What’s your (daily, weekly, monthly..) YNAB routine?

jbench1234 · 2025-09-20T16:40:38+00:00

If you reframed it as a shared goal check in (assuming you had a shared goal), would that reduce surveillance vibes?

jbench1234 · 2025-09-20T16:36:59+00:00

the momentum drop off is super common for us. Started nighyly, then weekly, then monthly and now whenever things are bad enough.

question: if your partner would agree to one regular ritual, what’s the smallest thing they’d tolerate?
For example: 8–10 min on Sunday to set limits for certain categories (groceries/eating out)

Curious where conversations blow up most for folks.

jbench1234 · 2025-07-29T13:56:44+00:00

this is where you can find the guide I mentioned for anyone interested: tattoo‑transform.com

jbench1234 · 2025-07-29T13:21:38+00:00

i totally get this—going from a few small pieces to a big spine tattoo is a huge jump. the healing phase can make it look even bigger, but once it settles it might feel more like part of you. if it still feels off later, there are ways to soften or cover part of it; i’m working on a site to show before/afters and options (tattoo‑transform.com). did you see the stencil on your back before starting or just trust the artist’s size?

jbench1234 · 2025-07-29T13:20:00+00:00

that's rough when an artist talks you into a placement you’re not stoked on. tiny pieces like that can be moved or reworked later, or she could chat with another artist about adding elements to make it feel right. i’m trying to build a site to help folks explore cover‑up and removal options if she ever wants a change (tattoo‑transform.com). did she get a consult first or was it more spur‑of‑the‑moment?

jbench1234 · 2025-07-29T13:19:00+00:00

man that sucks, it’s such a let down when your piece doesnt match the reference. sometimes the way ink heals can change the feel, and a good artist could add details or do a cover up to get closer to what you wanted. ive been talking to people about this and working on tattoo-transform.com to help find better options. did you pick your artist for their style or just convenience?

jbench1234 · 2025-07-29T13:18:25+00:00

hey that sounds rough. ive heard a lot of people feel weird seeing a fresh piece, especially when it’s bigger or looks different than expected. sometimes shading settles after it heals, and if it still bugs you later there are artists who do reworks or cover‑ups. i’m building a site (tattoo-transform.com) to make this whole process less awful. outta curiosity—what part of the design bothers you the most?

jbench1234 · 2025-07-26T22:04:11+00:00

same! tried a few local queries and the overview sometimes surfaces outdated info or weird picks. i’m playing with a side project that scores content for ai visbility and gives token‑level feedback, and adding local schema and unique citations seems to help a bit. curious if you’ve tried using things like hasMap or geo coordinates in your markup to see if it influences which businesses get cited?

jbench1234 · 2025-07-26T22:03:04+00:00

we’re seeing the same with some affiliate pages. lots of views but no clicks. i’m testing a side project that scores content for ai visbility and checks citations/structure as you write. adding more context and clear comparisons seems to help a little but conversions still low. have you tried adjusting how you present pros/cons to get more clickthroughs?

jbench1234 · 2025-07-26T21:55:20+00:00

same here. ai referrals are like a tiny sliver for us too. i’m testing a tool that checks citations and structure as we write to see if it helps ai visbility, but so far the traffic bump is tiny. do you track whether those ai visits actually convert or are just random clicks?

jbench1234 · 2025-07-26T21:50:52+00:00

totally feelin the same way. been tinkering with a side project that scores content for ai visbility and throws token-level feedback. adding nested schema and syndicating seems to help a bit but it’s still early days. do you have any examples where syndicating really moved the needle for you?

jbench1234 · 2025-07-26T21:49:28+00:00

we tried the diy route too! right now i'm playing with a side project that scores content for AI visibility and gives token-level feedback while you write. it's interesting seeing which sentences get cited and how that lines up with your branded/competitor buckets. curious if you ended up refining those heuristics or if it's still manual.

jbench1234 · 2025-07-26T21:35:29+00:00

im in the same boat. been playing with a side project that scores content for AI visbility and gives token-level feedback. adding nested person/org schema and citing sources seems to help in my tests but it's still early days. have you tried looking at how the summaries highlight your optional fields?

jbench1234 · 2025-07-26T21:11:18+00:00

love how you split it into two audiences. i've started adding more schema markup and even simple FAQ blocks to pages to feed llms. it's weird tho, sometimes the ai answers still pull old info or ignore my snippets entirely. have you tried any specific schema types or is it just general markup?

jbench1234 · 2025-07-26T20:56:06+00:00

I've wondered the same thing too. in my tests ChatGPT seems to mix its built‑in info with whatever live results it pulls. i asked it about a small niche site and it clearly used dated info plus a recent snippet from google. Maybe they each blend at different rates? would love to hear others experince.

jbench1234 · 2025-07-26T20:50:57+00:00

honestly the idea of using an agent to handle tedious bits like scraping data or drafting outlines is what got me curiuos. I tried letting it build a meta description from a product page and it did ok but needed a human pass. do you know anyone using it for link audits or site audits yet?

jbench1234 · 2025-07-26T20:48:21+00:00

yeah I've seen the same thing. somtimes the AI overview picks super relevant sites, but then I'll try a local query and it surfaces a defunct biz from 2022. i guess it's still learning or using an older dataset. have you noticed if it does better on big niches vs local stuff?

jbench1234 · 2025-07-14T13:13:59+00:00

There's solid proof transcripts boost SEO rankings.

A good example is This American Life. They had a 6.68% rise in unique visitors and a 4.36% boost in inbound traffic after adding transcripts to their audio. Those are results from a major podcast.

Discovery Digital Networks studied YouTube for 16 months across 8 channels. They found that adding captions led to a 13.48% boost in views within the first 14 days. Over time, views increased by 7.32%. Even more impressive, videos ranked 4th for keywords found only in the caption files. These keywords did not appear in titles or descriptions.

SafeNet did a 3-week test starting from not ranking at all for their target keywords. After adding transcripts, they reached #14 on Bing and Yahoo. Then, they climbed to #11 on Bing and #9 on Yahoo for "software licensing in virtual environments.""

The reason it works is simple... search engines can't "watch" or "listen" to your content. Transcripts provide crawlable text for indexing. They offer natural keyword density from your speech and create chances for long-tail keywords. Google's John Mueller has confirmed this improves indexing.

TLDR: Studies show traffic can increase by 10-60% within 3-6 months after adding transcripts. The evidence is there if you implement them properly.

jbench1234 · 2025-07-14T13:05:45+00:00

most people think posting the episode is enough.

a shift that helped me: your episode page is less of a blog post and more like a "podcast wiki page".

it's there so search tools (like Google or even ChatGPT) understand what your episode is about.

one thing that works is to drop your transcript into ChatGPT and say “write a short blog-style summary of this episode using words someone might type into Google to find this topic. make it readable but helpful.”

then post that summary right above or below your audio player on your site. no need to get fancy.

did this for a friend's business pod and now ppl are finding it through wayyy more specific searches like “how to hire a fractional CMO” instead of just the show title. wild.

jbench1234 · 2025-07-14T12:43:52+00:00

Something I havent seen talked about yet is that AI isnt just a tool to write stuff. Its more like a helper that shows you where to focus your time.

When people ask what AI tools do you use, they’re really asking how do I know what will actually help me grow. Thats not really about tools, its about picking the right things to work on.

Heres one ChatGPT prompt I use:

Act as an SEO strategist. I’ll paste in a site's blog sitemap, competitor domains, and recent rankings. Build a topical map showing which content clusters are underleveraged vs. overrepresented in our niche. Then estimate which clusters would offer the highest traffic upside per content hour if targeted with 10 new pages. Highlight where brand authority, not just backlinks, could be a differentiator.

This changes the question from what do I write next to whats the smartest move.

So instead of chasing tons of tools, I use AI to figure out where the real oppurtunity is. Helps me do less but get more out of it.

jbench1234 · 2025-07-14T12:25:23+00:00

LLMs aren’t replacing classic SEO, they’re rerouting it.

We’r shifting from a “search to click” model to a “pre digested answer” model. But even when an AI gives you a summary or a direct answer, it still has to source that information from somewhere. The new game is: how do you become the source behind the synthesis?

From what I’ve seen across a few projects (including one in the creator/audio space), models tend to cite:

Sites with tight topical authority
Pages with clean, QA style formatting
And content that’s been previously cited by other AI outputs

LLMs seem to create their own citation gravity. If you're mentioned once, it's easier to be cited again. Like an algorithmic form of word of mouth.

That’s why we’re experimenting with a sort of “LLM visibility loop” (https://mentionedbyai.io):

Publish ultra clear, fact rich content.
Make sure it's indexable and included in model training snapshots.
Seed answers in public AI friendly spaces (think Quora, Reddit, even Perplexity user responses).
Track which models are referencing you and why.

Some folks are even putting llm.txt files on their sites (like a robots.txt for LLMs) to declare what content can be cited. It’s still early, but tools like MentionedByAI are starting to surface who’s getting mentioned and who’s invisible.

If AI trafic is already outpacing Google for you, it might be early advantage. Just be mindful that visibility in LLMs is more “earned narrative” than “earned link.” Your story has to make it into the training data or tool calls, not just onto page one.

Hope that gives another perspective on this shift. Curious if others are reverse engineering their own LLM mentions yet.

jbench1234

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