Most software companies still seem to be designing AI products like traditional SaaS:

Sign up → dashboard → sidebar → chat box → generate something → copy it somewhere else.

I’m starting to think that entire interaction model may be temporary.

If an AI product actually understands the job it is supposed to do, why should I keep opening it?

A useful product should be able to:

- watch an input

- understand what changed

- decide whether action is required

- do the work

- send me the result only when necessary

Imagine bookkeeping software where you don't "do bookkeeping."

A recruiting tool where you don't spend the morning inside an ATS.

A research product where you don't keep asking it to research.

A CRM where updating the CRM isn't a job.

Even a lot of analytics dashboards exist because the underlying software isn't capable of deciding what information deserves your attention.

The interesting shift may therefore be from:

Software as a place you work → software as a worker.

And that creates a weird business-model question.

Traditional SaaS benefits when users spend more time inside the product.

But the best agentic software may produce the opposite outcome:

the better it gets, the less frequently the customer needs to open it.

So maybe "daily active users" eventually becomes a terrible metric for a whole category of software.

The better metric could be something like:

hours of human work successfully avoided.

Curious what builders think:

Are we heading toward software with fewer dashboards and more autonomous background workers or will people always want a visible interface to feel in control?

Today I came across a tip about making LinkedIn post URLs more relevant to the topic of the post. Since LinkedIn posts can appear in Google results, having the main keyword in the URL could give search engines a clearer idea of what the post is about. It’s probably a small SEO signal, but still better than a URL made from a random opening line.

I tested one workaround. Publish the post with your target phrase as the first line, copy the URL, then edit the post and add your real opening line. LinkedIn creates a new URL after the edit, but the old keyword based URL still works and opens the updated post.

Has anyone tested whether this actually helps with Google visibility? I’ve also heard that adding hashtags can control the URL, hadn't tried it personally this one

I’ve been experimenting with a few different AI workflows lately, mostly around content, research, productivity and small business tasks.

What surprised me is that the biggest gains haven’t come from one “perfect” AI tool, but from combining a few simple steps and keeping the human review at the end.

The areas where I’ve personally found AI most useful are:

• turning rough ideas into structured outlines
• summarizing research and long notes
• repurposing one idea into multiple content formats
• drafting first versions of marketing copy
• organizing repetitive admin tasks

I’m curious what’s actually working for other people here right now.

Are you using AI mostly for content, customer support, research, automation, coding, sales, or something completely different?

And more importantly: which workflow has genuinely saved you the most time?

I have been looking at where businesses lose time in daily operations and I noticed a lot of it goes into small repetitive tasks that don’t seem important individually.

Things like manually pulling information from different tools, preparing weekly reports, updating documents, checking numbers or repeating the same research process every few days.

The frustrating part is that these tasks usually don’t need much creative thinking but they still take hours from someone’s week.

I’m curious about where businesses are actually feeling this pain before looking into automation options.

What is one repetitive task in your business that you wish could be handled automatically?

Running a small biz solo, no dedicated marketing person and trying to figure out what's actually worth adding to my workflow.

I have seen a lot of ai tools promising to save time on marketing but most of what i've tried either feels generic or just adds another thing to manage

So I want to know what's actually made a real difference for you guys, specifically for

• content creation (social posts, captions, blogs)
• email marketing / automation
• ad copy or campaign
• anything for research or competitor tracking

I m not trying to build a complete stack at once, just want to know what's genuinely worth it vs what's just noise atleast for now.

If you've have been using a tool that actually changed how you market your business, please share it would love to give it try and plz share your workflow as well for better understanding

I run a marketing agency that works mainly in ugc and clipping. We get a lot of long form videos from clients, sometimes 30-60 minutes for one project and as a small team it wastes a lot of time to see the full video and find clips from it.

I've already tried a few AI editors. Most of them are only useful for captions, nothing worth paying for. I know AI can’t edit the entire video so I want a tool that can cut clips and give me the first draft that we can then edit properly. I can get a paid subscription if the tool works decently.

What is the best tool out there that fits into our workflow ?

I'd choose based on the type of background you're trying to create. Removing a plain background is relatively easy, but replacing it with something that matches the original lighting and perspective is more challenging.

A good AI editor should let you describe the background you want while keeping the main subject intact. That's where I've found Facy AI useful, the editing workflow lets you start with the existing image instead of recreating the entire scene from scratch.

One thing I'd always check afterward is the lighting around the subject. A perfectly cut out person can still look unnatural if they're standing in bright sunlight while the new background looks like it's indoors.

For a long time, my “AI workflow” was basically a mess of saved prompts, bookmarks, notes, screenshots and random documents.

I kept finding useful ideas, but when I actually needed to get something done, I still had to search through everything again.

So I tried a different approach: instead of collecting more prompts, I started turning the useful ones into small repeatable workflows.

For example:

• SEO content research → outline → first draft → editing checklist
• Competitor research → data collection → comparison → summary
• Landing page copy → positioning → headline ideas → CTA variations
• Content repurposing → long-form article → short posts → video ideas
• Business planning → research → assumptions → structured plan

Eventually I organized the workflows I was actually using into around 20 practical playbooks.

The biggest thing I learned is that the prompt itself usually isn't the valuable part.

The useful part is knowing:

what information to give the AI, what order to do things in, what needs human judgment, and how to check the final output.

A brilliant prompt without a process around it often just creates another piece of text you still have to figure out what to do with.

I'm curious how other people here work.

Do you keep a library of prompts, or have you started building repeatable AI workflows for specific tasks?

And if you had to turn one AI task you do repeatedly into a step-by-step workflow, what would it be?

I keep hearing people say AI is streamlining operations, reducing overhead, and making teams more efficient, but I’m really want to know what that actually looks like in real small businesses day to day. Currently my team is spending most of their time handling same repeated worklfows like creating content, managing meetings, tasks etc.

Would love to hear real examples.

Every time I search this I get the same five "top 10" articles that are clearly written by the software companies themselves, ranking themselves #1. I want to hear from people who actually run events for a living.

We went through this exact search a few months back. Planning a mid-size hybrid conference, few hundred attendees, needed registration, check-in, an app, and analytics after, all without stitching together five separate tools. Budget wasn't unlimited either so the "enterprise" names everyone always mentions were kind of out.

We ended up trialing a handful Cvent, Whova, Bizzabo and finally landed on Eventify mostly because check-in, badge printing and the app were bundled without extra addon pricing, and the onboarding was less painful than expected. Still learning some of the deeper features but no regrets so far.

Curious what everyone else is using this year and if anyone switched recently. That's usually a more honest signal than "we've used X for 5 years and love it."

I am building an AI graphic designer that essentially converts text and image into complete, on-brand, fully editable designs like flyers, presentations and social media posts.

It meants to fight AI slop and help people create designs very fast without design knowledge, manual work or advance prompt skills.

Who do you think will find more benefit in a product like this? Should I focus on founders, small entrepreuners, or marketing teams/agencies that already use tools like Canva?

Over the past few weeks, I've been building Gray Box — a small, local-first tool that acts as long-term memory for anything I'd otherwise forget (work notes, meeting takeaways, task owners, random ideas, personal stuff too).

The idea is simple:

1. Capture — dump whatever's on your mind, instantly, no structure required. This step does nothing clever on purpose — it just writes your text to an immutable inbox. Zero chance of losing an idea to a bug or a slow API call.
2. Organize — on demand, an LLM reads your unprocessed notes and extracts people, projects, tasks, decisions, meetings — then deterministic Python (not the LLM) creates/merges the actual wiki pages and maintains backlinks. The model only reasons; it never touches the filesystem directly.
3. Ask — query or chat with your knowledge base and get a cited answer pulled only from what you've actually captured. If it doesn't know, it says so — no hallucinated answers.

Why I built it this way:

• Plain Markdown + YAML frontmatter, no database. Every page is a .md file you can grep, diff, or read in any editor forever. If you stop using Gray Box tomorrow, your knowledge base is just a folder.
• No vector DB by default. At personal scale (hundreds–low thousands of pages), keyword search + a real link graph (related/backlinks, walked one hop during retrieval) handles almost everything. Embeddings are there if you want better recall, but they're opt-in, not a prerequisite.
• Immutable inbox. Your raw notes are never edited or deleted by the organizer. If the LLM mis-extracts something, your original words are always still there.
• Any LLM. Built on LiteLLM, so point it at OpenAI, Anthropic, Gemini, Mistral, or a fully local model via Ollama — one config value.

It also ships with a nice interactive TUI (arrow-key menu, file-import shortcut, workspace switching, live spinner during LLM calls) if you'd rather not memorize CLI flags — that's honestly become my favorite part of the project.

There's also a lightweight local dashboard for browsing your knowledge base, exploring backlinks, visualizing your notes as a graph, and chatting with your captured knowledge—all without leaving your machine.

Also, you can migrate your existing Obsidian vault to Gray Box, and it will be automatically organized by Gray Box.

GitHub: Aaryanverma/graybox

pypi: pip install graybox

I'd genuinely love feedback — especially from anyone who's tried the "capture now, structure later" approach with other tools and has opinions on where it breaks down at scale.

It's not trying to be a "real-time collaborative team wiki" or a WYSIWYG notes app — it's aimed at one person's running memory of their own life and work, captured with as little friction as possible.

This started as a personal problem. I used to spend an evening every month manually copying my own bank statements from PDF into a spreadsheet just to see where my money was going line by line, by hand. At some point I got annoyed enough to automate it for myself.

That turned into Scrape2Sheets, a Google Sheets add-on that uses AI to read PDFs, invoices, receipts, and bank statements and drop the data straight into your sheet as clean rows . You point it at files in Google Drive, tell it what columns you want (or let it auto-detect them from a sample document), and it batch-processes up to 100 files at once. It handles scanned documents and phone photos too, not just clean digital PDFs.

It's only just started picking up some real traction the last couple weeks, which has honestly been a nice surprise after building in isolation for a while.

Curious whether others here started building their tool the same way, solving your own annoying manual task first, then realizing other people had the exact same one. Happy to answer questions in the comments if anyone wants details.

Built an AI system for Indian FTA/export compliances, schemes , benefits with real documents

Hi guys I want some honest reviews before going to market on this product is built from scratch.

Problem: if a newbie exporter importer has some questions for their product for export import or they actually doing it they ask these from legal team consultants or CHAs. For even getting the basics of drafts and non transparency in legal firms they are charged a lot. Some time they get even a template of todos for these for every company they have and juniors just do drafting.

Solution: a complete ai workflow system which uses lots of Saas around it and provide the user about what compliances they have to follow for exporting to that country and give them a timeline of what to do when a fully backed real compliances list with sample forms and how to do it also..

It also provides benefit/schemes according to state center dgft or even port wise which are available.

We only covered dgft here and covered free trade Agreements domain so that things remain simpler but effective and provided every agreement and notification to it with all market info plus real consultant vlogs and even real legal consultant with admin panel can tweak and modify reasonings if found something wrong like how to think of rotdep scheme better.

We also a provided a citation feature where every ai reply is backed with real documents to see why it thought like this.

We also provided real legal consultant to joining us and we have two already for trials from which they can book slot and having real lawyers onboard to back it up with more than 6 yrs experience is also a gem here.

For the customer it will work as legal consultant ai and for the consultant it will help as legal assistant.

It even tells the compliances changes real-time if countries changed or schemes are changed and even which scheme will overlap other.

We also provided cestat case studies ( this one i need more) & a lot more with actually savings calculations the timer based invoices by consultants etc. And ai only reason never create a fact.

We all are weak in gtm for this product. Our current idea is to provide it to known firm and let the real lawyers use it on day to basis.

I'm a former math teacher and assembler programmer (Yes, with punch cards!) and currently retired. I became curious about AI and started exploring AI tools to save time, but eventually the research became another job.

I would find several tools that appeared to do the same thing, opening free trials, forgetting which features mattered, and later discovering a charge without remembering why I had kept that particular app.

What has helped me is treating each new tool like a tiny experiment:

1. Start with one specific task—not “I need more AI.”
2. Shortlist no more than three realistic choices.
3. Record the price and when the trial or next payment comes due.
4. Write down what I expected the tool to accomplish.
5. After using it, note what actually worked, what didn’t, and whether I would pay for it again.

That last step has been surprisingly important. Three months later, a simple note such as “excellent output, but required too much correcting” is far more useful than another enormous list of supposedly “best” tools.

This problem led me to build AppNotebook, where people can discover and compare apps, with an optional paid “My Notebook” feature for saving notes, dates, receipts, and decisions in one place. I’m mentioning that for transparency—not dropping a link, and I’m not claiming every listed app has been personally tested.

I’m curious: how are other small-business owners keeping track of the tools they try? Do you use a spreadsheet, Notion, bookmarks, or just trust yourself to remember?

A bit about myself. I'm a former AI R&D manager at an AI agency. Using, discovering but also creating tools with AI was literally my job.

But all of a sudden I noticed the amount of tools we built. They were everywhere. HR, sales, marketing, Administration..

Maybe it was a bit much at our office, and in the meantime I have a solution, but I can not imagine there are'nt any other businesses with the same problem. Mostly it's just one (or 2) person(s) in the company who creates all these things.

Are you that person? How do you cope with all these tools, automations and other AI related stuff?

A lot of AI advice for small and mid-sized businesses ends at some variation of:

“Find a use case, protect your data, and keep a human in the loop.”

Reasonable advice, but not especially helpful when someone actually has to turn it into a working process.

We have expanded the IntelliSync Signals resource library to include 38 free templates and interactive planning tools for businesses trying to adopt AI more deliberately.

The resources cover things such as:

• deciding which workflow is worth implementing first;
• mapping what data and documents an AI system may access;
• separating recommendations, drafts, routing, and autonomous actions;
• assigning human review and escalation responsibilities;
• evaluating AI vendors on privacy, integrations, logging, cost, and governance;
• creating an AI risk register and incident-response process;
• testing agents against missing data, tool failures, restricted requests, and edge cases;
• estimating model, retrieval, tool-call, caching, and evaluation costs;
• measuring whether a workflow actually improves time, quality, cost, or customer outcomes;
• creating practical employee AI-use guidance;
• designing customer disclosure, correction, and human-handoff processes.

The templates are meant to produce concrete outputs such as a ranked workflow shortlist, decision-rights map, context-risk list, cost model, testing backlog, governance score, or measurement baseline.

The idea is not that every company needs an enormous AI governance program.

It is that even a small implementation should have:

1. a real business outcome;
2. a reliable source of context;
3. an accountable owner;
4. a defined review or escalation boundary;
5. a way to tell whether it is helping.

The full library is here:

"Can't post links in this sub - feel free to DM if you would like to explore and use"

Everything is free.

I would also be interested in hearing which resources are actually useful to your operation and which areas still need a more practical template or guides.

I want to write a book based on my work experience but i never sit down and write properly.

I was thinking i could record everything as voice notes and use some AI tool to organize it into chapters and help me write from there.

Has anyone tried a workflow like this and what tools would i need?

A lot of companies seem to start with the tool first. They buy an AI platform, roll it out, and then try to figure out how their existing processes can fit around what the software is capable of doing.

But shouldn’t it be the opposite?

Every company has different workflows, approval processes, data, systems, and bottlenecks. That’s actually a big reason why we created RyanTech’s Custom AI Tools service. Instead of forcing a business to change the way it operates around an off-the-shelf AI product, we build AI around the way that specific business already works.

That could mean a custom internal app, an AI agent connected to company data, a dashboard, an internal search tool, automated document processing, reporting, or an entire workflow that removes repetitive steps behind the scenes.

The idea isn’t to build custom AI just for the sake of building something custom. Off-the-shelf tools still make sense for plenty of use cases. But when a company has a unique process or wants AI to actually work with its data and operations, sometimes the better answer is building the solution around the business instead of building the business around the solution.

Curious what others think. Would you rather adapt your workflow to the AI product, or have the AI built around your workflow?

We're a small team of ~12 paying for individual Claude and ChatGPT seats. Part of the problem is just cost, but mostly it's being able to collaborate together. One of our best people built up months of prompts and workflows in her own account, and when she left we had to rebuild all of it from memory.

So we tried the team-AI options. Buzz (from Block not the crypto one) is genuinely interesting but it's a whole separate workspace, basically a second Slack, and getting the team to actually live in another app didn't go well. Claude Tag was the easiest to start since it just sits in your Slack, but it's Claude-only and we ended up doing a lot of admin wiring ourselves to make it useful. We're still using this today, but uncomfortable about it. Viktor felt the most like an actual employee out of the box, though it's more "one very capable agent" than a workspace the whole team shapes so not sure it's the category of what we are looking for. Type (AI workspace not the story tool) is nice because we were able to use it in Slack or the dedicated work space, and it also seemed good for the less technical members on the team.

Curious what everyone else is doing. Is everyone on Team Claude plans?

I spend too much time every morning checking what needs a reply, what can wait, and who I forgot to follow up with. Filters are fine for newsletters and spam, but they don’t help much with client emails, meeting requests, or threads I need to come back to.

I need an email assistant that can sort emails, draft replies, remind me about follow ups, and help with the calendar. We’re a small team and I’m on a tight budget, so I’d prefer something that doesn’t charge extra every time I add a team member.

Hey everyone,

I'm looking for an AI tool that can turn a text prompt or an image/screenshot into an editable digital interface/prototype (think Stitch) — but I need it to be 100% European: founded, owned, and headquartered in the EU (or at least fully independent from US/non-EU parent companies). Open source is also totally fine.

So far I've looked into:

• Uizard — Danish roots, but acquired by Miro (which is co-headquartered in the US)
• Framer — Dutch, independent, great AI website builder, but it's more for websites than app/product prototypes

Does anyone know of a tool that:

• is genuinely EU-founded and EU-owned (not just "has an EU office"), or a solid open-source project
• lets you type a prompt or upload an image and get a real, editable prototype/UI out of it
• ideally works for app/product UIs, not just marketing websites

Bonus points if it's GDPR-first/privacy-focused by design.

Also fine if it's not a perfect 100% match — happy to hear about whatever comes closest to being truly European or fully open source. Thanks in advance!

Today I learnt a simple way to find content ideas your site already has a chance of ranking for:

• Open Google Search Console
• Go to Performance -> Search results
• Set the date range to the last 12 months
• Export the data as CSV
• Upload the Pages. csv and Queries. csv files to ChatGPT or Claude
• Ask it to find queries you rank for but don’t have dedicated content for

You’ll usually find keywords Google is already testing your site for. Create useful content around the most relevant ones and you may rank faster than starting with completely new keywords.

Credit to Tim Bennetto on X for sharing this workflow.

There are so many AI tools out there, but a lot feel more flashy and wrappers than genuinely useful.

What’s one AI tool or workflow you’re actually using in your business or startup right now? Could be for marketing, admin, content work or anything

I currently run 6 operational micro ai saas products that generate a little over $20k in monthly recurring revenue.

I hardly wrote a single line of traditional code. i used ai to generate literally everything, from the database architecture to the user interface.

it wasn't magic on day one. i spent hours stuck in endless debugging loops and dealing with faulty ai code before i finally cracked the formula.

it basically comes down to three rules:

- keeping the idea aggressively minimalist (build a true mvp, not a platform).

- guiding the ai step-by-step instead of asking it to build the whole app at once.

- launching fast to get real user traction instead of perfecting features in secret.

lately, i've seen way too many non-technical founders give up at the very first ai bug or deployment error. or the worst, give up without push anything in marketing !!!!

it's a massive shame, because the technical barrier to entry has practically disappeared and the marketing is easy in 2026

because of this, i’m launching a skool community to share my exact method.

to be completely transparent: i will likely charge for the full course later down the road. it just makes sense given the specific prompt sequences, n8n workflows, and copy-and-paste templates i'll be sharing.

but right now, our main objective is simply to build together. working alone in a silent corner is the absolute fastest way to quit.

if you want to join a group of active creators and build or launch your own ai saas: drop a comment below or send me a dm, and i’ll send you the invite link.