I've been building Hoops GM — a free basketball franchise manager that runs entirely in your browser (desktop + mobile, no sign-up).



You run the front office: trades, the draft lottery, free agency, the salary cap — then coach live games on a real possession-by-possession engine, with an owner who tracks your record and can fire you.



Extras: pick a "franchise idol" to build around, blitz games at up to MAX speed, chase a Hall-of-Fame dynasty across seasons.



Play (free): https://hoops-gm-chi.vercel.app

Would love any feedback on the first 5 minutes.

I've been exploring a question that feels increasingly important as agentic AI develops:

What happens if we stop building AI to help entrepreneurs and start building AI that can actually perform the entrepreneurial loop?

Today, the typical architecture looks like:

Human → Idea → AI → Product → Company

I'm interested in reversing it:

AI → Problem → Opportunity → Business Model → MVP → Validation → Growth → Iteration

In other words, the AI isn't just writing the code.

It is responsible for the entrepreneurial process itself.

An AIpreneur system could potentially:

• discover unmet needs from market signals
• generate and rank business opportunities
• formulate hypotheses
• design business models
• build and deploy MVPs
• run experiments
• analyze user feedback
• change the product based on evidence
• decide which experiments to kill
• identify promising opportunities
• continuously iterate toward product-market fit

The human role changes accordingly.

Instead of necessarily being the founder, the human could become the capital provider, governor, strategic constraint, or partner.

This is the idea behind AIpreneur.

I'm building an open-source AI Entrepreneurship Lexicon + Framework to give this emerging paradigm a vocabulary.

Some of the concepts include:

AutoFoundr — AI systems capable of autonomously executing parts of venture creation.

DataFound — discovering potential ventures from data and market signals.

Prompture — exploring venture hypotheses through generative intelligence.

AIonate — using AI not merely to automate a process, but to redesign it.

CogniScale — scaling a venture through continuously improving machine cognition.

SelfIterate — allowing the entrepreneurial system to learn and modify its own strategy.

But the vocabulary is only the beginning.

The real experiment is:

>

I'm not claiming we've solved this.

Quite the opposite.

I want developers to try to break the idea.

What would the architecture look like?

Where should autonomy stop?

How should an AI decide that an opportunity is worth pursuing?

Can an AI genuinely discover a non-obvious market rather than remixing existing businesses?

What happens when multiple AI entrepreneurs compete?

And perhaps the biggest question:

At what point does an AI agent stop being a tool and start becoming an economic actor?

I've put the initial lexicon and framework here:

GitHub — AIpreneur

It's open source and intentionally unfinished.

I'd genuinely like feedback from people working on AI agents, startups, autonomous systems, economics, and AI safety.

Don't just tell me whether you like the idea.

Try to build it. Try to break it. Add to it. Fork it.

Maybe the next generation of startups won't be AI-powered startups.

Maybe they'll be AI-founded startups.

I own a residential cleaning company in Colorado. We're at about $75k/month with 209 recurring customers and a 5.0 rating from 80+ Google reviews. I'm not a developer. Over the past couple of years I've built out an automation layer on no-code tools plus AI that runs most of the back office, and since this sub is where I learned a lot of what I know about service businesses, here's the full inventory. Numbers included, and one expensive failure at the end.

The stack is Make.com, Airtable, Stripe, Slack, a texting service, and our booking software. Total tool cost is a few hundred a month. I direct the builds with AI doing the heavy lifting; I don't write code.

1. Billing runs itself. When a crew marks a job complete in our booking software, an automation calculates the final amount (base price plus a distance adjustment from Google Maps), writes the job to a ledger in Airtable, and either charges the card on file or sends a Stripe invoice, depending on the customer's setup. Commercial clients get swept into one monthly invoice automatically. I don't touch routine invoicing at all.

2. Speed-to-lead texting. Every lead from Thumbtack, Angi, or our website gets a personal text from my number in under a minute: "Just got your quote request. Okay to call in the next couple minutes?" If they don't reply within five minutes, a follow-up goes out. Every lead also posts a card into a Slack channel with their name, address, home details, and a tap-to-call phone number. When a lead texts back, it shows up as a thread in Slack and anyone on my team can reply from Slack; the reply goes out as a text from our number. Thumbtack runs about one new recurring customer a week for us, and speed is most of why.

3. Hiring without phone tag. Applicants from our job ads get an automatic text inviting them to book their own interview through a scheduling link. When they book, they get a confirmation text with a photo of our office so they can find it, and the interview lands on my manager's calendar and mine. No back-and-forth, no chasing people who were never going to show.

4. Post-service survey that pays customers. After each service, customers get a short survey. Completing it automatically applies a $5 credit to their next invoice, no coupon codes, no manual step. Low ratings ping a Slack channel so we can call before it becomes a bad review.

5. Daily ops accountability. Our operations tasks live in Airtable. At 4pm a bot posts anything not done to Slack. At end of day, another automation scores each task on-time, late, or missed, and posts a digest. It sounds small. It changed how consistently things get done more than anything else on this list.

6. Crew paperwork. Every day at 2pm, an automation builds a PDF appointment sheet for each of the next day's jobs, with customer notes and access details, and files them in a Drive folder for the crews. Mileage and route reports per cleaner generate themselves monthly.

7. SEO content. Twice a week an automation drafts a blog post from a topic queue, generates an image, publishes to our site with proper schema markup, and cross-posts to our Google Business Profile. Our organic leads have grown steadily since we cleaned this pipeline up.

The failure: our referral program. We built an automated referral email that sent happy customers a $50 coupon code to share. It ran for months. Zero redemptions. Not low, zero. When I finally audited it, the whole design was wrong: one-sided (nothing for the referred friend), email-only for something people share by text, no way to attribute who referred whom, and the coupon literally couldn't apply the way we'd configured it. We're rebuilding it two-sided over SMS. Lesson I'd pass on: an automation that runs is not an automation that works. Instrument the outcome, not the activity.

What actually mattered, ranked: speed-to-lead first, billing automation second (it's not glamorous but it's hours every week and zero missed invoices), the ops scoreboard third. The SEO pipeline compounds but took the longest to pay. The stuff I'd skip if starting over: anything I automated before the manual process was solid. Automation amplifies whatever's there, including the broken parts.

Happy to answer questions about any piece, costs, or how I'd sequence it starting from zero.

👋 Hey n8n community,

I pulled the image-description part out of a bigger product-content workflow and turned it into a small standalone template, since a few people wanted just that piece. It's now up on the n8n library.

What it does:

• Upload one or more product photos through an n8n form.
• Each image is described on its own (looped, so nothing gets bundled into one call).
• The easybits Extractor returns a structured description per image, which works as product copy and doubles as image alt text.
• You get a styled results page with a thumbnail and a copy button per image, plus a clean fallback when an image can't be read.

Template: https://n8n.io/workflows/16901-generate-product-image-descriptions-from-form-uploads-with-easybits-extractor/

The thing I keep wondering: most shops and sites still write image descriptions and alt text by hand. How are you handling it right now, manual, a vision model, or something automated? And if you were taking this to production, what would you add first, bulk upload, direct publish to your shop, multi-language?

Best,
Felix

👋 Hey n8n Community,

A while back I built a purchase order extractor for a friend who was drowning in PO PDFs. It let him batch-upload the documents through a form and pull all the data into a Google Sheet through the easybits extractor. That alone saved him a lot of manual re-typing.

Last week he told me his company is moving onto SAP, and he asked whether the workflow could also spit out EDI files so he can push the orders straight into the ERP instead of keying them in by hand. So I built that in, and while I was at it I made the whole thing a good bit more robust.

How it's set up:

• Batch PDF upload: the form takes one or many PO PDFs at once, and a toggle lets you decide per submission whether you also want EDI files out.
• Extraction: each PO runs through the easybits extractor one at a time and lands in a Google Sheet, one row per line item, with the source document name on every row so you can always trace a row back to its PDF.
• EDI 850 generation (optional): when the toggle is on, each PO is also turned into a valid X12 850 EDI file and saved to a Drive folder, ready to upload into SAP. A separate sub-workflow handles the generation, so the main flow stays clean.
• Duplicate check: after extraction it checks the PO number against what's already in the sheet. If that PO was processed before, it skips it, so you never get double entries.
• Flag summary: the completion screen tells you if any field was missing or looked off in an extraction, and lists any duplicates it skipped along with the PO number.

Short video attached showing a batch run of three POs with EDI generation switched on, then a re-upload of one of them so you can see the duplicate check catch it and report which document and PO number it was.

Both workflows (the main one plus the EDI sub-workflow) and a setup guide are here: https://github.com/felix-sattler-easybits/n8n-workflows/tree/f4dec1bef3561aa9e803bb21b96ebff1ab0dde04/easybits-purchase-order-extractor-v2

You'll also find it alongside 20+ other n8n workflows in my repo. If it's useful to you, a ⭐ really helps other builders discover it too: https://github.com/felix-sattler-easybits/n8n-workflows

Curious how the rest of you are handling the PO-to-ERP step. Are you going through EDI, hitting a direct API, or still uploading into the ERP by hand?

Best,
Felix

Curious how others are handling this.

We’re building seeki.eu a pan-European AI property marketplace. We always knew content and link building would be part of the job. The difficult part is doing that while also trying to build the actual product.

We’ve been sitting under 20k impressions for few months now. At the same time, we have over 400k pages that have been crawled but aren’t indexed. My AI agents are telling me that it's because our domain not having a good authority (and bing tools are outright saying we lack backlinks from high quality domains). Which makes sense, Google won't go full throttle on a new website nobody knows about. They suggested writing blogs posts which will be cited on other portals and sending them manually to news outlets (does anyone do that?). But same like Google, why would they cite a brand new website nobody knows?

We also use Clarity to monitor citations, and after we added some new articles (optimized for AEO) to Google’s index, we started seeing a few of them show up in AI-search citations the following week (the speed of it was quite surprising).

One thing I find especially annoying is the indexing workflow. Every time we publish a new blog post, we have to go into GSC and manually request indexing (even though we have sitemaps, but it takes Google ages to get it from sitemap). There seems to be a fairly small quota too, around 10 URLs for us. I haven’t found a proper way to automate this for normal blog posts.

Is everyone just doing this manually, or is there a better workflow?

More generally, what tools are small teams using for:

• content planning and writing
• social publishing
• link building and outreach
• monitoring mentions or AI-search citations
• finding relevant discussions to participate in
• tracking whether any of it is actually working

There are plenty of tools for individual parts of this, but I haven’t found anything that feels particularly practical for a 1–5 person team that is also busy building the product.

I’m not looking for another list of enterprise marketing platforms. I’m more interested in what people are actually using day to day, including spreadsheets, scripts, manual processes, or combinations of smaller tools.

👋 Hey n8n community,

A few weeks back I helped one of our users whose data table extraction kept bleeding cells between rows: 95% of the data came out right, but the last 5% landed in the wrong rows, so he could never fully trust it. The way I fix pipelines like that is I never eyeball the output, I build a testing workflow that scores every extraction against a known-good reference so I can benchmark it and see if my changes actually helped.

I shared a first version of that tester, and a bunch of you asked for a v2 that lets you upload your own reference through the same form instead of hardcoding it. So that is what this is.

I also recorded a short video where I run a full test end to end, if you'd rather watch it in action.

How it works:

You upload two things on one form: the document you want to test, and a reference to check it against. The reference can be a CSV (exported straight from Excel) or a PDF/image of the same table. The workflow extracts your document, compares every cell against the reference, and shows a pass/fail card with the accuracy, the mismatches, and how long the extraction took. Each run is logged to a Google Sheet so you can compare engines and track accuracy over time.

The clever bit is trust. A CSV is trusted as-is because a human made it. A PDF reference gets extracted first and shown back to you to confirm before it is used as ground truth, so you are never grading one guess against another.

A few takeaways even if you skip the video:

1. Don't eyeball table extraction. Scoring every cell against a reference tells you exactly which rows slipped, instead of scanning 20 rows by hand.
2. Trust your reference before you trust the test. If your ground truth comes from an extraction too, verify it first, or a "100%" means nothing.
3. When rows slip, refine the descriptions. The easybits Extractor lets you write a description per data field, and that context is usually what fixes it. Tightening a field's description often covers new layouts too, without touching the workflow.
4. Your reference CSV headers have to match your pipeline field names. That one mismatch silently fails every row, so I added a small column map in the workflow to line them up.

Grab the tester here: https://github.com/felix-sattler-easybits/n8n-workflows/blob/e203ef38bc69db58e08e282b18bc287d69d7d85b/easybits-data-table-extraction-testing-tool/easybits_data_table_extraction_testing_workflow.json

It sits in my repo with 20+ other n8n templates I have built with this community: https://github.com/felix-sattler-easybits/n8n-workflows

How do you currently check whether an extraction is actually correct, by hand or with something automated?

Best,
Felix

👋 Hey n8n Community,

I've built a lot of finance workflows over the last few months for friends who run small businesses, and going back through my library I realised I'd never shared the most basic one people keep asking for: a simple batch invoice extractor. So I cleaned one up and pushed it to the n8n template library: Extract batch invoice data from form uploads with easybits and Google Sheets.

The idea is simple. You upload one or many invoices (JPG, PNG, or PDF) through a single form, and it extracts the data from all of them in one go, instead of dragging every invoice in one by one. Each invoice lands as a row in a Google Sheet, and when the batch finishes, the form shows a summary marking every file with a ✅ or ❌ so you instantly see which ones need a second look.

How it's set up:

• An n8n Form takes one or more invoice files.
• The files get split into one item per file, keeping the original filename.
• It loops over the invoices one at a time, sending each to the easybits Extractor, which returns the fields (invoice number, date, vendor, total, and so on) as a structured data object.
• The filename gets reattached, and a check runs over the critical fields.
• One row per invoice is appended to Google Sheets, with a pass/fail status.
• A batch summary is shown as the form's completion message.

A few things from the build that might save you time on your own flows:

• The extractor bundles everything you hand it into one request. Pass it all the files at once and you get one merged result back, not one per invoice. Looping one file at a time is what gives you a clean result per invoice. This one cost me a debugging session.
• Treat "missing" as a signal, not an error. The extractor returns null when a field isn't on the document. Instead of fighting that, I lean into it: a small check flags any invoice missing a critical field, which is what powers the ✅/❌ summary. Worth catching the sneaky empties too (the string "null", empty strings, whitespace), so nothing slips through looking present when it isn't.
• The fields are yours to change. The mapped fields are just a starting point, so you can add whatever you need to pull from your own invoices, like a VAT ID, PO number, or IBAN. The extractor also has auto-mapping, so you can upload one example invoice, let it detect the fields, and tweak from there.

I also recorded a short video showing how it runs end to end, which I'll post alongside this.

For more free workflows, feel free to check my GitHub as well: https://github.com/felix-sattler-easybits/n8n-workflows. A star helps other builders find it, so I'd be really thankful for that support.

How do you all handle the invoices that fail extraction? Curious whether people flag them for manual review like this or route them elsewhere.

Have a good start to the week.

Best,
Felix

Out of boredon I added ffmpeg and MELT to my server running Hermes to see if it can edit videos. I dropped 11 videos into a folder and gave it the prompt below.

Video: https://www.youtube.com/watch?v=c_OVKAWGyFU

Prompt:
There are a bunch of mp4 videos in /path/dogfun/ that I want to turn into one long movie. The video are of my dogs. The malinois/shepherd looking one is Adi and the black dog with a white chest is Duckie. Whenever each dog is on screen, I want you to add text below the dog with their correct name. I want you to find some rowdy punk rock music as the soundtrack. Open the video with a title card overlay on top of the video called "Dogstravaganza" and the very end should have scrolling credits for Duckie and Adi at the last 5 seconds of the finished video. Use crossfade and swipe transitions between each of the videos.

I am lazy, and it feels so boring to babysit and watch ai agents do the job and asking for input or waiting for task completion.
So I built a simple tool that notifies me (via ntfy) on my phone.

I know its wayyy too lazy, but hey, at least I dont zone out playing on my ps4 anymore, lol.

If someone is like me and also tired of watching the laptop screen instead of playing fifa, be my guest: https://nockit.uk (yes, that was the cheapest domain I could get)

A walkthrough of RoboCo with screenshots. Open source-self hosted AI Software Company.

---

Let's clarify a couple things:

Task hierarchy:

- Root task (Main PM and Main PR Reviewer exclusive; but Board can help unblock if there's any blocks).
- Cell Task (Cell PMs and Cell PR Reviewers exclusive; but Board and Main PM can help unblock if there's any blocks). Inherits from Root Task.
- Subtask (Cell Devs, Cell PMs and Cell PR Reviewers exclusive; but Main PM can chime in). Inherits from Cell Task.

Task lifecycle:

Main PM creates subtask (delegate), Cell PM (be | fe | ux-ui) create subtask (delegate), Devs work on the tasks and open a PR. QA checks the work done and sends back with "needs_revision" to the original Dev or pass/approve moving to the Documenter agent. Documenter finishes its bookkeeping, moves on to Cell PR Reviewer. PR Passes or fails -> same cycle as QA. Sends back for rework or approves and merges. Once a Cell PM sees all subtasks are in terminal state (cancelled or completed) opens its PR onto the root task. Once the Main PM holds the complete implementation, opens a PR into your master/main branch and the task is moved onto "Awaiting CEO Approval"... so, your approval.

Task creation:

Go to the Task Assistant tab, select the type of task you want created, and just let it interview you. Personal recommendation is to always do the Board Review of the Drafted Proposal so that the Product Owner and the Head of Marketing can adjust the scope and find gaps on the Proposed Task Draft from the Task Assistant.

Don't sleep on conventions/project settings!!

If you really want a good quality of code, to have your time back and take a breather from your computer and work: Take the time to setup things correctly. You'll thank yourself later for doing it so. I mean it. Take your time, read the settings, enable whatever you need/like and the output will be exactly what you asked/setup for.

---

That's pretty much all you need to get yourself up and running with RoboCo.

From personal experience: I've recovered my life-work balance. It allows me to forget about development FOR HOURS ON END, until I've got something to actually review and pass/reject. The cycle continues.

The mission? I've created it for solo-devs, solo-founders as well, that need a team but they can't yet afford it or just don't have it atm. This, RoboCo, is that team behind you. And it's been great for myself so I naturally want to share it with others.

---

PS: Reddit only allows 20 images. I had way more. Full docs here.
PS 2: You can check its progress here, since it's building itself live in public