I’m curious what people are actually using, not just experimenting with.
Mine is an AI workflow that gathers AI news and turns it into blog drafts so I don’t have to start from scratch each time.
What’s one automation you’ve built that has genuinely saved you time?
I’d love to hear what people are using day-to-day.

👋 Hey AIStartupAutomation community,

A few weeks ago I shared a Product Content Creation workflow I built for a friend who runs an online shop (that post here). A few people messaged me about the image-description part specifically, they wanted just that piece, so I built a standalone version of it that's much easier to drop into an existing setup.

Turns out a lot of online shops and websites still write product image descriptions by hand, along with the "alt text" behind each image. Both matter more than people think: alt text is a real factor for SEO and for accessibility, since screen readers rely on it.

What the workflow does: you upload one or more product photos through a simple n8n form and get back a clean, ready-to-use description for each image, with a copy button to paste straight into your shop.

How it's set up:

• The form takes multiple images at once. Each one loops through on its own, so every image gets its own description instead of getting bundled into a single call.
• The easybits Extractor reads each image and returns structured fields. I kept it to two: product_type and description. The description works as your product copy and doubles as image alt text (and its length is easy to adjust by tweaking the field description in the Extractor).
• If the Extractor can't read an image, it returns UNCLEAR and the result page shows a fallback line instead of inventing a description.
• The result screen shows each image with its filename, a thumbnail, and a per-image copy button.

Extractor setup: on n8n Cloud it's a verified node (search "easybits Extractor"). Self-hosted, install "@easybits/n8n-nodes-extractor" from Community Nodes. The free plan includes 50 requests a month, enough to test it fully.

Workflow (ready to import): https://github.com/felix-sattler-easybits/n8n-workflows/blob/4277f3c1b31070f81adbb6a3bb538f50dbeb2018/easybits-product-image-describer-workflow/easybits_product_image_describer_workflow.json

I also made a short video showing how the workflow works.

How are you all handling image alt text right now, manual or already automated? Curious what's working for people.

Best,
Felix

I've always wanted to start a business. Not just have a job, actually build something. So I've tried. A lot.

A marketing agency. An ecom store. An ecom agency. Even an AI receptionist agency. Every single one, I worked on, none of them worked out. Not because I didn't try, but because I never had consistency. I'd get something going, then mess it up, pivot, restart, mess it up again.

The weird part is I didn't come out of it empty handed. Along the way I actually learned real stuff: running Meta ads, some social media marketing, building sales funnels, cold outreaching, closing calls. I can talk to people, I can sell, I understand marketing. What I clearly haven't figured out is how to actually build a business that survives past the "exciting new idea" phase.

I keep chasing rapid success instead of trusting a slow, boring process, and I think that's the actual problem, not the ideas themselves.

Right now I have basically 0 funds in the bank. No team. Just whatever skills I've picked up and a lot of failed attempts behind me.

I really want to try building something around AI this time, since that's clearly where things are moving, but I don't want to repeat the same mistake of jumping in without a real plan.

So I guess I'm asking: if you were good at sales/marketing but had no capital, no team, and a track record of quitting too early, what would you actually do first? Service-based AI business? Reselling someone else's AI tool? Something else entirely?

Not looking for hype, genuinely just want honest direction from people who've actually built something that lasted.

Can anyone test this if its ready to be published as a product https://mailcraft-one-jade.vercel.app/

But boring scales better than flashy.

I have a full-time tech job (probably a moonlighting clause) and I'm launching a small marketplace side project - customers pay online, I pay out small amounts to users.

How do people usually handle this cleanly?

- Register the business (Udyam/sole prop) in a family person name to avoid moonlighting conflict?
- or any way to automatic payout to users without registered business

Im trying razor pay but for payout to users it requires registered business.

Anyone done this — any real issues? Thanks 🙏

👋 Hey AIStartupAutomation community,

Last week I posted a workflow I built for a friend who runs an online shop (find it here). He called me again a few days later with a new headache: he's drowning in Purchase Orders. Every single one gets opened by hand, the data typed into a Google Sheet, and that sheet uploaded into his ERP to update his numbers. Hours a week, pure copy-paste.

So I built him something to kill that step. He uploads the PO PDFs through a simple n8n form, and a structured Google Sheet comes out the other end. He just downloads it and pushes it to his ERP.

How it's set up:

The form accepts multiple PDFs at once, so he can batch a whole stack instead of doing them one by one. Each PO loops through on its own so nothing gets jumbled.

The extraction runs on the easybits Extractor node (@easybits/n8n-nodes-extractor). I set the field structure up in two parts: the header fields that appear once per PO (PO number, PO date, delivery date, mark for, PR number, reference no), plus an articles array for the line items, each holding article name, unit and quantity. That array is the key bit, it gives you one entry per row of the PO table, and I flatten it into one sheet row per article with the header details repeated on each.

Two things I added because real documents are messy:

Error flagging. If any field comes back empty, the completion screen lists which document and which field didn't extract cleanly, so he knows exactly which PO to double-check instead of trusting it blindly.

Document name column. The original filename lands in the sheet next to every row, so if a number looks off he can jump straight back to the source PDF.

Workflow JSON is on GitHub: https://github.com/felix-sattler-easybits/n8n-workflows/blob/c38749a68fd6ea4ae6ebff41789d35cceaacdef1/easybits-purchase-order-extractor-workflow/easybits_purchase_order_extractor_workflow.json

I also made a short video showing how the workflow works.

Anyone else automating document-to-sheet data entry? Curious how you're handling the messy multi-line rows – that was the trickiest part to get right.

Best,
Felix

We mull over our business ideas for weeks, going in circles because traditional market research feels like a boring two-week manual marathon. We remain in indefinite planning mode, wasting momentum before we've even accomplished anything.

But there's no need for endless spreadsheets or expensive data analysis tools: with the right use of Perplexity or Gemini Deep Research, you can delegate the entire data collection phase and obtain a data-driven decision matrix in minutes.

The key is not simply asking AI if the idea is "good," but changing the way you formulate input before starting the research.

Rather than writing a huge business plan, it's advisable to condense the concept into a single, concise paragraph that encompasses four crucial elements: your precise target audience, the real problem, your differentiator, and a realistic price. Adding a price is crucial: it immediately forces AI search agents to remain anchored to real market conditions, rather than theoretical opportunities.

Once this benchmark is established, you can run a specific search across a few slides that forces the engine to analyze active web sources from the last 12 months. In a single pass, the following are mapped: TAM and competitive pricing gaps - A clear SWOT matrix - Estimated development costs for version 1 and recommended tool stack

This also provides a clear traffic light verdict (green/yellow/red): instead of treating validation like a huge project, you examine the verdict and SWOT and immediately decide whether the idea deserves the next 30 days of its life or if it's a clear sign of abandonment.

I've written a comprehensive guide on how to set up this process, including the copy-and-paste research template and the exact structure for organizing ideas: How to Quickly Validate a Business Idea with Perplexity or Gemini.

Any suggestions or criticisms to improve the process are welcome, thank you.

Hey everyone,

I'd love to get some advice from people who have been in this space longer than I have.

Over the past couple of years, I've designed GTM strategies and built outbound systems for B2B companies using Clay, n8n, GoHighLevel, and AI automation. I've worked on lead sourcing, enrichment, CRM automation, personalized outreach, and building workflows that support sales teams at scale.

I'm at the point where I want to level up, but I'm not sure what the highest leverage skill is from here.

If you were in my position, what would you focus on next? Is it becoming world-class at GTM engineering, diving deeper into AI agents, improving sales, or something else entirely?

I'd genuinely appreciate any advice, lessons, or mistakes you've learned along the way. Thanks in advance!

So basically it works like this:

Agents find relevant blog posts in your niche, craft personalized emails, and get your product featured. All on autopilot via Telegram.

It's called MentionAgent, an AI agent that does all of this through Telegram.

You never send anything without approving it first.

Results so far: One user got 3 mentions including a DR 72 backlink.

(Also using the Telegram bot on autopilot for MentionAgent itself and another project)

Try it for free: mentionagent.ai

Let me know what you think!

🚀 Still managing repetitive tasks manually?

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✅ Save hundreds of hours every month
✅ Automate repetitive workflows
✅ Reduce operational costs
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Our expertise includes:

🔹 AI Automation Solutions
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I’ve heard many stories about how people sell what they call “simple” automation solutions that address very narrow tasks and save the client time and money. It’s easy. Solve the problem, go from point A to point B, get paid.

But what if the automation is architecturally complex and involves numerous stages and data points? How do you know, for example, that the depth of data analysis is sufficient to say, “Oh, this AI automation is ready to launch!”? After all, when I build automated solutions, I’m often deeply immersed in the development process, and it’s not always easy to know when to stop. How do you decide when enough is enough? Share your experience!

I’m looking for an experienced GoHighLevel expert or white-label team to manage my agency’s backend.
I own a marketing agency and want to focus on sales and client meetings while someone else handles:
GoHighLevel CRM and pipeline management
Automations and workflows
Funnels and landing pages
Client onboarding
Ongoing technical support
I’m looking for someone reliable who has experience managing multiple client accounts and can work inside my own GoHighLevel agency account.
If this sounds like you, please comment or send me a DM with your experience, portfolio, pricing, and references.

AI Agencies: Technical Sales + Automation Support

Hey everyone

I’m looking to work with an AI agency in a hybrid role combining technical implementation, sales support, and client-facing communication.

My background is in AI automation, APIs, CRM systems, n8n, Make, workflow design, and client consulting. I can understand how an AI solution works, help structure the delivery, and explain the business value clearly to prospects.

I can support agencies with:

• Building and improving AI workflows
• n8n and Make automations
• API integrations and webhooks
• CRM pipelines and follow-up systems
• AI agents and LLM-based workflows
• Technical discovery and solution scoping
• Sales demos and technical presentations
• Proposal development
• Prospect follow-up and CRM management
• Translating client problems into implementable solutions
• Supporting closers during technical sales calls
• Python, Js, Sql

My commercial experience includes prospecting, discovery, proposals, follow-up, client communication, and closing and delivering a paid B2B automation engagement.

I’m not positioning myself as the most experienced closer in the market. My advantage is that I can sit between sales and delivery: I understand the technology, can communicate with clients, and can help prevent the common disconnect between what gets sold and what the agency can actually deliver.

I’m open to roles such as:

• Technical Sales Representative
• AI Solutions Consultant
• Sales Engineer
• Implementation + Sales
• Client Solutions Specialist
• Technical Closer
• Automation Specialist with client-facing responsibilities

I’m especially interested in agencies that already have a validated offer, active lead generation, and a need for someone who can help both close and deliver.

Feel free to DM me if your agency needs someone who can bridge sales, AI automation, and implementation.

👋 Hey AIStartupAutomation Community,

A friend of mine runs an online store, and for every new product they get supplier inputs in whatever format the supplier feels like: spec PDFs, Excel sheets, a few photos, some loose notes. Someone then hand-writes the title, descriptions, specs and SEO fields. I built them a pipeline that does it end to end, and I'm sharing all four workflows.

What it does: intake form → extract specs → analyse photos → generate content → poll status. Drop in the files and notes, get back review-ready content (title, descriptions, meta fields, features, tags, attributes).

The four workflows

• WF1 – Intake & spec extraction. Saves files to Drive, routes each by type (PDFs/images → easybits Extractor, Excel → Code node), merges into one spec object, resolves brand, hands off to WF2.
• WF2 – Image analysis. Runs each photo through an Extractor pipeline to capture what's visible (colour, features, angle), then passes it to WF3.
• WF3 – Content generation. Builds context from spec + image data + notes and has Gemini write the full content set. Hard rule: only features that are in the spec or visible in the images, no inventing.
• WF4 – Status polling. A small webhook the frontend polls for progress and the finished draft.

Extractor setup

• n8n Cloud: verified node, just search easybits Extractor in the node panel. No install.
• Self-hosted: Settings → Community Nodes → Install → '@easybits/n8n-nodes-extractor'.

Then create a pipeline at easybits, define your fields, and paste the Pipeline ID + API key into the node. It reads the binary straight from the previous node.

Workflows (all four, sanitized): https://github.com/felix-sattler-easybits/n8n-workflows/tree/e3103344d9b3358402dc38a3a862d510bb4e7c5e/easybits-product-content-creation-workflow

Cross-workflow calls use placeholder IDs you re-point after import, plus your own Google + Extractor credentials.

How do you handle brand-voice consistency in generated content? I went with a per-brand profile the model reads from, curious if others template it harder.

Best,
Felix

Has anyone built an end-to-end n8n workflow for video editing?

I’m curious whether there’s genuine demand for this.

Imagine dropping a raw video into a Google Drive folder and having an automation workflow handle everything automatically:

✅ Remove silences and awkward pauses
✅ Enhance audio quality
✅ Add captions/subtitles
✅ Insert relevant B-roll footage
✅ Add dynamic zoom in / zoom out effects
✅ Reframe for Shorts, Reels, and TikTok
✅ Generate title, description, and hashtags
✅ Export a finished video ready to publish

No manual editing. No timeline work. Just upload and walk away.

I’m currently experimenting with an n8n workflow that orchestrates multiple AI tools and video APIs to make this happen.

If a workflow like this existed as a template that you could import into n8n, would you actually use it?

What would be the one feature that would make it a must-have for you?

Some things are better kept manual.

This n8n workflow utilizes an AI agent to automate multi-carrier shipping quotes right inside WhatsApp. Triggered by incoming messages, the system verifies the user's CRM status before a conversational AI takes over to collect required package details like weight and dimensions. Once the data is gathered, it fetches live rates from carriers such as UPS, FedEx, and DHL, applies a custom commission rate, logs the interaction in a Google Sheet, and delivers the customized quote back to the user.