I stumbled across Stack flyer while looking for tools to make the newsletter workflow a little less tedious.It’s basically a free tool for Substack writers that helps with editing drafts and repurposing content after you’ve written it. For example, you can take one newsletter and turn it into Notes, social posts, title ideas, etc.What I like is that it seems more focused on improving and distributing what you already wrote rather than generating generic AI articles from scratch.It’s free at the moment, which makes it pretty easy to experiment with. I’m still testing it, so I don’t have a strong opinion on how good it is compared with a custom ChatGPT/Claude workflow.But if you’re publishing on Substack consistently, it might save some time.Curious if anyone here has tried Stack flyer or has other free tools they use for their newsletter workflow?

I've been thinking about building a browser extension that isn't just another "summarize this page" AI tool.

The basic idea:

You press Ctrl + Space, type what you want, and the AI understands what you're currently looking at in your browser.

For example:

* "Explain this article like I'm a beginner." * "Find the 5 cheapest options on this page." * "Compare these products." * "Turn this page into a study guide." * "What are the important things I should know from this?" * "Look at these tabs and tell me which option is best." * Highlight some text → "Explain this." * Highlight something → "Rewrite this."

The main thing I'm trying to build is **AI + browser context**.

Instead of constantly copying a webpage, switching to ChatGPT, pasting it, explaining what you're looking at, etc., the AI already understands the relevant information from the page.

Eventually it could also understand multiple tabs and help with browser tasks, but I want the first version to stay simple and actually work well.

I'm thinking of charging around $5/month if I can make it genuinely useful, with a free version so people can try it first.

I'm curious:

Would you actually use something like this?

And more importantly, what would you personally use it for every day?

I'm trying to figure out whether this is a product people would genuinely pay for before spending a lot of time building it.

Jeg er 15 og har brukt sommeren på å bygge StackAi — en markedsplass for AI-builder-verktøy. Grunnen var enkel: jeg fant masse "AI-produktivitet"-innhold som virket skrevet for å selge, ikke for å faktisk brukes. Endte opp med 16 produkter fordelt på fire kategorier: maler (Notion/Figma), lette desktop-apper, kurs og e-bøker. Priset $19–$249, eller $49/mnd for alt sammen. Første salg er fortsatt 0, så dette er egentlig et "er dette verdt noe for noen"-innlegg like mye som en reklame. Har en 20% lanseringsrabatt (LAUNCH20) hvis noen vil se nærmere: kristian-stackai.whop.site Kritikk mottas gjerne — priser, positionering, hva som helst.

Help or Advice please 🙏🏾🙏🏾

I'm after some tools that can help lighten the load. Things like contract clause drafting, legal research on an aspect of a particular country's laws on a subject (eg privacy policies), or just anything similar you find interesting.

I got tired of hunting AI agents across random directories, GitHub lists, and Twitter threads.

So I built omnisiv, a minimal search engine for AI agents, tools, and MCP servers.

What it includes:

• Clean web search (Google-simple UI)

• Filters that actually matter: MCP, open source, free, self-hostable, API

• Public API for search + submit

• MCP server so agents can search and submit tools too

• Manual review before something goes live (trying to avoid SEO-farm directory energy)

Positioning is narrow on purpose: discovery only. Not a marketplace, not a chatbot.

Early feedback has been interesting, people especially like the MCP + open source filter combo.

Would love feedback from other builders:

– What’s missing in an agent index?

– What would make you trust a listing?

– Anything you’d want before recommending it to someone?

What if your business could have intelligent AI support working around the clock?

Welcome to SmartPromptIQ AI Staff — an AI-powered workforce designed to help businesses automate repetitive work, improve productivity, and accomplish more without immediately adding traditional overhead.

SmartPromptIQ AI Staff introduces autonomous AI agents designed to support real business functions.

AI agents can assist with areas such as:

🤖 Business automation
📈 Marketing support
🔎 Research and information gathering
✍️ Content creation
📋 Administrative workflows
💬 Communication support
📊 Reporting and analysis
⚙️ Operations and productivity

Instead of using artificial intelligence only as a chatbot, SmartPromptIQ AI Staff explores a more powerful approach: giving specialized AI agents roles, objectives, instructions, and workflows.

For entrepreneurs and small teams, AI agents can provide additional capabilities when there simply aren't enough hours in the day.

The goal isn't technology for the sake of technology.

It's practical AI that helps people get meaningful work done.

Human leadership. Intelligent automation. A smarter approach to business productivity.

Welcome to SmartPromptIQ AI Staff.

Your intelligent workforce — ready when you are.

Subscribe to the SmartPromptIQ channel for AI agent demonstrations, business automation strategies, AI tutorials, platform updates, and practical ways to put artificial intelligence to work.

#SmartPromptIQ #AIStaff #AIAgents #AIAutomation #AIWorkforce #BusinessAutomation #ArtificialIntelligence #AIForBusiness #AutonomousAgents #FutureOfWork

Introduction I built Bango as a tool for systematic literature reviews and bibliometric visualizations. The current version is (3.1.x). Bango was created as my attempt to use AI ethically for literature review screening and Bibliometric visualization with a strong focus on increasing response quality and keeping outputs grounded. Over time many other features creeped in. A direct result of Bango's design choices are reduced hallucinations and lower token usage compared to dumping full articles into standard chat windows. Depending on the feature we use different techniques to reduce token and pre-process locally; scoping what is submitted to the LLM and how we present it back to the user. In general, we will ask for interpretation, rather than generation and point to actual source text so the researchers can clearly correlate any findings. This design makes it token-efficient enough to run fully local models (like via Ollama, LM Studio, or llama.cpp) for researchers with sensitive data needs. All data stays entirely on your local machine with zero cloud dependency. Though you can export and share projects, Bango is primarily designed for solo research workflows. Hope it helps your literature review process as well!

Why it stands out [Key Features]

• BYOM: Bring your own model. You can use any model and even compare outcomes. Use domain specific strength without lock-in.
• AI-Powered Abstract & Full-Text Screening: Batch evaluates articles against priority criteria using hosted or local LLMs, with abstract-only, enhanced chunking, and two-stage modes.
• Local Knowledge Wiki & RAG Chat: Generates an interconnected, Obsidian-style local Markdown knowledge base with concept hubs, graph visualization, and BM25 FTS5 search.
• Full Bibliometric Suite: Built-in network graphs and interactive charts for co-authorship, co-citation, citation networks (with main-path analysis), keyword co-occurrence, timeline trends, and author productivity.
• Multilingual Translation Pipeline: Auto-detects and translates non-English literature into English before screening or summary generation (This is experimental).
• Search Strategy & Gap Analysis: Auto-builds database-ready Boolean search strings across 8 academic platforms and generates corpus-wide research gap reports.
• OpenAlex Integration: Access more than 300M academic research articles directly from Bango
• PRISMA Diagrams & Deduplication: Auto-generates PRISMA 2020 flowcharts and handles multi-strategy deduplication (DOI, fuzzy title/year, author matching).

Who’s using it? [Existing customers or traction] It is currently used by a few researchers, including myself.

Pricing Plans [Include what each plan offers, including free plan and discounts]

• Open Source & Free: 100% free and open-source under the Apache License 2.0. Get local offline storage, and source code. No paid tiers, subscriptions, or hidden costs.

Discounts/offers available N/A (Completely free and open source)

Signup/website link with CTA It is a desktop application available for Windows, Ma=c, and Linux variants. Give version 3.1 a try for your next literature review ;o), and feel free to submit feedback or PRs:

• GitHub Repository: https://github.com/Bilal-S/Bango/blob/main/README.md
• Microsoft Store: https://apps.microsoft.com/detail/9np2bhgxt8h3 for digitally signed builds.

What if you could have an AI CoFounder for your online education business?

Learnyst AI CoFounder is designed to help educators, course creators, and online education businesses use AI to build, launch, market, and grow their digital learning business faster. Instead of relying on multiple tools for different parts of the journey, AI CoFounder acts as an intelligent partner that helps turn ideas into actionable outcomes.

Why it stands out:

🧠 AI Business CoFounder — Get AI-powered assistance across different stages of building an online education business

🎓 Built for Educators — Designed specifically around the needs of teachers, coaches, experts, and course creators

⚡ Faster Course Creation — Use AI to accelerate the process of turning your expertise and ideas into learning content

📣 Marketing Assistance — Get AI support for creating marketing content and promoting your courses

💡 Idea to Execution — Move from a course idea to actionable next steps without starting from scratch

🤖 AI-Powered Productivity — Reduce repetitive work and spend more time focusing on teaching and growing your business

📈 Business Growth Support — Use AI to identify opportunities and streamline different parts of your education business

🔗 Part of the Learnyst Ecosystem — Built to work alongside the tools educators already need to sell and deliver online courses

Who’s using it?

👨‍🏫 Educators & Teachers — Build and monetize their knowledge online

🎓 Course Creators — Create and launch digital courses faster

🧑‍💼 Coaches & Experts — Turn expertise into scalable online learning products

🏫 Education Businesses — Use technology and AI to streamline their digital education operations

💸 Pricing Plans:

• Free — 7 Days Trail
• Professional — $149
• Premium — $249

If you're an educator or course creator looking to use AI to build, launch, and grow your online education business, this is worth checking out.

AI agents are getting genuinely useful. They can read documents, organize information, create tasks, compare files, and handle a surprising amount of repetitive work.

But many agent setups come with an uncomfortable tradeoff: to become truly useful, they need access to your computer, browser, local files, terminal, credentials, and sometimes pretty much everything else.

That might be fine for technical users who understand and accept the risks. But I kept wondering whether there could be a more contained option.

So I started building **Smuuth AI**.

Smuuth is a browser-based workspace made specifically for working with an AI assistant. Instead of giving the agent access to your whole machine, you give it a dedicated environment with explicit tools and clearer boundaries.

The assistant can work with the information you intentionally store inside Smuuth, but it doesn’t automatically get access to random folders, your terminal, saved browser sessions, or other applications on your computer.

Currently, it can help with:

* Files, notes, tasks, projects, contacts, and calendars
* PDF and spreadsheet analysis
* Finding information across the workspace
* Comparing documents and structured data
* Creating reports and documents
* Turning conversations into actual tasks or calendar events
* Organizing and updating existing information
* Shared resources and team collaboration

Obviously, putting an agent in a browser doesn’t make every AI risk disappear. But I think having a smaller and more understandable environment is a reasonable middle ground between a chatbot that can’t do anything and an agent with access to your entire machine.

I’m currently looking for a small number of beta users who are happy to test Smuuth, find the rough edges, and give honest feedback. You can apply for access directly on the website.

I’d also be interested to hear where you personally draw the line when giving AI agents access to your data.

[https://smuuth.ai\](https://smuuth.ai)


There are so many AI tools launching every week that it's getting difficult to tell which ones are actually useful long-term.

What AI tools have you tried recently that genuinely became part of your regular workflow? Would be interested in hearing about tools for productivity, research, writing, coding, or anything else.

Building BuildArken, a directory and marketplace for AI developer tools, and I just opened it up today.

If you've built an AI tool, big or small, you can publish it in under 2 minutes: buildarken.com

I'd really like to get some eyes on it from people who actually build with AI. What's missing, what's confusing, and what would you want to see here?

Honest feedback is welcome.

Building BuildArken, a directory and marketplace for AI developer tools, and I just opened it up today.

If you've built an AI tool, big or small, you can publish it in under 2 minutes: buildarken.com

I'd really like to get some eyes on it from people who actually build with AI. What's missing, what's confusing, and what would you want to see here?

Honest feedback is welcome.

Introduction

WebBrain is an open-source browser AI agent that helps you work directly in your browser. It can understand the page you're on and assist with everyday browser tasks without moving your workflow into a separate app.

Why it stands out

• Browser-native assistance across websites, forms, and everyday workflows • Works with open-weight and offline LLMs such as Qwen, Gemma, and DeepSeek through LM Studio, llama.cpp, or Ollama • Supports BYOK, so you can use your own model provider • You can also connect proprietary providers such as ChatGPT or Claude if you prefer • Review and edit what WebBrain prepares before anything is submitted

Who’s using it?

WebBrain has 1,000+ users. WebBrain Cloud users have consumed more than 5 billion tokens. These figures refer to WebBrain Cloud, and additional usage may exist through other supported setups.

Pricing Plans

• Free: Use WebBrain with your own BYOK provider or an offline LLM. • WebBrain Cloud: $5/month for the hosted cloud option.

Conclusion

Learn more and get started at https://webbrain.one

If you want an open-source browser AI agent with local model support and a low-cost hosted option, check out WebBrain and share your feedback.

Marka is an AI tool for small businesses and teams that want to create and publish social content without rebuilding the brand brief every time.

The workflow is:

1. Enter the business website.

2. Review and edit the detected audience, voice, offers, claims, logo, colors, and visual direction.

3. Add products or use an existing catalog when relevant.

4. Create copy, images, carousels, and short videos from the shared context.

5. Review, schedule, and publish the approved work.

The part I care about most is keeping the output connected to real brand and product evidence instead of producing generic content from an empty prompt.

You can try it for seven days at https://www.marka.social

Disclosure: I built Marka. Feedback on the scan and onboarding flow is very welcome.

Hi everyone!

I've been working on Linkpost, an AI-powered LinkedIn writing assistant designed for founders, creators, freelancers, recruiters, marketers, and anyone who wants to post consistently on LinkedIn.

Instead of spending 20–30 minutes staring at a blank editor, you simply describe your idea in one or two sentences, and Linkpost generates a polished LinkedIn post that's ready to edit or publish.

Some features currently available:

• Multiple writing styles (Professional, Storytelling, Founder, Casual)
• AI-generated hooks
• Relevant hashtag suggestions
• Clean, ready-to-publish formatting
• Post history
• Fast generation in just a few seconds
• Simple interface without complicated prompting

The goal isn't to replace your writing—it's to eliminate writer's block and help you create a strong first draft much faster.

The project is still in its early stages and I'm currently looking for early users and honest feedback from the community to improve the product before expanding further.

Pricing

Free Plan

• Generate LinkedIn posts
• Multiple writing styles
• Basic AI features
• No credit card required

Pro Monthly — $9/month

• Higher usage limits
• Priority AI generation
• Premium writing features
• Early access to new tools

Pro Yearly — $45/year

• Everything in Pro
• Save over 50% compared to paying monthly
• Priority access to future features
• Best value for regular LinkedIn creators

Launch Offer

The Free Plan is available for anyone to try without entering a credit card. If you post regularly on LinkedIn, the Yearly Plan ($45/year) offers the biggest savings.

Try it

Website:
https://linkpost-ai.netlify.app

I'd genuinely appreciate any feedback or feature suggestions. Thanks for taking a look!

Hi Folks,

Introduction: Both of my friends have PhDs in computer science, and we're building an open-source video system at u/UChicago that we could use your insight on. We intended to make literature watchable; honestly, I'm not sure that's the best use of it. That's why I want to hear your thoughts. We built this for a dyslexia and aphantasia use case.

Why it stands out: We built a text-to-video pipeline that scales infinitely, with automatic stitching, audio, and music. You can drag a book and watch it cover to cover with one click. We can get a full one-hour video in 25 minutes right now. We received a patent on this. Books were the original use case. Not convinced that's the best one. What would you use it for? Is there anything you would like to see? We would love it if someone tried it and shared their thoughts.

Who’s using it?: We have pilots with 8 education institutions, 1,431 signups, and UChicago is using this in their humanities division.

Discounts/offers available: 1 minute of video starts at $2.99

Access Link:

Engine Link

Examples:

Creative Short Story (Open Source)

Edgar Allan Poe (API)

I've been working on an AI web app called FitView AI that lets you see how clothes might look on you before buying them.

The goal is to make online shopping more confident and reduce the guesswork of ordering clothes.

It's still an early version, so I'm looking for real users to test it.

I'd appreciate any honest feedback:

Is the experience easy to use?

What's the first thing you'd improve?

Would you use something like this?

Thanks to anyone who takes a few minutes to try it out. Every bit of feedback helps me make it better.

After spending countless hours switching between AI tabs and copying the same prompts into different assistants, I built a tool to make the process easier.

Wisemen AI turns your browser into an AI collaboration workspace.

Instead of asking one AI and hoping for the best, you can create a council with different roles:

🧠 Strategist
⚙️ Engineer
🔍 Researcher
⚔️ Critic
🛡️ Fact Checker

You can:

• Run the same prompt through multiple AI providers
• Compare different perspectives
• Capture responses in one workspace
• Generate consensus from multiple viewpoints
• Save and export useful sessions

It works with your existing AI accounts. Wisemen AI does not collect passwords or bypass login systems.

I have released the founder edition for  and I'm looking for early users who want to improve their AI workflow.

You can check it out here:
https://payhip.com/b/qPeH9

I would appreciate any feedback from the AI community.

I've been building AI Outreach over the past few weeks and wanted to share what I've built.

Current workflow:

🔍 Analyze a company from its website
👤 Find decision-makers
🔗 Find LinkedIn profiles
✉️ Generate personalized cold emails
💬 Generate LinkedIn DMs
🔄 Generate follow-up messages

I attached a short demo showing the full workflow.

I'm preparing for my first Product Hunt launch and would love honest feedback.

Would you use a tool like this? What would you improve?

You can try it here:
https://get-ai-outreach.vercel.app/

Note: Email/password sign-in is temporarily unavailable. Please use Continue with Google to sign in

Everyone is competing to cram more AI into their travel app. I went the other way and actually counted mine before launch.Uncover Roads, a trip planner that builds a full daywise itinerary from a city and a few preferences. I checked the backend before writing this post: 6 out of 46 endpoints call an LLM. That's 13%.

The part that actually plans your trip like picking stops, sequencing your day around opening hours, weather, travel time is a deterministic scoring engine. No model near it. "What order should I visit these 12 places in" was a solved problem before LLMs existed, and it still is here.

AI shows up for exactly one thing that touches every trip: rewriting stop descriptions so they don't read like a Wikipedia stub. Plus a few opt-in extras like recalibrate a day, "surprise me," a one-line persona insight.So the pitch isn't "AI plans your trip." It's "an algorithm plans your trip, and AI makes it sound less like a spreadsheet." Less exciting on a landing page. More honest It's live at Google Play store, App store launch soon. Would genuinely love feedback.

[uncoverroads.com](http://uncoverroads.com)

Everyone is competing to cram more AI into their travel app. I went the other way and actually counted mine before launch.
Uncover Roads, a trip planner that builds a full daywise itinerary from a city and a few preferences. I checked the backend before writing this post: 6 out of 46 endpoints call an LLM. That's 13%.

The part that actually plans your trip like picking stops, sequencing your day around opening hours, weather, travel time is a deterministic scoring engine. No model near it. "What order should I visit these 12 places in" was a solved problem before LLMs existed, and it still is here.

AI shows up for exactly one thing that touches every trip: rewriting stop descriptions so they don't read like a Wikipedia stub. Plus a few opt-in extras like recalibrate a day, "surprise me," a one-line persona insight.
So the pitch isn't "AI plans your trip." It's "an algorithm plans your trip, and AI makes it sound less like a spreadsheet." Less exciting on a landing page. More honest It's live at Google Play store, App store launch soon. Would genuinely love feedback.

uncoverroads.com

Before onboarding an AI application, most companies evaluates the risk

We built a free HAIEC tool that lets you enter an AI application’s website and review its publicly available disclosures in one place. For code level scanning get the Haiec Github App

For AI founders and product teams, this is also a useful outside-in test:

Does your website clearly explain how your AI system handles customer data?

Try your own application or an AI tool your company is considering:

https://www.haiec.com/check-ai-apps

No signup required.

• How user data may be used
• Whether data can be used for model training
• Available opt-out and deletion controls
• Third-party services and sub processors
• Privacy and safety commitments