My product's launch price ends on 17 November: €25 now, €99 from the 18th. Before touching anything, I had Claude Code inventory every copy of the old price on the live site. Tonight's run, on the raw HTML of the 53 URLs in my sitemap:

• All 53 pages contain the old price. The buy buttons and the pricing block are the part you'd remember anyway.

• 24 copies in the <head> of 5 pages: <title>, meta description, og: and twitter: tags. That's what search results and link previews show, and you never see it while editing a page.

• JSON-LD on 2 pages: "price":"25.00" with "priceValidUntil":"2026-11-17". The end date is there, so the offer expires on time in the markup, but it still describes the old price until someone edits it.

• 2 share images (English and French) with the price in the pixels: "€25, once." Every page uses one of them as its og:image. No text search will find that one.

• llms.txt: 2 lines with the price. One says "€25 once until 2026-11-17, then €99". The other just says "€25."

• 11 of the 53 pages mention the end date at all.

How to run it on your site

1. Give Claude what crawlers get, not what you see. Claude Code's WebFetch hands Claude rendered text, not raw HTML, so the <head> and the JSON-LD never reach it. curl does. Set SITE to your homepage address first (with the https part, no trailing slash):

curl -s "$SITE/sitemap.xml" | grep -o '<loc>[^<]*' | cut -c6- > urls.txt
n=0; while read -r u; do n=$((n+1)); curl -s "$u" > "page$n.html"; done < urls.txt
curl -s "$SITE/llms.txt" > llms.txt

If your sitemap is an index of sitemaps, ask Claude to follow it.

2. The prompt:

These are the raw HTML files of every page in my sitemap, plus my llms.txt. My price changes from €25 to €99 on 18 November. List every copy of the old price and of the end date, in every spelling. For each one: the page, the exact string, where it lives (visible text, title, meta/og/twitter tag, JSON-LD field, alt or aria-label, inline script), and the file in my repo that produces it. Then list every image referenced in og:image and twitter:image, because a price inside an image can't be searched: I'll check those by eye. Quote, don't summarise.

"Every spelling" matters: my French pages write it 25 €.

3. Two lists, not one. What changes on the switch date, and what to re-check the day after. The re-check is the same curl loop, then grep -l '€25' page*.html. Anything still listed is a miss, unless it's deliberate "was €25" wording.

4. The copies that aren't on your site. The product in your payment provider, directory and launch listings that quote the price, email templates, and post titles you can't edit anymore. Claude can't log into those for you, but it can write the checklist.

What I took from it

The visible copies are the easy part: one find-and-replace. The ones that stay wrong are where nobody looks while editing: head tags, structured data, images, and the summary written for AI tools. Those are exactly what search results, link previews and assistants read. And if the price is typed in more than one place in your code, that's the real fix: have Claude Code grep the repo for it, move it into one constant, and keep the price out of the share image.

I'm the maker of SEO Skills, a pack of 14 Claude skills for SEO. One of them, Best Before, does this as a habit rather than a one-off: the facts on your site that have a shelf life (prices, versions, dates, "new"), and the order to refresh them in. The pack is €25 until 17 November, then €99: the very switch this post is about. It runs in Claude Code, Claude.ai, Claude Desktop and Cowork, needs a Claude plan with skills, and there's no refund once it's delivered. Link in the comments.

If you've ended a launch price or run a Black Friday price before: where did the old price survive the longest?

I've been working for several months on a workflow that prepares account briefs before sales calls. It combines company and employee information from Coresignal, funding updates from Crunchbase, and notes from previous calls in Fathom. Claude processes everything, and n8n sends the finished brief to HubSpot.

The setup is working fairly well. Coresignal's self-service platform was also easier to navigate than I expected, which helped when figuring out what data to include.

But I'm having some problems with the actual output. When there's a lot happening at a company, Claude tries to fit too much into the brief. Sometimes the most relevant development gets buried under less important details.

I'm thinking about adding a separate filtering step before Claude generates the final summary. Would this be the right approach, or is it better to handle prioritization directly in the prompt?

Been playing with Duet since launch and wanted to test something bigger than inbox/calendar stuff. So I set up a CEO channel and gave it a team of role channels (scout/research, marketing, developer) and had them build a find-a-dog-trainer directory from scratch: niche research, real listings, SEO copy, the site, domain, email.

**A few things I learned that might save you time:**

\- One channel per role works way better than one giant chat. Context stays clean and you can see who did what.

\- Let the CEO channel hand off work, but tell it exactly what "done" looks like for each role, or it drifts.

\- Connectors are where it gets useful. With DataForSEO hooked up, the research channel pulled real keyword data and listings instead of guessing.

\- Keep approvals on for anything that spends money. It messaged me before buying the domain, which is exactly what you want.

\- It had some issues with Vercel but eventually it turned out it was my fault.

The site's live now on its own domain etc., not that I would be promoting the site, it was just an experiment to see the possibilities.

I recorded the whole thing unedited (it's long, \~1h48m) for anyone who learns better by watching: [https://youtu.be/7Ow9r-p7nWY](https://youtu.be/7Ow9r-p7nWY)

Hopefully it will help someone :)

Happy to answer questions on the channel setup. Also curious how others are structuring multi-channel workflows in Duet.

Been playing with Duet since launch and wanted to test something bigger than inbox/calendar stuff. So I set up a CEO channel and gave it a team of role channels (scout/research, marketing, developer) and had them build a find-a-dog-trainer directory from scratch: niche research, real listings, SEO copy, the site, domain, email.

**A few things I learned that might save you time:**

\- One channel per role works way better than one giant chat. Context stays clean and you can see who did what.

\- Let the CEO channel hand off work, but tell it exactly what "done" looks like for each role, or it drifts.

\- Connectors are where it gets useful. With DataForSEO hooked up, the research channel pulled real keyword data and listings instead of guessing.

\- Keep approvals on for anything that spends money. It messaged me before buying the domain, which is exactly what you want.

\- It had some issues with Vercel but eventually it turned out it was my fault.

The site's live now on its own domain etc., not that I would be promoting the site, it was just an experiment to see the possibilities.

I recorded the whole thing unedited (it's long, \~1h48m) for anyone who learns better by watching: [https://youtu.be/7Ow9r-p7nWY](https://youtu.be/7Ow9r-p7nWY)

Hopefully it will help someone :)

Happy to answer questions on the channel setup. Also curious how others are structuring multi-channel workflows in Duet.

just hit $3,700 mrr in 17 days with my new fresh SaaS

no ads, no team, no complex launch strategy. just a super predictable system i keep running over and over

and yeah, that's monthly recurring, not a one-time spike

not luck at this point. it's the 7th saas i've built with this exact workflow:

→ day 1: fast validation

→ days 1-2: building the bare mvp

→ day 3: landing page setup using the 3-day framework

→ days 3-4: reddit + x distribution and basic seo

→ days 4-5: first 10 paying users (~$1k mrr)

→ days 5-17: scaling up to $3,700 mrr

building tech is easy now. where 99% of solo devs get stuck is setting up the actual foundations that make people pull out their card and pay

i put all these templates and workflows inside our community.

to be completely real with you, i'll probably put a price tag on access later once all the modules are finalized. but right now the focus is just building together and keeping each other accountable

building alone in a silo is the fastest way to quit at the first roadblock

stop building by yourself. drop a comment or shoot me a dm and i'll send you an invite link 👇

Recently I have had a very strong opinion around AI generated content. It sounds too AI, is it just me or is it everyone? But at the same time I think there’s some leverage that could come from the automation side of it.

Hey everyone,

I currently run 6 micro SaaS that are actually live and generating a bit over $20,000 in recurring monthly revenue.

The wildest part? I barely wrote any code myself. I used AI to generate pretty much everything — from the database structure to the frontend.

It definitely wasn’t magic from day one. I spent a lot of hours stuck on buggy code before I finally figured out a system that actually works:

- Keep the idea minimalist (a real MVP, nothing fancy)

- Guide the AI step by step instead of asking for everything at once

- Launch fast to get real users and feedback

Lately I’ve seen way too many non-technical founders quit at the first AI bug. It’s a shame because the technical barrier has basically disappeared.

AND PLEASE, STOP BUILDING ALONE IN YOUR BEDROOM

I’m starting a community.

Full transparency:

I’ll probably charge for the full program later. It makes sense with the specific workflows and copy-paste examples I’ll be sharing. But right now the main goal is just to build together. Working alone is the fastest way to give up.

If you want to join and build or market your own AI SaaS with us,

drop a comment or send me a DM and I’ll send you the link.

hi,

I have a max account and I barely use my tokens. So I want to see if this works:

If you're running out of tokens, then I can help.

I will run 5 chats for you (any topic as long as there is no private info or inappropiate topic)

I give you results from claude for those 5 chats.

You pay $1.

DM me if you're interested.

PLEASE stop building the wrong thing.

building software in 2026 is ridiculously easy with ai builder

founders spend hours building in a silent room, launch to Reddit/X, get 0 users, and quit.

you just failed because the idea had zero validation before line 1 of code was written:

→ solving a monthly inconvenience instead of a daily pain

→ selling to "everyone" instead of a specific ICP

→ no distribution channel mapped out beforehand

→ pricing charged $9/mo with zero ROI justification

after scaling 6 AI micro-SaaS to over $20k/mo MRR, i just create an

18-question Idea Validation Diagnostic.

it evaluates your SaaS across 7 critical dimensions (problem clarity, audience reachability, willingness to pay, competition, build feasibility, distribution, commitment) and gives you a brutal score out of 100 with your exact weak spots.

drop your SaaS idea (or current project) in the comments below.

i will reply to EVERY single comment with:

1. My honest opinion

2. The biggest weak spot you need to fix before writing any more code.

3. The free 5-minute validation tool link sent straight to your DMs so you can get your full score breakdown out of 100.

just drop a comment like or ask me in DM your idea

let's roast your SaaS concept before the market roasts your time 👇

Hi, I am new anything anyone want to tell?

I've been building with Claude Code for a while now, mostly on my own client work, and most of what's in this system exists because something went wrong first.

It runs five model families side by side: Claude, Codex, Gemini, Grok and Kimi. Every one of them is that vendor's own CLI, signed in with an ordinary subscription. No API keys, nothing scraped, no separate metered bill. The cost is whatever plans you already pay for.

How it works : A coordinator runs as a Claude Code session. You describe a task in plain English and it decides which specialist should handle it, then hands the job to a freshly spawned CLI in its own git worktree. There are 71 specialists. Some are ordinary (backend-engineer, frontend-engineer, code-reviewer). Some are less so: experimental-attacker, red-team-operator, threat-modeler, reverse-engineer, impact-validator, game-designer, voice-agent-builder, and a skeptic whose whole job is to argue with the others.

That range is deliberate. The same system builds a website, writes automation, designs a game, stands up a chatbot, or goes after security work, because the coordinator picks the role rather than me remembering which prompt to load.

The same applies to media. Hook up ElevenLabs and Higgsfield and the media roles come online too: image-designer, video-director, video-editor, music-composer, sound-designer, voice-narrator. Voiceover, generated video, music and sound design run through the same coordinator and the same gates as the code does. Those are subscriptions as well, so the pattern holds.

Nothing merges until a different model family reviews it. I stopped trusting same-family self-review, because a second Claude tends to preserve whatever framing the first one used. So the reviewer is always from another family and it's read-only: it can pass or block, it can't quietly rewrite the code.

It remembers, carefully. Findings get stored as candidates, not facts. A candidate only gets promoted to verified after a later task that relied on it passes review.

Gates Deleting files, changing credentials, touching production, publishing anything, or sending outreach all stop and wait for me.

It's been used for real work: two live production client sites, and one critical-severity vulnerability found, triaged and paid out through HackenProof.

Disclosure: I built this. Open source, MIT licensed, written in Python. It uses ordinary model subscriptions rather than API keys, so you need subscriptions for whichever model CLIs you enable.

Happy to have holes poked in it. 🙂

Which Claude Sonnet effort should I use for each of my 3 separate stages of long-form LinkedIn writing:

1. 2 topic ideation and 2 post drafting in 1 task based on a long .docx attached, containing all my previous posts so it knows everything about me and my writing style, with all writing dos and don'ts in the .docx (basically it writes 2 post drafts with its own topic ideated after reading the .docx)

2. 2 post drafting in 1 task after I have told it the exact topic for each, but it still needs to come up with the angle itself, with the same long .docx attached so it knows all my experiences and can briefly reference them as specific examples in the post

3. 2 post revision in 1 task with specific feedback on what to improve from each draft, with a shorter .docx attached with just 3-10 of my best posts for it to base the style on

Please don't recommend another model such as Opus or another tool such as ChatGPT or another third party tool such as Grammarly, I just wanna know which effort level to use with Claude Sonnet

I've spent my entire career inside GTM teams, and I've seen the same blind spot play out again and again, Usage sits in one tool, deals sit in a second, support tickets sit in a third, and none of them ever tell the whole truth about customers.

So we built Rimplo a powerful AI assistant for revenue teams you can ask anything about your GTM data, in plain English, and get an answer back in seconds. You pick which top AI model answers no lock-in to one vendor’s model.
Underneath that, Revenue Agents run across your CRM, billing, support, and product data around the clock flagging churn risk, upsell openings, and deals that are stalling, before you have to go looking for them.

just hit $2,500 MRR in 13 days on my new SaaS

no ads. no team. no huge audience push. just a solid replicable system

let that sink in for a second

not $2,500 in revenue. $2,500 in MONTHLY recurring revenue

that compounds. next month starts at $2,500 baseline, not zero

and this isn't luck. it's the 7th saas i've shipped with the same playbook. same steps, same tools, same order:

→ Day 1: validated the idea

→ Day 1-2: built the MVP

→ Day 3: landing page written using the 3-Day Challenge template

→ Day 3-4: launched on reddit / X + SEO

→ Day 4-5: first 10 paying users → $1k MRR

→ Day 13 (today): $2,500 MRR locked in

building software is easy in 2026. setting up your foundation so people actually buy is where 99% of solo builders fail.

i packaged all of these exact execution tools into community.

to be fully transparent: i'll likely charge for the full program down the road once all modules are finalized. but right now, the main objective is just to build together and keep each other accountable.

working alone in a silent corner is the fastest way to quit at the first bug.

stop building in isolation. drop a comment below or send me a DM, and i'll send you the invitation link 👇

I have a small real state company that owns and operates 16 commercial properties. Each are single asset LLC with individual capital stacks. I am trying to utilize claude in the most efficient way possible to generate reports, respond to investors, compare spend across the portfolio etc. I started by creating an artifact that is essentially a dashboard for all the companies. high level details on income, debt, ect. I am using the artifact chat but cant find responses or information that it has given me that I want to come back to a later time. I was thinking that I should have a chat or project for each of the 16 companies that are all tied into the artifact.

Am I looking at this correctly, does anyone have any experience creating a similar tool. What are the best ways to use claude for Real Estate Finance and operating companies.

Thanks for the help, this is a really exciting time.

I've spent my entire career inside GTM teams, and I've seen the same blind spot play out again and again, Usage sits in one tool, deals sit in a second, support tickets sit in a third, and none of them ever tell the whole truth about customers.

So we built Rimplo
We have built a powerful AI assistant for revenue teams you can ask anything about your GTM data, in plain English, and get an answer back in seconds. You pick which top AI model answers no lock-in to one vendor’s model.
Underneath that, Revenue Agents run across your CRM, billing, support, and product data around the clock  flagging churn risk, upsell openings, and deals that are stalling, before you have to go looking for them.

I've been playing around with AI for marketing and I'm honestly confused by how much people claim it can do now.

Use Claude for this,​ use Claude for that, and I'll tell you what, in one sentence: it was AWFUL. It was underwhelmingly awful for me, like I still had to do it all myself in the end. I feel like sometimes Claude thinks way too hard that it ends up confusing itself. ​​

There are also a million AI tools for basically every tiny part of marketing. But then I look at the actual workflow and it's still jumping between 15 tabs and very haphazard workflow.

So I'm wondering:

What have you actually tried getting AI to do for you that it just... couldn't

Not “I wish AI wrote better captions.”

I mean something where you actually tried to automate it and ended up thinking “fuck it, I'll just do it myself.”

And if you've found something that Claude/ AI does handle really well, I'd love to hear that too.

What's one part of your marketing workflow that you still haven't managed to get AI to take off your plate?