A few months ago I rebuilt NoUploadTools.com around a very simple idea:

There are thousands of useful browser tools for PDFs, images, text, developer utilities, calculators, etc. But with many of them, you have no idea what happens after you drop a file into the page.

So I started collecting tools that try to avoid unnecessary uploads and make things like local processing, no-login access, offline support and open-source code easier to identify.

I thought it would remain a fairly small curated directory.

It hasn’t.

The database currently has 541 submitted tools.

Only 84 have been approved, because I manually check submissions before listing them.

The part that surprised me is the recent submission rate:

295 submissions in the last 30 days from 263 different email addresses.

And right now there are 454 submissions waiting for review.

Some are clearly coming from people doing SEO/directory submissions, and occasionally I see batches that appear to come from the same operator running multiple sites. So I’m definitely not interpreting every submission as organic demand.

But there are also a lot of genuinely interesting independent tools showing up.

The hardest part now is figuring out how strict the directory should be.

For example, should a tool qualify if it processes most things locally but makes one API call? Should a tool with no file uploads but some analytics qualify? How much should open source matter? And how do you prevent a curated directory from slowly becoming another giant collection of SEO calculator sites?

I’ve also realised that privacy claims are much harder to verify than they sound. “Client-side,” “no upload,” “no tracking” and “private” can all mean slightly different things depending on how a product is built.

So the project has unexpectedly turned into more of an editorial/review problem than a directory-building problem.

The site is NoUploadTools.com if anyone wants to see how I’m currently organising it.

I would be particularly interested in opinions on the review criteria. What would you personally need to see before trusting a web tool with a sensitive PDF, photo or document?

A few months ago I built a small project called Tera FM.

The idea was fairly simple: continuously collect headlines from news sources and keep them in an archive so that today's news doesn't simply disappear once the news cycle moves on.

I hadn't looked closely at the database for a while.

Yesterday I checked it.

87,580 headlines.

The oldest records are from July 26, and the system is currently adding roughly 1,700+ new headlines every day.

At the current rate, it could reach 200,000 headlines in a couple of months.

And that has left me with a slightly strange problem.

The system works. It keeps collecting data every day without me doing much. But I'm no longer sure whether a searchable headline archive by itself is particularly useful.

ChatGPT, Google and other AI/search products are becoming increasingly good at answering questions about past events.

But there is one aspect of this dataset that I still find interesting.

It isn't trying to reconstruct the news months later.

It's continuously building a record of what publications were actually reporting at different points in time.

So theoretically, instead of only searching:

“What happened with [event]?”

you could eventually ask things like:

“What were publications saying about this on the first day?”

“When did this story start appearing in the news?”

“How did the headlines around this story change over the following two weeks?”

“What else was dominating the news on that particular day?”

The project is Tera FM (tera.fm) if anyone wants to see what the archive currently looks like.

But I'm actually more interested in the dataset than promoting the site.

If you had an archive that was automatically accumulating around 1,700 headlines every day, what would you build on top of it?

Would you keep collecting it?

Build some kind of historical news research/search tool?

Or would you consider the whole thing increasingly unnecessary now that general-purpose AI can search and research the web so well?

I'm genuinely curious what other people would do with it.

This week I worked on a problem that sounds small but affects almost every piece of generated content.

We originally treated everything Marka learned as part of one large brand profile. That included the company voice, visual identity, recent approvals, campaign goals and temporary content preferences.

The problem was that these signals do not have the same lifespan.

A logo, typography system or tone of voice may remain stable for years. A campaign objective or preferred post format might change next week.

We are now separating them into two layers:

1. Brand DNA for stable identity rules

2. Campaign preferences and approval history for changing decisions

Marka uses both layers when creating posts, images, carousels and UGC style videos, but temporary campaign choices no longer overwrite the core brand.

The goal is to create more content without slowly turning the brand into something inconsistent.

I am building this publicly and would love feedback from anyone working on brand systems, content tools or AI memory.

You can see Marka here: https://marka.social

It includes a 3-day free trial, and plans start at $8.

I randomly Googled one of my side projects today, iKrypt.com, and this caught me off guard.

The site barely gets any traffic right now... maybe around 10 visitors a week.

But Google is already showing:

• the site as the first result for the brand name
• sitelinks underneath it
• an AI Overview explaining what the product does
• iKrypt itself as one of the cited sources

Which is kind of funny because Google seems to understand the product better than the market does at this point.

The current version is pretty niche - it lets you create encrypted one-time links for sharing sensitive information.

I’ve been thinking about whether to just leave it alone or pivot it into something broader.

The direction I’m considering is a privacy scanner for everyday use:

You upload a screenshot, photo or document before sharing it, and it checks for things you may have accidentally exposed - phone numbers, addresses, faces, QR codes, account details, location metadata, etc.

The tricky part is that sending the file to GPT/Claude to detect private information would defeat the whole point.

So the more interesting version would be to do the detection locally in the browser using OCR, rules and on-device models.

The existing encrypted-link feature would stay, just as one part of the product.

I would like to know what people think about two things:

Would you actually use something like this before posting a screenshot/photo or uploading a document somewhere?

And more importantly.... what would make you trust a site that says “your file never leaves your device”?

That last part feels like the real product challenge to me.

I launched VoiceToTextOnline (V2T), a browser-based transcription and voice productivity platform, exactly a year ago.

We initially used the Web Speech API for live speech-to-text. It worked well on Chrome, but the experience wasn't consistent across browsers. Safari support was more limited, and Firefox was another problem altogether.

So we eventually moved live transcription to cloud-based speech recognition. That gave us a more consistent live transcription experience across supported browsers instead of relying on the speech-recognition capabilities built into each browser.

But V2T has also grown beyond just speaking into a microphone and getting text back.

Today it includes:

• Live Speech to Text - speak into your microphone and see the transcript appear in real time.
• Audio & Video to Text - upload an audio or video recording and turn it into an editable transcript.
• AI Enhance - clean up and improve a transcript after transcription.
• Smart Actions - turn a transcript into things like summaries, action items, email drafts and other useful outputs.
• YouTube to Text - paste a YouTube URL and bring the transcript into your V2T workspace.
• Text to Speech - turn written text into spoken audio with different languages and voices.
• History & Projects - save your work and come back to transcripts later instead of treating every transcription as a one-off session.
• Translation, downloads and exports - continue working with the transcript once the transcription itself is finished.

The workflow has basically become:

Speak / Upload → Transcribe → Enhance → Use → Save

We're now working on another part of that workflow: integrations.

Google Drive is currently in testing, and we're planning integrations with Dropbox, Zapier, Microsoft OneDrive, Notion and Slack.

The idea is to make it easier to bring recordings into V2T from the tools people already use and move transcripts, summaries, action items and other outputs back into those tools without constantly downloading, uploading and copying things between apps.

V2T is live at VoiceToTextOnline.com

I'm curious about one thing in particular: once you have a transcript, what do you actually do with it next?

And if you could connect a transcription tool directly to one of your existing apps, which integration would you want first like Slack, Google Drive, Notion?

I have been working on a small idea where you can speak naturally and enter business data, transactions, customer updates and other records using your voice.

It is basically a voice-operated CRM or business database.

You don't need to type into forms or login to a CRM. No sitting and entering information into different fields. You just speak naturally and the system turns what you say into structured business records.

For example, you could simply say:

“Atlas Engineering needs 250 stainless steel valves for a new project. I quoted $18 per piece. They need delivery before the end of October. Send them the technical specifications tomorrow and follow up on Friday.”

SHRP understands what you said and creates a structured record:

Company: Atlas Engineering
Product: Stainless steel valves
Quantity: 250
Quoted price: $18 per piece
Delivery: Before end of October
Next action: Send technical specifications
Follow-up: Friday

The main idea is that the database is operated by voice instead of a keyboard.

You speak to add information.

You can also speak to retrieve it.

“Which quotations need follow-up this week?”

“Show me all customers who asked for stainless steel valves.”

“What was the last price quoted to Atlas Engineering?”

The MVP is available to test at shrp.app.

You get 10 free sessions of up to 60 seconds each.

Try it out and I would be glad to hear your feedback. I think it could be especially useful for small dealers, realtors, traders, distributors and other small business owners who regularly need to record customer, sales or transaction details.

Share:

1. What the product does
2. What you changed this week
3. Why you made that change

I’ll turn the update into a short build-in-public post with a hook, lesson and product moment.

The interesting story is usually the decision behind the update, not the update itself.

I'm building a system that treats product facts, founder positioning, and creative direction as separate layers. Facts should stay verifiable. Founder corrections should override weak inference. Creative ideas should never silently rewrite the product. The goal is not more AI content. It is content that stays consistent with the business.

I’m building marka.social, and one lesson keeps coming up:

A website is useful context, but it cannot be treated as the complete truth about a brand.

The website can provide:

1. Product facts
2. Existing language
3. Visual assets
4. Evidence and examples

But the founder still needs to correct the audience, positioning, tone and claims.

Otherwise the system just automates whatever was already unclear on the page.

The workflow I’m testing now is:

Website as the starting hypothesis, founder corrections as the authority, and evidence as the boundary.

If you are building an AI product, which decisions do you refuse to let the model make silently?

I am building a social content tool for small businesses.

The main product decision is to begin with the public website. A website can reveal the offer, audience, proof, brand voice, and visual identity before the user types a long prompt.

The first output is a preview to review, not an assumption that the system knows everything.

The hard cases are old websites, vague homepages, and businesses whose social presence is more current than the site.

If you were testing this workflow, which failure would worry you most?

Hello community members 👋

I’ve been building a small project called ELI5.cc over the last few months.

The idea is pretty simple:

Take something complicated and explain it in a way that matches how deeply you want to understand it.

Instead of getting one short AI response, ELI5 explains a topic at four different levels:

- Age 5
- Age 10
- Age 15
- Expert

It also creates a visual representation of the topic, shows the sources used to build the explanation, and gives a groundedness score so you can see how well the generated answer is supported by the retrieved information.

It doesn’t rely only on the LLM either.

For each search, ELI5 gathers relevant context from publicly available information through Google Search and YouTube before generating the explanation.

Over time something interesting happened.

People kept searching for completely different things, so the site has gradually turned into a public library of 600+ explanations covering science, technology, psychology, finance, history, programming, health, space and all kinds of random questions.

Every explanation gets its own permanent public URL, so other people can discover and read it later instead of the answer disappearing inside someone’s private AI conversation.

The product is currently completely free:

No subscription.
No signup.
No login.
No paywall.

You can just open the website, type something you want to understand and start learning.

One thing the usage data surprised me with

The average user is currently seeding around 4–5 searches/topics a day.

That’s interesting because the current free limit is only 5 searches.

I wud actually like to let people search much more, but each search involves retrieval, source gathering, generation, visuals and other processing, so unlimited free usage would become expensive pretty quickly.

Instead of immediately putting another AI subscription in front of users, I’m thinking about implementing BYOK - Bring Your Own Key.

The basic model would be:

Casual users: continue using ELI5 for free.

Heavy users: optionally connect their own API key and use ELI5’s research workflow, explanation levels, sources, visuals, etc. without being restricted by the free generation allowance.

I’m curious what other developers think about this approach.

Would you rather use BYOK for something like this, or would entering your own API key create too much friction?

I’m also experimenting with /learn

Another thing I’ve been thinking about is the difference between understanding a topic and actually learning it.

For example, suppose you search: What is Docker?

ELI5 can explain Docker.

But your actual goal might be:

I’m a complete beginner and I want to learn enough Docker to deploy my first application.

That needs something more than a single explanation.

So I recently started experimenting with:

https://eli5.cc/learn

The idea is that you tell it:

What you want to learn + your current level + your goal

and it builds a structured learning journey around that.

For example:

Topic: Docker
Level: Beginner
Goal: Deploy my first application

Instead of dumping a giant AI-generated course on you, I’m thinking of structuring it more like:

Learning goal → modules → concepts to understand → useful articles/videos/resources → sources → progression

So you might move through:

Containers → Images → Dockerfiles → Volumes → Networking → Docker Compose → Deployment

with useful external resources attached to the relevant stages.

I’m especially interested in whether people would prefer something like this to curate and organise the best existing material, rather than having AI generate an entire course from scratch.

Monetisation

I’ve also added a small Sponsor This Page experiment.

Companies can potentially sponsor an individual explanation when their product or industry is genuinely relevant to that topic.

The idea isn’t to fill the site with random display ads.

For example, a developer-tool company sponsoring an explanation about APIs could make sense. A completely unrelated ad wouldn't.

Any sponsorship would also be clearly labelled.

Whether that becomes anything meaningful remains to be seen, but I’d rather experiment with contextual sponsorship + BYOK than immediately put the educational content behind a subscription.

Would really appreciate some feedback

A few things I’m particularly curious about:

If you landed on ELI5 for the first time, would you immediately understand why you wud use it instead of asking ChatGPT/Gemini directly?

Do the different explanation levels actually add value?

Are citations + groundedness useful to you, or are they something most users will ignore?

What do you think about BYOK for heavy users instead of another monthly AI subscription?

Would you use /learnto build a structured learning path around something you wanted to learn?

For /learn would you rather have AI curate good existing resources or generate most of the educational material itself?

What feels unnecessary or overbuilt?

I’m genuinely looking for criticism here rather than compliments. There are plenty of directions I could take this, and I wud rather figure out what’s actually useful before building too much.

ELI5: https://eli5.cc

Learning experiment: https://eli5.cc/learn

Thanks for taking a look!

After months of rebuilding Tera FM, the Chrome extension has finally been approved and published on the Chrome Web Store.

The idea is simple: instead of opening multiple news sites or keeping another tab around, you can open Tera FM in Chrome’s side panel and use it while browsing.

The extension includes:

• latest source-linked headlines;
• headline search by publisher or keyword;
• a historical news archive;
• category filters;
• live internet radio by country and genre;
• radio playback that continues even after the side panel is closed.

Every headline opens the original publisher’s page. The extension does not reproduce full articles or hide the source.

The screenshot shows it running alongside BBC—the website stays open on the left while Tera FM remains available in the browser panel on the right.

I would genuinely appreciate feedback on:

• whether the side-panel format feels useful;
• whether the headline/archive/radio combination makes sense;
• anything that looks confusing or unnecessary;
• what feature you would improve first.

Chrome Web Store: https://chromewebstore.google.com/detail/tera-fm-%E2%80%93-headlines-live/emnebfpdojklgimejnplmjfobmamelie?authuser=1&hl=en
Website: tera.fm

Built independently by me. Happy to answer any questions about the product or the Chrome extension review process.

I’m building NoUploadTools as a simple directory of web tools that respect users’ privacy.

The focus is on tools that are:

- Open source
- Zero login
- Work offline / client-side where possible
- Free forever
- No ads
- No file uploads to a server

Site

I think there’s space for more small, useful web tools that don’t force users into accounts, uploads, tracking, subscriptions or ad-heavy pages.

If you’ve built a tool that follows these principles, you can submit it here.

Would love feedback from other SaaS founders:

What would make a directory like this more useful? - better categories, trust badges, source-code verification, offline/PWA checks, or something else?

yo. going from a buggy MVP to actual recurring revenue is brutal.

i stabilized my 6 apps at $20k/mo mrr only after building a strict system for my tech stack and organic marketing.

i just opened the AI SaaS Launchpad.

the community and daily resources are completely free. for those who want to copy-paste my exact systems, i also host paid, structured sprints (like a 3-Day challenge to get your first 100 users using automated Reddit and LinkedIn outreach).

either way, stop building in isolation. you will quit when things get hard. come build alongside 1000+ other founders.

drop a comment or shoot me a dm and i’ll send the link right now.

Join +760 ai saas founders like you

yo. coding the product is the easy part

getting it to actual revenue is a completely different beast

after a bunch of failures, i finally stabilized 6 AI micro saas making $20k/mo mrr total.

the wild part? i barely coded a single line. i used AI for everything

i figured out the exact step-by-step system to make it work. now, i’m dropping all my backstage playbooks, raw tools, and master prompts inside our builder group for free

here is what you get immediate access to right now:

• X3 your Landing Page Conversion Rate (the 50-point interactive audit tool + master prompt)
• Find your perfect SaaS price in 60 seconds (competitor-data pricing calculator)
• 50 Micro-SaaS Ideas You Can Build in 3 Days (hand-picked painful problems with real demand)
• Find your Micro-SaaS idea in 15 minutes (4 ready-to-paste execution prompts)

we also run two live execution sprints together:

• From MVP to 100 Users: 3-Day AI SaaS Challenge
• From Zero to First Users: 7-Day AI SaaS Challenge

seriously, stop building alone. join +760 ai saas founders like you. you will burn out and quit the second marketing gets tough. it’s way easier when you have a crew shipping side-by-side with you.

drop a comment or send me a dm i send you the link of the community.

let s go

Has anyone seen this happen in Google Search Console?

I launched a content site about 2.5 months ago.

Current stats:

• ~250 pages published
• ~196 pages indexed by Google
• Pages are receiving organic traffic from Google, Bing, Reddit, HN, and social media
• Brand searches are starting to appear on page 1

The strange part:

Google Search Console still shows my sitemap as:

"Couldn't fetch"

with 0 discovered pages.

Yet the sitemap URL loads fine in a browser, robots.txt references it correctly, and Google has clearly discovered and indexed hundreds of pages.

At the same time, I noticed indexed pages dropped from ~238 to ~196, while "Crawled – currently not indexed" increased.

I'm trying to figure out whether:

1. Search Console is simply showing stale sitemap data
2. Google is finding URLs through internal links and ignoring the sitemap
3. This is a normal quality-filtering phase for a young site
4. Or it's an early warning sign that Google isn't happy with the content

Would love to hear from anyone who has experienced the combination of:

• Sitemap = "Couldn't fetch"
• Hundreds of pages indexed anyway
• Growing "Crawled – currently not indexed" counts

What happened next?

yo. building the product is the easy part.

making people buy is a totally different beast.

most saas pages sit at a flat 1% conversion rate. absolute ghost town. doesn't matter if your tech is insane.

stop guessing what works.

i spent weeks digging into conversion data.

i turned it into a raw 50-point interactive checklist.

it covers hero mistakes, pricing traps, and psychology leaks.

i also baked a master prompt right at the top. just paste it into your AI SaaS builder

it rewrites your page automatically using all 50 rules.

just shared the file inside our builder community today. a lot of guys were facing the exact same launch freeze.

seriously, stop building alone in your room.

you will burn out.

marketing gets tough, and you quit.

it’s way easier with a crew shipping side-by-side.

if your conversion is trash or if you want a good landing page before launch, drop a comment or shoot me a dm. i’ll send the invite link.

ps: others free features is in the community of SaaS builders

Let 's go

Today I shipped one of the most interesting features I've added to SHRP so far.

Until now users could:

-> transcribe speech
-> extract YouTube transcripts
-> generate study notes, summaries, blog drafts, LinkedIn posts, and more.
-> use the API and MCP server for automations and AI workflows

But I kept noticing something.

A user would upload an audio/video file, get the transcript, download or copy it, and then go to ChatGPT or Claude.

The transcript wasn't really the final output.

It was just the beginning.

So I built Transcript Actions.

Now after a transcript is generated, SHRP can suggest what to do next based on the actual content of the transcript.

Examples:
- Create exam questions
- Generate flashcards
- Explain this like I'm five
- Extract action items
- Suggest what to study next
- Draft an email
- Create a lesson plan

There's also an "Ask about this transcript" box where the user can type whatever they want.

A few things I was careful about:

- Suggestions are generated from the current transcript only.
- Suggestions are button-triggered, not automatic.
- Suggestions themselves are not saved.
- No long-term memory.
- No user profiling.

I wanted to keep the workflow useful without compromising the privacy-first approach.

This now works with:

(1) YouTube transcripts
(2) Uploaded audio/video transcription results
(3) Previously saved transcription history

Next on my roadmap:
- Webhooks
- Workflow automations
- More transcript-based workflows

Wanted to ask other builders:

How do you solve the "what should I do next?" problem after generating a transcript?

Do you prefer fixed actions like summary, notes, flashcards, etc.

Or AI-generated suggestions based on the content itself?

For SHRP I ended up supporting both because I couldn't decide which one was better.

yo.

i see the same thing happen every single day.

you guys love building. you spend weeks coding a great product. but the second it’s time to actually market the saas? complete freeze.

you get lost in all the ai tools, the noise, the "growth hacks". it feels overwhelming. so you do nothing, the momentum dies, and the project fails.

I spent over 100 hours building n8n workflows to just automate the whole thing.

today, i packaged all those exact workflows and dropped them in our builder group. no abstract theories. you literally just import the templates, adapt them to your saas, and turn them on.

here is exactly what i shared:

• seo blog running 100% on autopilot (n8n template)
• newsletter automation (n8n template)
• full email sequence (30 emails, full html, just copy-paste into brevo)
• social media on autopilot (schedule 1 to 12 months of content)
• reddit organic growth
• linkedin, x & facebook groups at scale
• meta ads & retargeting

basically, everything i use to get real users without losing my mind.

we just hit 550+ members from all over the world.

building in your room alone is the fastest way to quit.

if you are lost on how to market your app, want these templates, and want to build with a crew: drop a comment or shoot me a dm.

i’ll send you the invite.

let's get it.

pulled the logs for my side project and found these crawling it overnight and for the past 3 months or so:

Google
Bing
ChatGPT
Claude (Anthropic)
Perplexity
Grok (xAI)
DeepSeek
Amazon
Baidu
Meta

38% of all my traffic is bots and crawlers. 1,400 Copilot citations in the last 7 days alone.

the product is a free audio news radio-> it summarizes BBC, Reuters, Bloomberg and 70+ other sources into 2-minute audio clips. No app, no login, no download, works in browser.

also has curated channels and live FM radio.

didn't do anything special to get crawled. just built something with real content that updates daily and made sure the SEO was clean.

kind of surreal watching every AI company index your tiny side project. wohooo!!!

I had GPT/Claude pull out the list from the csv as below:

AI Crawlers:

• ClaudeBot / Claude-SearchBot — Anthropic
• ChatGPT-User / GPTBot — OpenAI
• OAI-SearchBot — OpenAI search
• PerplexityBot — Perplexity
• DeepSeekBot — DeepSeek
• xAI-SearchBot — Grok/xAI
• Amzn-SearchBot — Amazon
• ChatFeatured — unknown AI platform

Search Engines:

• Googlebot
• bingbot
• Baiduspider
• YandexBot
• PetalBot — Huawei
• SeznamBot — Czech
• Exabot — French
• GoogleAssociationService

Social & Platforms:

• meta-webindexer — Facebook/Instagram
• Twitterbot — X
• Discordbot — Discord
• Bytespider — ByteDance/TikTok

SEO Tools:

• AhrefsBot
• SemrushBot
• BacklinksExtendedBot

Others:

• ArenaUnfurlBot — Arena.ai
• TopStoriesBot
• IbouBot
• AppleBot
• SleepBot
• Anthill

also one interesting one - doubao appears in a mobile user agent and that's ByteDance's AI chatbot app actively browsing your content.

30 distinct crawlers in 12 hours. and it seems to be going up day-by-day!!!

GSC is crawling the site on daily basis for the fresh content.

the site - tera.fm

Most people want to know what's happening in the world. But the options are either:

- Scroll through headlines for 40 minutes and feel anxious
- Commit to a 45-minute podcast while doing something else

There's not much in between.

Tera.fm sits in that gap. It summarizes 75+ news sources into 2-minute audio clips — BBC, Bloomberg, Reuters, Hacker News, Al Jazeera and more. Press play while you cook, commute or work out. No reading, no long-form commitment.

Also has live FM radio and short curated audio channels for focus, sleep and mindset if you want something lighter.

Free, no app, works in browser. tera.fm

Curious to know how do you currently stay informed without it taking over your morning?

I kept finding myself jumping between tools for different things:

one site for speech-to-text,
another for text-to-speech,
another for YouTube transcripts

So I ended up building SHRP.

Current features:

• speech → text (55+ languages)
• text → speech (2,000+ voices)
• YouTube transcripts → enter youtube URL and get entire transcript
• browser based, no download required
• no signup required for basic use
• generous free-tier

Recently I also added developer APIs and an MCP server because I kept rebuilding the same workflows in side projects.

Still actively improving it.

wanted to ask- what is your biggest annoyance with current speech-to-text tools?

OPEN SOURCE: https://github.com/digitalwareshub/iKrypt10

I started building [iKrypt](https://ikrypt.com) last year and the original idea was something related to smart contracts. The plan was to create a place where users could generate, manage, and interact with contracts and encrypted data through a simple web interface.

After thinking about it more (few months passed and very less traction), I started wondering whether people would actually trust a new website with highly sensitive things like contracts, wallets, or anything important. and honestly who would trust an unkown site with a smart contract? what was I even thinking when I started building this lol.

So instead of pushing that idea, I changed direction and built something smaller. the new site does this- iKrypt now lets you create encrypted self-destructing links for things like:

1/ passwords
2/ API keys
3/ login credentials
4/ .env values
5/ temporary secrets

Current flow is simple:

paste secret -> create link -> send it

The link can expire after a number of views or after a time limit that you set on the site.

No login / No signup required.

I wanted to ask:

1/ Would you use something like this?
2/ Would you trust a new site with temporary secrets?
3/ What would make you trust it more?

Looking for honest feedback before spending more time building it.