DEV Community: pr0biex

Your revenue goal is not a plan. Here is the arithmetic that makes it one.

pr0biex — Wed, 28 Oct 2026 10:07:52 +0000

A revenue goal copied from someone else's screenshot is not a plan. It is a wish with a deadline.

The missing step is between the money and the calendar: how many customers, at what price, with what churn, inside the hours you actually have. Skip that step and the plan dies in February, when the first month does not look like the average.

Start with the money you need

Most annual plans start with a revenue target someone else picked. Start with your life instead.

Take the owner pay you need to take home. Add the business expenses that do not move. Then set aside a tax reserve before you spend anything. The revenue need is the sum, grossed up for the reserve.

With $60,000 in owner pay, $12,000 in expenses, and a 30% tax reserve, the revenue need is about $102,857 for the year, or $8,571 a month.

That is the number the business has to cover. Not a number a screenshot told you to want.

Solve for customers, not revenue

Revenue is an output. The inputs are average revenue per customer, churn, and the number of new customers you can add each month.

At $50 a month per customer, $102,857 a year is not 2,057 customers. It is 2,057 customer-months before services. The workbook first subtracts $12,000 of planned services revenue, leaving $90,857 of product revenue, or 1,817 customer-months. Spread across a year that starts with 40 customers and loses 5% of them every month, the constant number of new customers that makes the 12-month total equal the target is 23 a month. That ends the year at 233 customers and $11,650 in monthly recurring revenue.

The difference between 23 new customers a month and 2,057 customers is the difference between a plan and a panic.

The constraint most plans skip: hours

A customer count is not a capacity plan. If each customer takes 1.5 hours a month and you have 30 hours a week, you can carry about 86 customers. The default plan ends at 233, which is 2.7 times the hours you actually have.

That is not a failure. It is the plan doing its job before the year starts. The fix is not more evenings. It is a price change: at $100 a month per customer, the same target needs about 9 new customers a month and ends at 104 customers, which fits the 30-hour week at 1.2 times capacity.

Move the price or move the target. Do not move your sleep.

Why a yearly plan needs a weekly review

A yearly number gets checked once, in December, which is the worst possible time to find out.

A Friday review takes fifteen minutes: customers added, customers lost, hours spent, and whether next week still points at the number. Weekly, the correction is small. You notice in week three that you added one customer, not three, and you change one thing. Yearly, the correction is a lost year.

Where to start

The 2027 Solo Business Plan is the workbook behind the math above. It starts from owner pay, expenses, and tax reserve, then solves for new customers per month, year-end MRR, traffic, and capacity. It includes a Notion build spec and a printable weekly review.

https://probiex.gumroad.com/l/solo-business-plan-2027

FAQ

Do I need to know my churn before I start? No. Use a conservative estimate, then replace it with the real number after the first month. The workbook shows how much the answer moves when churn changes.

Do I need Notion? No. The XLSX workbook is the model and does the math. The Notion spec is there if you want a dashboard.

What if I sell services as well as products? The workbook subtracts planned services revenue before it solves for product customers, so the customer count is not inflated by hours you have already sold.

Last updated October 2026 · Probiex.

Your AI-built app is probably leaking a secret. Here's the 20-minute check

pr0biex — Wed, 28 Oct 2026 09:36:09 +0000

You shipped a Lovable app on a Sunday. By Wednesday it had a Stripe checkout and one paying customer. Then you opened the browser bundle, searched for service_role, and found your Supabase key sitting in plain text. Every visitor with devtools could read your entire database.

Five checks catch almost all of this before a customer does: secrets in the client bundle, tables without row level security, write routes with no session check, webhooks that trust any caller, and a .env file that got committed. Do them in that order. The first is the fastest to verify and the most expensive to ignore.

How to check for leaked secrets

Build the app, open the output folder, and grep the JS for service_role, sk_live, and SUPABASE_SERVICE. In Next.js, also check every variable prefixed NEXT_PUBLIC_, because that prefix means it ships to the browser. If you find a key, rotate it before you touch the code. A leaked key stays valid until you rotate it, no matter what you commit next.

How to fix a table without RLS

Run this in Supabase:

select tablename, rowsecurity from pg_tables where schemaname = 'public';

Every row showing false is a table anyone holding your anon key can read. Turn RLS on, then write policies for select, insert, update, and delete separately. A select policy does nothing for delete, and that gap is how people lose data.

What to do before you take payments

Call your webhook with curl and no signature header. If it returns 200, someone can mark their own invoice paid. Then check each write route for a session lookup. Any handler that trusts a user id from the request body is an open door.

If you want the short version first, the 15-point check is free: https://probiex.gumroad.com/l/free-vibe-code-safety-check

I packaged the full checklist into a 60-point audit, a read-only CLI that runs 17 checks locally, and fix prompts you can paste into Cursor or Claude. It is the Vibe-Code Rescue Kit: https://probiex.gumroad.com/l/vibe-code-rescue

FAQ

Does the scanner upload my code? No, it reads files locally and prints a report with no API calls or telemetry.

Is this a penetration test? No, it finds the common expensive mistakes in AI-built apps and does not replace a qualified review.

Last updated October 2026 · Probiex.

I asked AI to write our launch post. Then my cofounder read it.

pr0biex — Fri, 23 Oct 2026 06:05:50 +0000

Last week I asked an AI assistant to write our launch post. It gave me three paragraphs in about forty seconds. Two made it out of the drafts folder. My cofounder read the final version and asked, half joking, if we had quietly started using an AI writing tool in 2024. We hadn't.

I did exactly that. I pasted the output in and changed a few adjectives. The piece shipped. It read like it was written by someone who had never talked to a customer.

The fix starts with the first sentence, which is also the most underrated line in any draft. AI search engines and excerpts pull the first direct answer, and AI-written openers tend to be broad claims, so the answer gets quoted before you get a chance to say anything true.

How to fix it

Score the draft before you publish. I use a 20-tell scorecard, grouped by structure, language, and evidence, with a 0 to 2 scale per tell. Anything you cannot verify scores 0.

Then run a cleanup pass:

Audit. Note every tell scoring 2.
Cut the weak sections. AI almost always writes one more than the piece needs.
Add one specific detail the model could not know. A number, a name, a date, a real quote.

The rewrite

You do not need to regenerate the whole piece. Swap the flagged lines using plain language:

"Content is king in the AI era" becomes "Start with your first real point."

"Our platform transforms the way teams work" becomes "It classifies support tickets and drafts replies. Setup takes an afternoon."

The tells

The scorecard sorts tells into structure, language, and evidence. Structure catches the rhythm problems. Language catches the vocabulary. Evidence catches the hand-waving.

If you want the full scorecard, the rewrite table, and the voice sheet, I put together The AI-Slop Audit: a 20-tell audit you can run in about 15 minutes. Check it out at https://probiex.gumroad.com/l/ai-slop-audit.

How do I know if my AI-written draft is bad?
Score it against the 20 tells; a result from 17 to 34 means it reads as AI and needs a rewrite before you publish.

How do I make AI writing sound less generic?
Add the specifics the model could not know, then run the flagged phrases through the rewrite table.

Last updated October 2026 · Probiex

The full catalog: 30 systems for people who run a business alone

pr0biex — Fri, 16 Oct 2026 18:55:56 +0000

59% of small-business invoices run more than 30 days late. 43 of 100 r/SaaS threads ask how to get lead generation. One in ten web pages now shows signs of AI writing.

Each of those numbers is the opening page of one of my products.

This store started with one free prompt pack. It is now 30 products, and the rule never changed: every product opens with published research that proves its problem is real, cites the source, then hands you the system that fixes it. Tools, not advice.

Here is the whole catalog, sorted by the problem each product attacks. One-time purchase, instant download, no subscription. The full page with all the detail lives at probiex.gumroad.com.

Getting customers

First 100 Customers: Warm Signal Playbook · Warm signals beat cold volume: 30 contextual replies do more than 1,800 cold messages.
90-Day LinkedIn Content Playbook · A day-by-day system, because most founders quit by post 5.
SaaS Founder Copy Vault · 80+ copy blocks for heroes, emails, and outreach, written to be adapted in five minutes.
The Landing Page Conversion Audit · Median B2B pages convert at 3.8% while top performers hit 10-15%. 81% of forms get abandoned. Find your leaks, ranked by recoverable revenue.
Silent Churn Rescue Kit · Day 7 decides most of your churn. A first-week behavior-triggered sequence, not another dashboard feature.
Cold Outreach Reply Pack · 40+ replies sorted by the objection that killed the thread.
GEO Operations System · A 0-100 scorecard for getting cited by ChatGPT, Perplexity, and AI Overviews, with a CLI scoring script and an llms.txt template.
Launch Week Email Kit · The seven emails that decide a launch, with subject lines and send-day timing.

Finance

The Late-Payment Playbook · Contract clauses, deposits, the two reminder emails most people never send, and the escalation ladder.
Freelancer Rate Calculator · Your rate floor from real costs and true billable hours. Competitor-copied rates often hide a 14% margin.
Break-Even CAC Calculator · The one CAC number your margins cannot survive above, before you scale spend into it.
The Pricing Calculator · Van Westendorp bands, value-metric selection, and three tiers as a workbook.
Runway & Breakeven Calculator · Real runway from trailing burn and committed spend, then the exact revenue where breakeven lands.
The Freelance Cash-Flow Planner · A rolling 90-day forecast with probability weights for late invoices.
SaaS Metrics Dashboard Kit · Paste six numbers on Monday, get the ten survival metrics with the decision each one forces.

Operations

Founder Anti-Burnout Weekly System · A fixed weekly cadence in about 15 focused hours, so building and selling stop competing.
Notion Content Calendar · A content database with pillars and repurposing, not a sticker board.
Notion Founder CRM · Leads, pipeline, and contacts specified for a one-session Notion build.
One-Person Agency Engine · Rate math, a 7-factor client scorecard, capacity thresholds, and the script for firing bad clients.
The Indie Hacker OS · Six linked Notion databases replacing the dozen tools most solo builders juggle.

Builds

Ship Your SaaS in 30 Days · A day-by-day plan from zero to paid, with the landing and launch templates.
LaunchKit Starter · A production Next.js 15 starter: auth, Postgres via Drizzle, billing, i18n, tests, CI. That is the boilerplate month removed.

AI and prompt systems

10 Free Claude Prompts for SaaS Founders · The starter ten: research, copy, launch, analytics. No email required.
100 Claude Prompts for SaaS Founders · 100 copy-paste prompts across research, copy, launch, analytics, and build-in-public. PDF plus source Markdown.
The AI-Slop Audit · A 20-tell scorecard that finds AI-written copy on your pages in 15 minutes.
Voice AI System · Schemas, compliance checklist, and setup guide for voice workflows that survive real usage, not just the demo.
AI Agent Blueprint Stack · Hand triage, inbox, scheduling, and reporting to supervised agents.
n8n Solopreneur Workflows · Three production workflows that run your week: RSS digest to email, leads to Slack, sales to your ledger.

Career and teaching

AI Resume Optimizer Spec + Kit · A weighted scoring rubric and prompt chains, so an AI resume tool ships quality instead of vibes.
AI Literacy Engineering Kit · 30 lesson plans that teach students to think critically with AI, with worksheets, rubrics, and a policy kit.

Where to start

The free pack costs nothing and needs no email: probiex.gumroad.com/l/free-claude-prompts.

If your worry is cash this quarter, start with the calculators. Each one exists to replace a sentence you should not trust, like "we have plenty of runway."

Everything is on one page at probiex.gumroad.com, with the research notes in place before the buy button on every product, so you can check my homework before you pay for anything. Code LAUNCH20 takes 20% off any paid product while the launch lasts.

FAQ

Are these courses or templates? Systems. Spec'd databases, checklists, and workbooks you copy into your own stack. Most of them you are running the same day you buy.

What if one is not for me? Every product page shows the complete contents before you buy, so you know exactly what lands after checkout.

Last updated October 2026 · Probiex

Day 7 decides most of your churn

pr0biex — Fri, 16 Oct 2026 14:54:22 +0000

At 9am on Tuesday, 214 people who signed up in the last 30 days opened your app. By Friday, 61 of them had not come back. Nobody on your team noticed, because those 61 never appear in your analytics as anything more than a quiet absence.

The useful part is that you already know who those 61 are. A user who tried the export twice in their first week is not lost. They are warming up. Time-based emails treat everyone the same. Behaviour-triggered ones do not.

Seven days is enough to see it. After day one, almost everyone who will ever pay you has already made the decision. The sequence below is built around triggers, not the calendar.

Day 0 sends the welcome and one action. Day 1 watches what people actually do. Day 2 nudges the quiet majority with a case study, not a discount. Day 4 reacts to behaviour: those who hit the aha moment get the next step at once, while the rest get a short note from the founder. Day 7 sends the final email, and it asks for permission to close the account.

The mistake founders make is treating those seven days as a countdown. They are a detection window. The email is only the last resort. The signal you are looking for already happened on day one, in whatever someone clicked, skipped, or abandoned.

Numbers worth copying. Teams that run this well measure the aha action, and anything under 20% activating within a week means nothing else you build matters. The final email recovers 5 to 15% of the dead accounts, and most of them stay because you asked politely, instead of assuming they were gone.

Before the email fires, your activation checklist does the heavy lifting. Count the steps between signup and the aha moment, and cut everything after the first screen. After day seven, a fifteen-minute review keeps the numbers honest.

Cancelled accounts are not failures. They are the most honest data you will get. Ask one question about why, offer one targeted save, and never guilt-trip them back.

If you want the full sequence built out, with the trigger logic and the weekly review, it is here: https://probiex.gumroad.com/l/silent-churn-rescue-kit

FAQ

What counts as activated? The one action that shows a user gets your value, defined in a single sentence before you plan any email. If you cannot name it, that is the first thing to fix.

Should I discount to win back the quiet ones? This system does not use discounts before day 7, because the goal is activation, not a second conversion push. Coupons work after someone has tried, not instead of finishing.

Last updated October 2026 · Probiex

The Landing Page Math Most Founders Skip

pr0biex — Wed, 07 Oct 2026 19:09:00 +0000

A SaaS founder I know paid $4,200 for a landing page rewrite. Six weeks later, signups had moved from 1.1% to 1.4%.

She felt good about it. She never asked the smaller question first.

Here is the arithmetic nobody runs.

Take 1,000 monthly visitors. At 1% conversion that is 10 signups. At 1.5% it is 15. Five more people. If each pays $30 a month and stays a year, that is 5 x $30 x 12 = $1,800 in added revenue. From a headline.

The part people miss: that lift is not one-time. It applies every month the page runs. Over a year, 1,000 visitors a month at the higher rate is roughly $21,600 in cumulative signup value from a one-and-a-half point change.

So the real question is not "can I afford a copywriter." It is "what is one point of conversion worth to me, and how cheaply can I move it."

Most founders never multiply this out. They either pay thousands for an agency, or they write copy in twenty minutes and ship it untested. Both are guesses wearing different price tags.

The calmer frame: your page is a machine. Headline, subhead, CTA. Each part either moves the percentage or it does not. You do not need a $4,000 budget to test a headline. You need a stack of decent starting points and an afternoon.

That is the idea behind the SaaS Founder Copy Vault (https://probiex.gumroad.com/l/ylpacf): field-tested headlines, CTAs, and email snippets you adapt yourself. Not agency work, not a course. Twelve dollars.

Run your own number first. Then decide if it is worth less than a single signup.

100 Claude Prompts for SaaS Founders

pr0biex — Tue, 06 Oct 2026 05:07:00 +0000

The 100 prompts behind every founder task in my SaaS workflow

I kept a running list of the prompts that reliably got Claude to produce usable output. After a year of iterating, it was 100. This is the full system:

Customer Research & Validation (20)
Copy & Conversion (20)
Launch & Marketing (20)
Growth & Analytics (20)
Social & Build in Public (20)

Each prompt has the exact context fields to paste in and the output format to request. No "act as a helpful assistant" filler.

https://probiex.gumroad.com/l/rztiv

I audited 40 pages of AI-generated copy. The worst ones all made the same mistake.

pr0biex — Mon, 05 Oct 2026 07:26:39 +0000

The first page fooled me. Clean design, confident headline, a market size statistic up top. I only caught it on my second pass, when I tried to quote one sentence to a colleague and realized I couldn't remember what it claimed.

That's the thing about slop that most people get wrong. It's not typos, and it's not robotic phrasing. It's unfalsifiable structure. Every sentence sounds like a claim, but no sentence can be checked. You could swap any two paragraphs and nothing would change, because nothing in them refers to anything specific.

Once you see that, you see it everywhere. Here's what my audits surfaced.

First surprise: the worst offenders were not obvious spam sites. They were polished landing pages, onboarding docs, and product descriptions with careful typography. Confidence is a costume. The typography was doing the persuading, not the sentences.

Second surprise: the same phrases recycle across completely different products. "Seamless experience." "Unlock your potential." "Built for scale." When three unrelated products describe three unrelated things with the identical phrase, that phrase is carrying zero information. It's noise wearing a suit.

Third surprise: humans write slop too. AI did not invent vague writing; it just made vagueness free. A human at least pays for slop with time. A model pays nothing, so it ships infinitely more of it. That changes the attack surface. Ten years ago you reviewed your own drafts. Now you have to review drafts that are technically yours but were effectively written by probability.

So the audit questions I landed on are simple. Can I point to the specific thing this sentence refers to? Could this sentence survive if I deleted the product name? Does it make a claim I could, in principle, verify? If the answer is no three times in a row, the page is slop, no matter how nice the font is.

I collected these into a short checklist called The AI-Slop Audit after a few people asked for my exact process. It lives here: https://probiex.gumroad.com/l/euyxrc

If you audit one page this week using those three questions, you'll probably want to audit everything else you own.

Your Follow-Up Cadence Is Not the Problem

pr0biex — Mon, 05 Oct 2026 07:04:00 +0000

Last year I watched a freelance designer send 47 follow-up emails over 61 days. Polite ones. Scheduled ones. One opened with "just bumping this to the top of your inbox." The client finally paid, apologized, and then mentioned their invoices had never listed a due date. "Net 30" was sitting there in the fine print, apparently decorative.

That's the part nobody says out loud. Late payment barely starts with the invoice. It starts with what you wrote, or didn't, before the work began.

The advice you'll hear in every thread is some mix of: follow up faster, stay firm but friendly, charge a late fee. It all assumes the client is forgetful and you need better reminders. In my experience, most late payers aren't forgetful. They're running on the terms you gave them, and you gave them a lot of slack.

Three things that moved our numbers more than any follow-up template:

A specific date, not net 30. "Due October 14" beats "net 30" every time because it forces both sides to do the math. Vague terms invite vague payment.
A late fee agreed to up front, not sprung later. A signed clause you rarely invoke is still worth having. It moves you from chaser to contract holder the moment a conversation gets awkward.
A kill switch. A written point where you pause further work until the balance clears. Freelancers avoid this because it feels aggressive. Ten years in, I've seen it do the opposite: clients respect the boundary, and you stop funding their cash-flow problem with your labor.

Notice none of these involve sending more emails. Follow-ups aren't the lever. Terms are. Every friendly bump you send without tightening the underlying terms just trains the client that your deadlines are suggestions with feelings attached.

If you want the exact clauses, invoice copy, and pause-work scripts we use for this, The Late-Payment Playbook lays them out: https://probiex.gumroad.com/l/vqblnp

Building a 90-Day LinkedIn Content Habit (Without Burning Out)

pr0biex — Mon, 05 Oct 2026 05:09:02 +0000

You log onto LinkedIn, see a few polished posts from other developers, and wonder how they’re always sharing practical ideas. The difference isn’t their job title or networks — it’s structure.

Let’s break it down. Unstructured posting often fizzles out because “share more” is too vague. A repeatable approach rooted in small steps helps you avoid blank-page syndrome and actually build an audience over time.

Step 1: Create a 3-Topic List

Why: When you niche down, you start to attract relevant conversations. For example, topics like “TypeScript tips,” “career pivots,” and “code review strategies” are specific but wide enough for 90 days of insights.

Step 2: Batch-Capture Experiences

Every time you debug an issue or help a teammate, jot down the scenario and lesson in a note app. These micro-stories will feed your posts, making them more real than generic tips.

Step 3: Schedule 2 Blocks a Week

Choose two 30-minute windows where all you do is shape a post. In the first, outline bullet points from your micro-stories. In the second, clean up and post.

Step 4: Start Replies, Not Monologues

Why: Posts that invite comments — like “What tool do you wish more people knew about?” — are easier entry points than fully polished essays. You’ll spot what resonates and gradually find your voice.

Want a ready-to-follow 90-day guide with prompts and a tracking sheet? 90-Day LinkedIn Content Playbook lays out daily steps you can reuse and tweak for your style. Stick to these basics, and LinkedIn posting becomes less about chasing trends and more about sharing your actual experience.

10 Free Claude Prompts for SaaS Founders

pr0biex — Mon, 05 Oct 2026 05:07:00 +0000

I packaged my 10 most-used Claude prompts as a free PDF

Every week I use the same 10 prompts to research customers, write launch copy, and audit growth. I cleaned them up (fill-in fields, output format instructions) and put them in a free PDF.

What’s inside

3 customer-research prompts that actually return real verbatim quotes
3 launch copy prompts (landing page, launch email, changelog)
2 analytics prompts for funnel leak checks
2 build-in-public prompts that don’t sound like a bot

Grab it here (free, $0): https://probiex.gumroad.com/l/efziwa

If you want the full 100-prompt pack, it’s linked on the same page.

I Checked 40 Sites for AI Search Visibility. They All Made the Same Mistake.

pr0biex — Sun, 04 Oct 2026 20:40:44 +0000

Last month I looked at how 40 small SaaS sites showed up when someone asked ChatGPT or Perplexity a question their product answers directly. 34 of them ranked fine on Google. Barely any of them got cited by an AI assistant.

Here is the uncomfortable part: so what if you rank on Google?

When a person asks an AI model "what is the best tool for X," the model does not read your page top to bottom. It pulls short passages that look definitive, well sourced, and internally consistent with what it already knows about your brand. If your content is written for a human skimming an article, the model usually skips it.

What most people do

Publish long blog posts optimized for one keyword.
Stuff product features into a homepage pitch.
Hope that backlinks will carry them into AI answers.

What actually works

Answer one specific question per section, in plain language, in the first two sentences.
Use clear headings that mirror real questions people ask.
Keep your pricing, claims, and definitions identical across your site and your public profiles. Models cross-check for consistency, and contradictions quietly disqualify you.
Add structured data (FAQ, product schema) so machines parse you without guessing.

The numbers from that same audit back this up. Pages with a direct answer in the opening lines of a section were cited roughly 3x more often than pages with narrative introductions. Sites with matching details across their homepage, LinkedIn, and GitHub appeared in AI answers 2.4x more often than sites with drifting claims.

None of this is about tricking the model. It is about removing ambiguity. The model is not unsmart; it is unsure. Every vague sentence gives it a reason to quote someone else instead.

Think of it like documentation. Sloppy docs get read by nobody. Precise docs get quoted constantly.

The good news: this is fixable in an afternoon. Go through your three most important pages, find every spot where a paragraph takes two sentences to say what could be said in one, and tighten it. Then check whether your product description on your site matches what your social profiles say.

If you want the full checklist and the exact operating habit I used to audit those 40 sites, that is essentially what the GEO Operations System packages up. It is $15, and it lives at https://probiex.gumroad.com/l/llftbq

Run the audience through Google first. Then give the AI a reason to cite you too.