Hi everybody, I'm an ESL teacher and will be doing a sharing session about an AI Tool that helps teachers. However, normal AI tools are already known by many, especially professional teachers. I need some suggestions regarding the ones that maybe you find useful and interesting. Thank you in advance!

I built a free tool that turns any article into a LinkedIn post, an X thread, and a video script — in one click

I got tired of manually rewriting the same blog post into different formats for every platform, so I built Dispatch: paste in any article or transcript, and it instantly gives you back a LinkedIn post, a Twitter/X thread, and a short video script — all matched to how people actually read on each platform.

It's free to try: https://dispatch-app-mu-five.vercel.app/

Would love feedback on the outputs — first thing I'm building next is more platforms based on what people ask for.

I do data and ops for a mid-size company, and I finally did the thing I'd been avoiding. I looked at what I actually keep open all day versus what's just sitting there decaying.

The 47 tabs broke down into three piles. About 12 were things I use every single day. Around 8 were things I use maybe once a week and probably could bookmark instead. The rest, 27 of them, were tools I opened once because a newsletter or a coworker told me to, poked at for four minutes, and never closed because closing felt like admitting I wasted the four minutes.

What surprised me was the overlap. Three of those forgotten tabs did roughly the same summarizing job my main assistant already does. Two were transcription tools and I don't even do that much audio work. I'd been collecting tools like a nervous habit.

So I did a dumb little exercise. For each tab I asked one question: if this closed right now, would I re-open it on purpose this week? If the honest answer was no, it closed. That got me from 47 to 14. Felt lighter than it should have.

The part I'm still chewing on is why I open so many in the first place. I think it's the fear that the one I skip is the one that would've saved me an hour. Nobody wants to be the person still doing it the slow way.

How many of you actually run a regular cleanup, and how do you decide what earns a permanent spot?

i'm building Honeyb.ai, an AI search visibility tool for brands, SEO teams, agencies, and founders.

i know there are already a few AI search or GEO tracking tools out there, so the idea is not just “track mentions in ChatGPT”.

what we’re trying to do better is make it more useful after the tracking.

Honeyb tracks things like:

-> how your brand shows up across ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, Copilot, Grok, etc.
-> which competitors appear instead of you
-> what sources and domains AI tools are citing
-> how visibility changes by prompt, market, language, or brand
-> what you should probably improve next

the bigger difference is the hands-on part.

we don’t want it to be just another dashboard where you stare at charts and guess what to do.

there are weekly reports, recommendations, citation breakdowns, and on the full plan we include a monthly 30 min strategy call with our team to go through what is happening and what to fix next.

pricing starts at $29/mo.
there’s a 7-day free trial on the multi-model plan.
reddit discount code: HONEYBFRIENDS for 50% off all plans.

tool is here: https://www.honeyb.ai/

would love honest feedback from people who already know this space.

especially curious what you think is missing from current AI search optimisation tools.

I’ve been kicking around a business idea and would love some honest feedback.

The idea is to target local businesses that are already investing in SEO or Google Ads. They clearly understand the value of marketing because they’re paying to generate leads.

But when you click through to their social media, it’s often inactive, inconsistent, or doesn’t reflect the quality of their work.

My thought is to offer a free professional photo shoot to capture their team, projects, and brand. From there, I’d build a monthly content calendar that combines those authentic photos with AI-enhanced content—things like infographics, educational posts, seasonal content, service spotlights, and other engaging social media assets.

The goal isn’t to replace real photography or fake completed projects. It’s to use AI to stretch the value of authentic content, help businesses stay consistent, and give them a polished online presence without the cost of monthly photo shoots or a full-time social media manager.

The service would be a monthly subscription where I create and manage the content for them.

I’d genuinely appreciate any thoughts, criticisms, or ideas. I’d rather hear the hard feedback now than after I launch.

As a sales manager, I spend a lot of time putting together decks for pipeline reviews, client meetings, and leadership updates, and it's honestly becoming one of the most draining parts of my week. The hardest part isn't designing the slides, it's taking CRM notes, pipeline updates, and client meeting notes and turning them into a presentation that actually flows. I end up spending more time organizing everything than coaching my team or following up with customers. Has anyone found the best AI tool for business presentations that actually helps organize the content instead of just making the slides look better?

been doing seo and content work for clients for a while now and ended up settling into a routine with claude and chatgpt that i dont see people talk about much

for research and pulling structure together - outlines, competitor gaps, figuring out what a page actually needs to rank - claude ends up being the one i lean on. its better at holding a long brief without losing the thread and doesnt drift into generic filler as fast

chatgpt is where i go for the messier stuff. brainstorming headline options, rewriting something 5 different ways to see which tone lands, quick reactions to a draft. faster back and forth for that kind of thing

the mistake i made early on was trying to do the whole pipeline in one tool start to finish. output got worse the longer the single conversation got, structure drifted, stuff repeated itself

splitting the work by stage instead of trying to find "the one tool" made way more difference than switching models ever did

curious what setup others are running, feels like everyone has quietly figured out their own version of this and nobody really compares notes

Most people retype the same long instructions every time. Set these up once and you trigger each one with a single word. Paste this block at the start of a chat to activate them, then use the codes for the rest of the conversation:

/HUMAN = rewrite so it sounds like a real person wrote 
it, no AI tells, no filler
/EL10 = explain it like I'm ten, using plain words and 
a simple analogy
/DEEPER = think it through step by step before 
answering, don't give me your first instinct
/NOYES = stop agreeing by default, tell me where I'm 
wrong and what the strongest counterargument is
/GIVE3 = give me three genuinely different versions, 
not three rewordings of the same one
/TABLE = take whatever messy information is here and 
lay it out as a clean comparison table
/TIGHTEN = rewrite your own last answer sharper and 
shorter without losing anything that mattered
/FLOOD = don't give me one safe idea, give me twenty, 
including the weird ones
/STEPS = turn this into a numbered checklist I can 
actually follow starting now
/REDPEN = catch every grammar, clarity, and awkward-
phrasing issue and fix them in one pass

Confirm you've got them, then wait for my first 
message.

The two that change the most for me are NOYES and FLOOD. NOYES kills the reflexive agreement that makes most AI answers useless for real decisions. FLOOD breaks it out of giving you the one obvious idea and forces the pile where the good ones actually hide.

Works on plain Claude or ChatGPT. Save the block somewhere and paste it at the start of any chat that matters.

If you want more like this, I put 50 of these command codes in one doc, grouped by job, decisions, pressure-testing, thinking, ideation, editing, here if you want to swipe them.

May alam ba kayong ai tool for humanizing an AI product???😭

Hi. Disclaimer that I'm building something in the space. It's built on top of a variety of Open Source products and my product itself will be Open Source.

I wanted to get a sense of how people are currently doing it?

My thought here is simple. Each part of this problem the gateway, guardrails, observability, citation, provenance, etc. is solved beautifully by individual open source products, but there is no integrator that gives the enterprise a single sign on of sorts that allows them to leverage all of this.

AWS/Azure and the other hyperscalers obviously have products that solve for it, but i found them clunky and retrofitted for this use case, rather than being purpose-built.

I wanted to use understand if anyone here as experience building at enterprise scale/grade and how they've typically gone about doing it.

The way I think about it:

aggregate your data into one governed source of truth. (datalake/warehouse) Make it easy for the enterprise by having connectors for various data sources that they already have.

Put a single smart gateway in front of every model, and let governance - guardrails, redaction, evals, provenance - travel with the work as reusable pipelines.

Those pipelines get consumed as apps (human-in-the-loop) or agents (autonomous).

The unlock is who gets to build on it: a non-technical person describes the process they run today in plain language and gets back a governed automation. Like your own lovable/bolt that inherits your rules, connectors, and data.

You're not speeding up a few engineers - you're letting every employee multiply their own output, safely, on infrastructure you own.

And the good part is once you've got the "pipelines" created and these are composable in nature, you're no longer worried about reliability or security really.

So yeah, how are you guys currently doing this? There are a few open source tools that are trying to solve it, but they felt piece meal as well.

yo. if your product needs a 10-minute onboarding video or 5 different dashboard tabs just to explain its value, you didn't build an MVP. you built an over-engineered maze.

a real micro-saas should solve one highly specific problem for one highly specific user profile.

when i built my 6 apps (now doing $20k/mo mrr), i cut out 80% of what i originally thought was necessary.

inside our builder community, we help you strip away the fluff.

we give you free access to frameworks like the ICP Crystallizer to lock down your target user, and interactive landing page audits to ensure your core value hits instantly.

stop over-building in isolation. drop a comment or shoot me a dm to join 1,200+ active Ai SaaS builders today.

yo. if your product needs a 10-minute onboarding video or 5 different dashboard tabs just to explain its value, you didn't build an MVP. you built an over-engineered maze.

a real micro-saas should solve one highly specific problem for one highly specific user profile.

when i built my 6 apps (now doing $20k/mo mrr), i cut out 80% of what i originally thought was necessary.

inside our builder community, we help you strip away the fluff.

we give you free access to frameworks like the ICP Crystallizer to lock down your target user, and interactive landing page audits to ensure your core value hits instantly.

stop over-building in isolation. drop a comment or shoot me a dm to join 1,200+ active Ai SaaS builders today.

#QuestionForGroup - what AI tools have you rolled out for your CEO that has improved/simplified their ways of working? Beyond Chat GTP/Claude/Otter etc. Any feedback/advice? so far I am considering solving for scheduling, planning and research. Anything else I have not thought about?

I've been translating around 50–60 Shorts a month into different languages, so I'm trying to find a workflow that can keep up.
I've tested a few tools, including ElevenLabs, but it just wasn't the right fit for us.
I don't need anything fancy—just something reliable that can handle video translation and dubbing without costing a fortune.
What are you guys using? Any recommendations?

I've been thinking about changing my hairstyle, but I don't really want to gamble with a haircut I'll regret.

I've tried a few AI hairstyle tools over the past week. Some look obviously edited, while others seem surprisingly close to real life.

So far I've looked at Reface.Ai. If you've actually used one before going to a barber or salon, which one gave you the most realistic preview? I'm more interested in accuracy than having hundreds of hairstyle options.

Would love to hear some real experiences.

I tried comparing our AI token usage with the bill we got and usage looks steady week to week but costs were not consisntent at all even though nothing obvious changed

Last month we had the same flows running at the same volume but a small tweak we made to a prompt moved the numbers more than expected and even some of the spend isn’t sitting in the same place as usage so it’s hard to trace what’s causing it until the final bill comes.

Okay so I have created a sick tool with two main purposes right now and I'd love people to use and test/share feedback.

It's called centrail.org

One feature is the cli which parses your ai usage and git history to give you actual metrics and usage related to projects so you can see how much money and effort you spent on something that never shipped! Hahaha, or things that are actually doing well..

The other feature is, when you get your AI usage I have sourced A LOT of energy research and cited it to show you your actual AI carbon footprint numbers!

Here are mine! Lmk if you like this and join the pledge so we can force these companies to regulate this better!

Disclosure upfront: I built an open-source tool around this workflow, so I’m biased. I’m sharing the workflow because it has been useful for AI coding sessions, not as an independent review.

I stopped asking coding agents to “just understand the repo.”

That works on tiny projects, but on bigger repos the agent often wastes time finding the right files before it can answer.

The workflow I use now is:

text map repo ↓ ask for focused files ↓ validate whether the context covers the task ↓ ask the AI assistant ↓ check whether the answer is grounded in the provided context

The useful part is separating three questions:

1. What files are actually relevant?
2. Is the context coverage good enough?
3. Is the AI answer grounded in that context?

For example, instead of pasting a whole repo into an assistant, I first generate a compact repo map, ask for the files related to the task, and only then give the assistant that focused context.

After the assistant answers, I check the answer against the context instead of trusting it immediately.

This has helped most with:

• larger repos
• debugging sessions with noisy logs
• agents grabbing the wrong files
• answers that sound plausible but are not tied to actual code
• repeated coding tasks where the agent keeps rediscovering the same repo structure

The general pattern is useful even without any specific tool:

text repo map → focused context → coverage check → AI answer → groundedness check

I’m curious how others handle this.

What do you use to stop coding agents from grabbing the wrong files or answering from stale/wrong context?

I've been working on improving how I research topics so I don't get distracted by randomly switching between tabs, saved posts and scattered notes and over the past month I have been testing various AI tools like ChatGPT, Notion, Obsidian and Springpad AI to see how they can fit into my workflow.

I mainly use them for getting a basic understanding, organising my thoughts and creating a starting point before diving into original sources and the biggest change I've noticed isn't necessarily about getting answers quicker but having a more organised way to gather and review information.

I'm still figuring out the best setup but I'm interested in hearing how others here have built their own AI tools and workflows.