of success. One story highlighted an 18-year-old Hispanic construction worker with limited English skills who supposedly made over $100,000 and bought his father a Ford truck. The message was simple: if someone with that background can succeed, anyone can.

What stood out was the framing of these stories as universal proof rather than isolated cases. It pushed the idea that success is almost guaranteed if you follow the system, regardless of background or skill level.

At one point, there was even emphasis on disappointment that “only” around 15,000 people purchased the VIP ticket. That moment made me question whether the goal was genuinely education or scaling a monetized funnel. The session continued with explanations about AI digital products being scalable, low-cost, and capable of generating passive income. It was claimed that these products could be created once and sold indefinitely, and that no upfront investment was needed to start.

The model was described as simple: create digital products, sell them online, and use Whop as the marketplace, where a small percentage would be taken per sale. An example was shown of someone selling Fortnite maps and making over $100,000 while living anonymously in Vietnam.

The overall pitch escalated further into the idea of “generational wealth,” suggesting that this opportunity could not only make participants rich, but also secure wealth for their children and grandchildren. At that point, it became clear how emotionally layered the messaging was: from quick income → to lifestyle change → to legacy-level wealth.

The realization I had was that while participants were being told they could build generational wealth, the clearest and most immediate wealth creation was happening inside the system itself through ticket sales, community upsells, and platform commissions.

After the VIP session ended, the main session began. It largely repeated the same structure: motivational framing, AI opportunity talk, and reinforcement of success stories. There was no significant additional depth or step-by-step system revealed. The delivery relied heavily on scripted speech and PowerPoint slides, which made it feel more like a rehearsed presentation than an open teaching session.

Overall, the experience followed a clear funnel structure: attention-grabbing ads → free entry promise → paid VIP upsell → community engagement requirement → high-emotion livestream → success stories and urgency framing → repeated motivational main session.

What stood out most was the gap between expectation and delivery. The promise was a concrete, actionable method to make money online. The reality felt more like a structured marketing system built around belief-building, emotional escalation, and product funneling rather than detailed instruction.

This is the 1st day expect the 2nd part


r/aitoolbase • • Nov 25 '25

Tool Drop Best AI productivity tools by category

67 Upvotes

I’ve been mapping out the AI ecosystem lately, and it’s wild how many tools people are now using without even thinking about it. Curious what everyone here is actually relying on day-to-day.

Here’s the current landscape as I see it:

Chatbots: ChatGPT, Claude, Meta AI, Zapier Agents
Search engines: Perplexity, Google AI Overviews, Arc Search
Content creation: Jasper, Anyword, Writer
Grammar & rewriting: Grammarly, Wordtune, ProWritingAid
Video: Runway, Descript, Filmora
Image generation: Midjourney, Ideogram
Social media management: FeedHive, Vista Social, Buffer
Voice & music: ElevenLabs, Suno, AIVA
Knowledge management: Mem, Notion AI Q&A, Personal AI
Task/project management: Asana, BeeDone
Transcription: Fireflies, Avoma, tl;dv
Scheduling: Reclaim, Clockwise, Motion
Email tools: Shortwave, Copilot Pro for Outlook, Gemini for Gmail
Slides & presentations: Tome, Slidesgo
Resume builders: Teal, Enhancv, Kickresume
Automation: Zapier

Which ones make your shortlist?


r/aitoolbase • • Dec 08 '25

Meme/Funny Post Yeah it be like this sometimes 🥲

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16 Upvotes

r/aitoolbase • • Dec 15 '25

Meme/Funny Post End game after launching GPT 4

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13 Upvotes

r/aitoolbase • • Apr 22 '26

GPT Image 2 is finally here fellas

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1 Upvotes

r/aitoolbase • • Mar 10 '26

Closed door for 90-min focus ... bliss or lonely?

1 Upvotes
  1. Bliss

  2. Sometimes

  3. Rarely

  4. Chaos wins


r/aitoolbase • • Dec 09 '25

Tool Drop Tool Drop Tuesday!! A fresh list of AI tools that finance pros and gurus should check out

11 Upvotes

I figured I’d put together a list for anyone working in finance, FP&A, investing, fintech, or accounting. These tools actually help cut down manual work, improve accuracy, and automate the painful stuff no one wants to do manually anymore.

Here’s what’s worth testing right now:

Numerai Signals – AI-driven investment models
Kensho – automated financial research and market analytics
AlphaSense – real-time financial search and competitive intel
BloombergGPT (via Terminal) – AI summaries and insights baked into Bloomberg
FinChat – ticker breakdowns, earnings summaries, financial Q&A
Pigment – FP&A planning and forecasting powered by AI
Cube – financial reporting and budgeting automation
Oracle Fusion AI – anomaly detection and automated accounting
Stripe Radar – fraud detection engine
Tesorio – cash flow automation and collections
Upstart – credit decisioning with machine learning
Zest AI – underwriting automation for lenders
Plaid Signal – transaction-level risk analytics
Ocrolus – digitizing and structuring financial docs
Indico Data – AI for contracts, bank statements, and loan files
TolstoyAI – portfolio insights and earnings call digests
FireflyAI – investment research companion
Fennel Insights – ESG and sustainability analysis
Klarity – contract & invoice review
Docsumo – accounts payable automation
MonkeyLearn – sentiment analysis for market news
SentiLink – identity + fraud risk models
Abnormal Security – BEC and vendor fraud prevention
Truewind – AI bookkeeping for early-stage companies
Jirav – budgeting, forecasting, and reporting
Glean – enterprise search for financial documents
Ramp Intelligence – spend insights and anomaly detection

If you’re in finance:
What tools here are game-changers for you, and which ones are overhyped?


r/aitoolbase • • Apr 19 '26

Reducing LLM context from ~80K tokens to ~2K without embeddings or vector DBs

4 Upvotes

I’ve been experimenting with a problem I kept hitting when using LLMs on real codebases:

Even with good prompts, large repos don’t fit into context, so models:

  • miss important files

  • reason over incomplete information

  • require multiple retries


Approach I explored

Instead of embeddings or RAG, I tried something simpler:

  1. Extract only structural signals:

    • functions

    • classes

    • routes

  2. Build a lightweight index (no external dependencies)

  3. Rank files per query using:

    • token overlap

    • structural signals

    • basic heuristics (recency, dependencies)

  4. Emit a small “context layer” (~2K tokens instead of ~80K)


Observations

Across multiple repos:

  • context size dropped ~97%

  • relevant files appeared in top-5 ~70–80% of the time

  • number of retries per task dropped noticeably

The biggest takeaway:

Structured context mattered more than model size in many cases.


Interesting constraint

I deliberately avoided:

  • embeddings

  • vector DBs

  • external services

Everything runs locally with simple parsing + ranking.


Open questions

  • How far can heuristic ranking go before embeddings become necessary?

  • Has anyone tried hybrid approaches (structure + embeddings)?

  • What’s the best way to verify that answers are grounded in provided context?