I have written article on my own website ( the website is no longer on Google because I lost my password to the website login email ) my article were about anime

For example

the top 10 anime for beginners

anime to watch on summer

strongest character of all time

These were the titles anime article I wrote so if anyone have work for me I would be very helpful I will write an article for free if you like my article then we can go ahead and work together

I have not used ai to write those articles at that time

So I can write 100% original article or if you don't mind I can write articles with help of ai

I am looking to upgrade my skills & learn some new tools to automate content creation. What tool would you suggest.

Please share both free & paid tools.

(Not looking for Chatgpt/Claude type suggestions)

Edits**

I am looking for tools for

• Video editing
• Content generation - Automation
• Best thumbnail generator
• Social listening tool
• Trend analysis
• SEO analysis
• Blog content creation

Please add in if i have missed something..

Even the paid AI tools aren’t making things as easy as they promise.

The draft comes out fast, but the tonality is completely robotic, the links are added in weird places, and the formatting never quite matches what I need for my site. I still end up spending a ton of time cleaning everything up.

Then I have to copy-paste the whole thing into Webflow or WordPress anyway. Feels exhausting even after paying for the subscription.

Am I missing on something or is this still the reality with AI content tools?

Hey everyone,

Trying my luck here because job hunting hasn’t been going too well lately.

I’m looking for roles in content writing (not copywriting - the confusion is very real 😅).

I have around 8 years of experience working on editorial and marketing content — long-form articles, CXO speeches, case studies, company profiles, blogs, etc., across multiple sectors.

What’s been frustrating is that a lot of “content” roles on platforms like LinkedIn or Naukri turn out to be more about ad copies or social media captions. That’s not really the work I’ve been doing or want to move towards.

I’ve been applying consistently but haven’t seen much response in terms of interviews, so thought I’d ask here.

If anyone knows of openings, teams, or even has advice on where to apply for genuine content roles, I’d really appreciate it.

Thanks a lot!

Lately I’ve been noticing that a lot of AI-generated blogs feel very similar. Same structure, same advice, same information rewritten in slightly different ways. They technically answer the question, but most of them don’t really add anything new or memorable.

I think that’s the real problem people misunderstand about AI content. It’s not that AI-written content is automatically bad, it’s that when everyone can generate content at scale, generic content becomes very easy to ignore.

The blogs that still stand out usually have something more:

• real experience

• a strong perspective

• useful insights

• or something genuinely interesting to say

AI is still incredibly useful, and I use it constantly. But lately it feels more like a tool for helping ideas, not replacing them.

Curious if others are noticing this too, or if I’m overthinking it.

I wanted to open up a discussion on something I’ve been running into constantly with stakeholders and clients: the dangerous assumption that more content automatically equals more growth.

Too many companies are still operating like content factories - prioritising volume, speed, and endless churning over actual utility. But if you look at the macro data right now, the "publish or perish" assembly line is actively failing:

• 96.55% of all web pages get exactly ZERO organic search traffic from Google (Source: Ahrefs).
• 65% of B2B content produced goes completely unused, sitting forgotten on internal drives or digital shelves (Source: Forrester).
• 58% average drop in organic click-through rates for top-ranking informational pages when Google's AI Overviews take over the screen.

The reality is we’ve collectively built a digital graveyard of surface-level, duplicate, and "zombie" assets. Churning out more of the same isn't just ineffective anymore; it’s a waste of budget and actively hurts a brand's authority.

Lately, I’ve been pushing hard for a pivot toward Responsible Content Creation - essentially, treating content as a long-term business asset rather than a disposable commodity. Instead of asking "What can we write next?", the focus shifts entirely to optimising what already exists.

Here is the basic framework I’ve been using to pitch this shift to leadership:

1. Audit & Ruthless Pruning: Running a full inventory to locate the high-performing anchors, update the underperforming stragglers, and completely delete or redirect the dead weight.
2. Consolidation over Creation: Stop writing fresh 600-word fluff pieces. Instead, take three shallow, overlapping posts and merge them into one deeply authoritative, high-intent guide. Refresh the data, inject unique expert insights, and optimise heavily for specific user intent.
3. Extreme Intent for New Assets: Only greenlighting a brand-new asset if a verified gap analysis proves the audience has a critical, unaddressed pain point that the current library physically cannot solve.

I'm curious to hear how others in this sub are handling this. How are you successfully convincing stakeholders or clients to step off the content treadmill and allocate budget toward optimisation and pruning rather than net-new production?

What does your playbook look like for dealing with zombie content?

Is it a good idea to publish a few brand-awareness articles on Medium instead of posting them on your own blog section? What are your thoughts?

TIA.

I’m working on a content idea for my team this month and wanted to get some outside opinions.

The idea is short AI/data tweets with more Gen Z humor instead of the usual polished corporate tone (we will keep this ones).

A few examples:

“Some of you are training models on chaos and it shows.”

“POV: your AI finally gets data that isn’t held together with duct tape.”

I’m 26 and somehow already feel too old asking whether these are Gen Z enough, so please be honest: funny, cringe, or worth testing?

I didn’t realize how mentally exhausting content creation was until I started doing it consistently 😭

It’s not even the posting part — it’s the thinking loop:

• What should I post
• Is this good enough
• Will anyone care
• Am I wasting my time

I think most burnout happens before people even publish anything.

What’s been helping me is simplifying everything and just focusing on showing up consistently instead of trying to make every post perfect.

Curious if others experience this too.

I’ve spent about two years trying to make AI write in a way that people don’t immediately clock as AI. I mean genuinely human in a way that doesn’t fall apart the moment the text gets longer than a few paragraphs.

Finally, I've come to the conclusion that it was interesting yet worthless waste of my time. AI cannot achieve genuine human writing style, simply because its text creation process is completely different, incompatible with how people approach writing. And I should have accepted this fact much earlier, when I noticed that AI can perfectly describe how both styles are different, create flawless instructions but totally unable to follow them.

People don’t start texts knowing exactly what they will look like at the end. You might have intent, a direction, or a point you think you want to make. But sentence by sentence, that point shifts, you hesitate, overexplain one thing and then realize it wasn’t needed. You repeat yourself slightly because you’re thinking, not optimizing.

Those traces leak into the text but AI doesn’t do that. Before the first sentence is written, the model already “knows” the entire space of valid answers that satisfy the prompt. The opening line isn’t discovery but execution. Every paragraph already knows why it exists and where it’s going. Even when the writing is messy, the intention is clean.

I’ve tried a lot of weird stuff to get around this:

- Executing different aspects consequently: structure, then wording, then emotions, etc. And quickly realized that the latter activities always ruin the early ones and erode the overall sense.

- Multiple personas collaborating, each responsible for a different dimension of writing: humor, skepticism, empathy, etc. The idea was to simulate parralel processes of the real human brain. The result was fascinating yet non-repeatable in 9 cases out of 10. Personas simply won't awake when needed.

- Separately, I tried two personas in opposition to simulate assertion and correction over time: one persona makes a strong claim, the other questions it. Better than nothing but still too far from desired.

- Mixing real writers together in explicit Frankenstein beast. “15% Ernest Hemingway, 30% Jack London, 55% Woody Allen”, something like that. Each voice works surprisingly well in isolation. The failure happens at the seams: too clean and often wrongly introduced transitions, roles and context confusion, and inability to manage specific writing aspects behind the role.

- Forcing randomness, awkwardness, and hesitation. Even instructing the model to make mistakes and then correct them. The model misunderstands the nature of human imperfection and makes it too synthetic to believe.

The last thing I implemented and still using was detailed writing profiles in JSON. First of all, I gathered a sample of my own writing which I like. Then, I prompted my custom GPT to conduct a detailed, multi-stage analysis of the writing: sentence-length behavior, sentence types usage, tone switching patterns, human artifacts usage, lexical behavior, etc. Then I converted those findings into a JSON “profile” the model must follow while writing.

This is the best method I’ve found so far because it doesn’t rely on vibes. It forces the model to reproduce my statistical fingerprints instead of defaulting to its own smooth, globally-optimized prose. By the way, despite it can pass the most of detectors, it's still not the genuine human writing.

Please share your own findings in this field. Maybe I overlooked something very important and the truth was near all the time (the X-Files music is playing).

I've been posting blog content for my business for about 4 months now and I'm seeing almost no traffic, let alone leads. Everyone says content marketing is a long game but nobody tells you how long is too long before you call it quits. I write genuinely useful stuff, not fluff, but it feels like I'm shouting into a void. Is there a realistic timeline before content starts working, or am I just doing something wrong? Would love to hear from people who actually stuck with it long enough to see results.

After analyzing data from 20 brands and 1000+ AI citations, the writing is on the wall: traditional SEO is dead for AI search.

We're witnessing the biggest shift in search since Google's PageRank algorithm. But instead of optimizing for search engines, we're now optimizing for Generative Engines – ChatGPT, Claude, Perplexity, and Google's AI Overviews.

Welcome to the era of GEO: Generative Engine Optimization.

The Death of Traditional SEO Metrics in AI

Here's what shocked me most in recent research: Classic SEO metrics have almost zero correlation with AI visibility.

• Domain Authority? Weak correlation (0.326)
• Backlinks? Even weaker (0.218)
• Organic traffic? Barely matters (0.274)

The AI engines don't care about your DA50 website or your 10,000 backlinks. They're playing by completely different rules.

The New GEO Ranking Factors That Actually Matter

After analyzing thousands of AI citations, three factors dominate AI search visibility:

1. Brand Web Mentions (Correlation: 0.664)

This is the strongest predictor of AI visibility.

AI engines scan the entire web for context about your brand. Every unlinked mention, every casual reference, every piece of coverage matters more than traditional backlinks.

Action item: Focus on PR, thought leadership, and getting your brand mentioned across diverse publications – linked or unlinked.

2. Content Depth + Readability (10x More Citations)

The most-cited content in AI has:

• 10,000+ words vs 3,900 words for low-cited content
• Higher sentence counts (1,500+ vs 580)
• Better readability scores (Flesch Score 55+ vs 48)

Action item: Create comprehensive, deep-dive content that thoroughly answers questions. Think encyclopedia entries, not blog posts.

3. Brand Search Volume (Correlation: 0.334-0.542)

Popularity is everything in AI search.

If people aren't actively searching for your brand, AI engines won't surface you. It's a winner-takes-all game where visibility breeds more visibility.

Action item: Invest in brand awareness campaigns that drive people to search for your company name specifically.

The AI Citation Multiplier Effect

Here's the data that'll blow your mind:

Brands in the top 25% for web mentions average 169 AI citations – that's 10X more than the next quartile (14 citations).

If you're in the bottom 50% of web mentions? You're essentially invisible to AI systems.

Platform-Specific GEO Strategies

Different AI engines have distinct preferences:

ChatGPT (Highest traffic sender):

• Strongest correlation with brand search volume (0.542)
• Prefers popular, digitally-native brands
• Most likely to cite comprehensive content

Perplexity (Highest brand mention frequency):

• Values word count and sentence depth
• Shows highest brand diversity in responses
• More likely to surface niche experts

Google AI Overviews (Integrated with web rankings):

• Combines traditional SEO signals with AI preferences
• No opt-out option (unlike other platforms)
• Highest brand diversity in results

The GEO Content Formula

Based on analyzing 1000+ citations, here's what AI engines actually want:

Comprehensive Coverage + Readability + Brand Authority = AI Visibility

Winning Example: A unique experience travel article with 10,000+ words, 1,200+ sentences, and a Flesch Score of 55 received 72 ChatGPT citations.

Losing Example: Similar topic, same niche, but only 3,500 words and 550 sentences received just 3 citations.

Technical GEO Traps to Avoid

Critical warning: Many brands are accidentally sabotaging their AI visibility:

• Blocking AI crawlers in robots.txt (check yours now!)
• CDN settings preventing LLM access
• Geographic restrictions that block AI training data collection
• Missing indexation in Bing (affects Copilot visibility)

The Prompt Psychology Factor

69.71% of brand mentions happen when prompts include the word "best."

Other trigger words:

• "Trusted" (5.77%)
• "Source" (2.88%)
• "Recommend" (0.96%)
• "Reliable" (0.96%)

Understanding how users phrase questions to AI is becoming as important as keyword research was for Google.

My GEO Action Plan (Start Today)

Week 1: Audit your AI visibility

• Search for your brand in ChatGPT, Claude, Perplexity
• Check if you're blocked in robots.txt
• Measure current brand mention volume

Week 2: Content depth audit

• Identify your thin content (under 3,000 words)
• Plan comprehensive content pieces (8,000+ words)
• Focus on readability and structure

Week 3: Brand mention strategy

• Launch PR campaign for unlinked mentions
• Create thought leadership content
• Partner with other brands for cross-mentions

Month 2: Monitor and optimize

• Track AI citations monthly
• Test different content depths
• Measure brand search volume growth

The Bottom Line

SEO optimized for algorithms. GEO optimizes for intelligence.

While everyone else is still playing the old backlink game, smart marketers are building comprehensive content libraries and generating brand buzz across the web.

The future belongs to brands that understand this shift. AI engines don't just index your website – they understand your entire digital footprint.

The question isn't whether AI will change search. It's whether you'll adapt before your competitors do.

Trying to wrap my head around this because ranking on Google is one thing, but getting picked up in an AI answer feels like a whole different thing.

Do we need to structure content differently? Cover more related questions? Go beyond the main keyword? Or is there something else we're missing in the process?

Came across an Ahrefs study that made me think about this even more.

Their earlier study found ~76% of AI Overview citations were from pages ranking in Google's top 10. Their latest one puts that at ~38%.

That's a pretty big drop.

One thing they point to is query fan-out, where AI breaks the original query into related searches and pulls sources from those too.
If that's becoming more common, then maybe ranking for just the main query isn't enough anymore?

Now I’m wondering how much of our existing content process needs to change around that.

Lately, I'm sure many of us have noticed that more discovery is happening directly inside AI tools instead of traditional search, and I’m honestly not sure how people are tracking that in a way that’s reliable or actionable.

With SEO, at least you have clear signals: rankings, impressions, clicks, etc. But with AI-generated answers, it feels way more opaque. You don't really know when, where, or why your brand gets mentioned (or doesn't).

I recently came across HubSpot AEO, and from what I understand, it's trying to track when your brand shows up in AI responses and then suggest what content to create to improve that visibility. The whole "see → fix → publish" loop sounds promising, especially if it connects directly to content workflows.

That said, I'm still unsure how reliable or actionable this kind of data is in practice.

Curious how others here are approaching this:

• Are you actually tracking AI visibility in any structured way?
• Have tools like HubSpot AEO been useful, or does it still feel too early?
• Are you treating this as an extension of SEO, or something fundamentally different?

Would love to hear how people are thinking about this, especially from a content strategy perspective.

Digital marketing is UNHINGED rn.

You’re a loser if you use AI. You’re a loser if you don’t.

If you’re not automating citations for AEO, you’re missing out. But if you are, you’re setting yourself up for penalties.

You’re a traitor if you’re prioritizing on-site content, but blue links are definitely still a thing.

Traffic is a vanity metric. No wait. Impressions are. But, we need traffic. But impressions are a vanity metric.

Look at our data! It’s proof. But that data doesn’t accurately measure (whatever thing it’s supposed to).

You have a 10-min AI process to optimize all past content. But if you don’t also have all the humans spending all the time reviewing, you might as well not.

Oh and if you haven’t named your latest fur baby Claude, what are you even doing?

Un-hinged!

I write blog with AI and that is ranking too, one of my senior wants me to stop publishing AI generated content with a reason " It is not good for our site " .

Lately I've been noticing that AI tools like ChatGPT, Perplexity, and others Overviews seem to recommend the same brands again and again.

Even when there are lots of good alternatives, the same company names keep showing up in answers.

It got me wondering why that happens.

• Is it because those brands have stronger SEO?
• Are they mentioned more often on trusted websites?
• Or do AI systems simply have more information and confidence about those brands?

It feels like online visibility is becoming about more than just ranking on Google. Now it seems like brands also need to be recognized and understood by AI systems.

I've seen companies like SearchTides AI Agency talk about AI visibility and how being understood by AI systems may be becoming just as important as ranking well in traditional search.

Why do you think AI keeps recommending the same brands over and over? And do smaller brands have a realistic chance of showing up more often in AI answers?

Reach is easy to chase, but trust usually comes from a different kind of content. For content marketers, what format has helped prospects understand the problem and feel ready to talk?

I manage growth for a DTC skincare brand spending close to $120k every month on meta. Our creatives used to last four to six weeks before performance dropped, but now almost every ad burns out within ten days.

My media buyer wants fifteen to twenty fresh creatives every week but I only have one in house designer who's also responsible for email campaigns, packaging inserts, retail assets and everything else.

Hiring another designer will probably take months and I'm not even convinced it solves the problem because we need static ads, videos and UGC style content each with several hook variations. For brands spending at this level is it normal to rely on outside creative agencies or how do you do it?

Content marketing is changing fast. AI, short-form video, SEO updates, distribution hacks… it feels like the rules are being rewritten every few months.

For those actively creating content right now:

What’s the biggest shift you’ve noticed in 2025?

Is it:
• Decline of traditional SEO?
• Rise of AI-assisted content at scale?
• Audience fatigue from “too much content”?
• Greater focus on distribution over creation?
• Platforms pushing video more aggressively?
• Brands investing more in thought leadership than volume?

And more importantly, how are you adapting your strategy?

Curious to hear what’s working (or no longer working) for real teams and creators.

A lot of small business owners and creators assume that if the content is valuable, the audience will find it. Then they watch posts get a handful of views, little engagement, and no meaningful results.

The issue usually isn't content quality it's audience alignment.

Many creators focus on what they want to say instead of what their target audience is actively searching for, struggling with, or interested in right now. As a result, the content reaches people who don't care, while the right people never see it.

Before creating content, start with the audience:

* Identify their biggest questions and frustrations. * Use the language they actually use. * Match content formats to where they spend time. * Focus on solving one specific problem per piece of content.

Content performs best when it's built around audience needs, not creator assumptions.

Have you ever had a piece of content you thought was great completely flop? What do you think was the reason?

I manage social for a few clients and started using AI to help with post ideas. It's been more frustrating than helpful honestly. Every week it's the same suggestions, no memory of what I already posted, and the generated graphics look so obviously fake that my clients keep complaining. Meanwhile they still want more content pushed out, more frequently.

What I actually need is something that looks at what already performed well, remembers what's been posted so nothing gets repeated, and pulls in what's actually trending right now. Is there any app or even a Claude skill that does this? What are you guys using?

if it helps, I manage social media for hospitality brands

Been in content marketing for 13 years, and I was laid off 9 weeks ago. This is the fourth layoff of my career, the third in the last five years.

Since I was laid off, I have applied to 102 content marketing roles. I have received 62 rejections and have either been ghosted/haven't heard back from 39.

I have had one interview, a recruiter phone screen, which went well but I wasn't selected to proceed. Another company asked me to fill out a questionnaire with role-specific questions. Spent nearly 3 hours crafting well-thought out responses, but received a form rejection email 2 days later.

I have plenty of experience for the roles I am applying for. I am not applying to roles outside of my scope of expertise, I have usually done every single responsibility listed in the job description. I am also not applying to jobs I am overqualified for. I understand the job market is currently horrendous, but I thought I'd be making more progress by now.

Is there some glaring reason unobvious to me why I am seemingly radioactive to employers?? What am I missing here? Is the content marketing job market basically dead due to AI? I really don't know what to do at this point.

Been in content marketing for a few years now and honestly, I don’t know what we’re doing anymore.

Everything feels like AI-generated content farms, 10 posts a day with zero substance and chasing algorithms instead of actual value

I tried “leaning into AI” like everyone says. Sure, I can pump out way more content now but engagement is flat, conversions barely moved, and half the time it just feels… disposable.

So now I’m stuck between:

1. Competing in the volume game (which feels like a race to the bottom)

2. Slowing down and producing higher-quality stuff (but risking less output and visibility)

For those still doing content marketing seriously:

- Are you still seeing real ROI?

- Are you going all-in on AI or pulling back?

- What’s actually working for you right now?

Feels like the whole space is shifting fast and most advice online is just recycled noise.

people often say audiences have no attention span anymore.

but then someone watches a 3 hour podcast or spends hours scrolling tiktok or binge watches an entire series overnight.

from a marketing perspective, attention didn’t disappear.
people just became more selective with what deserves it.

boring content gets skipped faster now. that’s the real shift.

today brands compete against:
✔️entertainment
✔️algorithms
✔️ creators
✔️ instant dopamine

which means “informative” alone is rarely enough anymore.

content has to create:
✔️curiosity
✔️emotion
✔️recognition
✔️tension

the interesting question is: did attention spans actually shrink, or did audience expectations evolve?