Useful for narrative-led B2B content, copywriting, and arguments about human craft versus AI.
Best for
Mid-market B2B software brands wanting founder-voice emails, longform thought pieces, and AI disclosure standards.
Not for
High-volume SEO articles, paid social captions, reach guarantees, and per-word rates.
Key takeaways
B2B content fails because it does not tell stories, not because it lacks AI.
AI takes formulaic writing jobs first; human craft is the differentiator.
Audience distrust of AI is a lasting constraint and a norm, not just a market gap.
Check first: Confirm current availability and ask for samples across other formats or assignments.
Main ideas
B2B content fails because it does not tell stories, not because it lacks AI · AI takes formulaic writing jobs first; human craft is the differentiator · Audience distrust of AI is a lasting constraint and a norm, not just a market gap
Anthony Moore writes about B2B content marketing, copywriting, and the craft of making brand writing feel human and story-driven.
They argue that brands lose readers when blogs, emails, and ads read like stiff sales pitches; the better alternative is storytelling that gives people a reason to care.
Follow them for candid arguments about writing, AI, and the job market, grounded in personal experience as well as advice about craft.
Moore connects clear editorial arguments to concrete examples.
In one post, they contrast forgettable B2B marketing with brands whose stories build a community, then point writers to fiction and narrative techniques as tools for improving campaigns.
Their view of AI is not simply that it cannot write: basic copywriting and other entry-level tasks are already vulnerable, while skilled, distinctive writing may stand out because many readers distrust AI and much generated content feels alike.
They also write in a personal, candid style, describing an unsuccessful job search after a layoff and explaining a decision to focus on roles that are genuinely appealing.
These examples make the work useful to readers thinking about B2B storytelling and the value of writing craft.
Ask for samples across other formats or assignments if that range matters to your decision.
Moore argues that B2B content has a storytelling problem, not just an AI problem.
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Most company content reads as stiff, robotic sales copy, while the brands worth studying tell stories and build communities.
They expect AI to absorb formulaic entry-level writing work but see a durable market for human voice, partly because audiences distrust AI-produced content and partly because skilled writing is hard to fake.
A difficult layoff and job search have also shaped their priorities: seeking content marketing, content management or copywriting work that is actually worth doing while spending more time with family.
The tension is that their own search shows quality recognition does not guarantee a role, even as they predict skilled writers will stand out.
B2B content fails because it does not tell stories, not because it lacks AI
Moore describes much B2B company content—including blogs, emails, ads and About pages—as stiff, stale, robotic and ineffective.
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The models they point to are brands that told stories and built communities rather than publishing barely concealed sales pitches. Narrative devices and fiction techniques can work even in bland B2B campaigns, Moore argues, while most AI attempts at that register land as tone-deaf.
Moore recalls studying brands whose customers would proudly wear their clothes to a family picnic. They have also started writing fiction to learn how stories reach readers and want to apply that craft to brand work.
Moore does not treat AI as the sole cause of bad content. The quality problem predates AI and creates an opening for better storytelling.
AI takes formulaic writing jobs first; human craft is the differentiator
Moore divides writing work into two groups.
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Basic copywriting, content marketing, SEO, email newsletters, social captions and sales pitches are being replaced, especially at the entry level.
AI cannot yet produce longform blogs, books, novels and thought pieces consistently.
Two reasons keep human writers in the market: a large share of people distrust AI-produced content, and quality human writing is hard, making distinctive voice more visible as AI-generated content homogenizes.
Moore's first job out of college was writing short reviews of elderly rest homes for $8 an hour, exactly the kind of entry-level work they say is disappearing. They point to longform and thought pieces as examples of writing AI can produce occasionally but not consistently.
Moore allows that AI can sometimes produce decent songs or a good longform piece, and says becoming a great writer is not guaranteed. Their own job search complicates the cream-rises claim: recruiters and hiring managers affirmed the quality of their content, yet they still could not secure a lasting content role, which they attribute to external factors rather than the writing itself.
Audience distrust of AI is a lasting constraint and a norm, not just a market gap
Moore argues that a large segment of the public will immediately discount content once they learn AI was involved, even in a small way, and that no amount of quality overcomes that distrust right now.
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They state a preference as a norm: preferring human-created art over AI-created art is the right default.
Moore writes that even if AI could make good songs, movies, video games, books or art, many people would immediately dislike and distrust the AI-produced work.
A hard job search reshaped Moore's priorities around fit, family and honest work
After a tech layoff, Moore spent six months applying to roughly 1,500 or more jobs, got around 40 interviews with 20 companies and still did not get hired directly.
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Their only job came through a recruiting agency as a four-month contract, and the content marketing work was shut down afterward.
On the next search, they plan to apply only to jobs worth having and spend more time with family and kids while looking.
They ask readers for content marketing, content management or copywriting leads.
Moore marks the anniversary of the layoff and gives the application and interview counts as concrete context. They relay a mentor's advice to use the unemployed time with family because work will come again.
Moore says the earlier effort was driven by desperation and that applying to everything was unsustainable. Their approach has changed, not their belief about writing quality.
Moore explains what they mean by human, story-driven B2B content and why they see storytelling—not AI novelty—as the durable skill.
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Start here for the core argument in their own words and concrete B2B examples.
Moore argues that B2B content is often stiff, stale, robotic, AI-sounding, and ineffective.
They recall studying brands at previous content jobs whose blogs and emails were not barely concealed sales pitches and whose communities would proudly wear the clothes to a family picnic.
They say AI can sometimes produce decent songs, but struggles to tell real stories.
They recommend writers spend less time fearing AI and more time learning narrative techniques from fiction and their favorite novels.
For brands planning a campaign
For a brand content test, ask candidates to rewrite a bland B2B blog or email as a story, not produce a generic AI-assisted draft. Evaluate whether they can turn a product message into a human narrative, demonstrate narrative craft, and avoid a sales-pitch cadence.
Moore distinguishes AI-vulnerable writing tasks from work that depends on trust, taste, and voice.
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This post is a useful starting point for understanding their view of craft and why they believe human writing still has a market.
Moore says generative AI will replace many basic copywriting, content marketing, SEO, email newsletter, social caption, and sales pitch jobs, especially entry-level roles.
They note that their first job out of college was writing short reviews of elderly rest homes for $8/hour.
They argue that writers still have two advantages: a large share of people distrust and discount AI-produced content, and quality human writing is hard to produce, so an authentic voice will stand out in a sea of homogenized slop.
They say AI can occasionally produce longform blogs, books, novels, or thought pieces, but not consistently.
For brands planning a campaign
Give candidates a brief requiring a distinctive voice and point of view, then compare their work with a generic AI draft.
Look for specific observations, original phrasing, and writing that earns trust.
A short test could ask them to write a 300-word thought piece or newsletter section on a real B2B topic and explain their editorial choices.
Moore describes what they have been doing between content roles and how the job search fits into their current professional story.
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Start here for context on their resilience, job-market experience, and content-marketing goals.
Moore recounts the anniversary of a tech layoff, six months of job hunting, roughly 1,500+ applications at 25-50 per day, about 40 interviews with 20 companies, and no direct hire.
They eventually found work through a recruiting agency on a four-month contract; talk of keeping them on ended when a higher-up shut down content marketing work.
This time, they say, they will apply only to jobs they actually want.
They mention a mentor's advice to spend time with family and kids while not working, and ask readers to send content marketing, content management, or copywriting opportunities.
For brands planning a campaign
Moore writes candidly about seeking content work and facing career setbacks.
For a hiring brief, use the post to open a direct conversation about role scope, stability, and the kind of content team they want to join.
Their human, first-person voice can also be tested with a short personal-essay-style brief.
B2B content has a quality problem. Storytelling is the fix.
Moore describes the B2B content landscape bluntly: company blogs, email campaigns, ad copy, and About pages are often stiff, stale, and robotic.
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The models they point to are brands that told stories and built communities, rather than blogs and emails that read as barely concealed sales pitches.
Moore compares randomly sampled B2B company content with brands that have built real communities, then asks what the stronger brands do differently: tell stories instead of pitching.
For brands planning a campaign
The agency's brief calls for a writer who keeps brand content human and story-driven.
That is Moore's central argument, not a side note.
For a writing test, provide a real product or service spec sheet and ask for a draft that reaches readers without a sales pitch.
Check whether it reads like a story or a template with adjectives swapped in.
AI absorbs formulaic writing jobs first; longform and thought pieces resist it
Moore divides writing work into two groups.
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Basic copywriting, content marketing, SEO, email newsletters, social captions, and sales pitches are being replaced, with entry-level roles hit hardest.
AI cannot yet produce longform blogs, books, novels, and thought pieces consistently.
Moore entered the field with a low-paid job writing short reviews—the kind of work now being automated.
Moore draws the line by job category and by the length and depth of the writing, rather than treating all writing work as one market.
Moore does not claim longform writing is safe in principle. Their claim is about current reliability: AI can produce a good longform piece occasionally, but not consistently.
For brands planning a campaign
Test Moore on the format the campaign needs. For longform brand articles, essays, or narrative thought pieces, use one of those as the writing test rather than short ad copy, where their argument says the market is weakest and differentiation is smallest.
Audience distrust of AI content is treated as a lasting constraint
Moore argues that a large share of the public discounts content once they learn AI was involved, even incidentally, and that quality cannot overcome that reaction.
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They take a position on the norm, not just the market: preferring human-created art over AI-created art is the right default.
For brands planning a campaign
This matters for agency positioning and disclosure.
Moore argues that if a brand uses AI anywhere in its content process, audiences will react to the process, not just the output.
Ask how they would handle a client that uses AI assistants internally, and look for a workable answer rather than a blanket refusal or endorsement.
Voice and craft as the differentiator when content homogenizes
Moore predicts that as AI lowers the barrier to publishing, most online content will feel homogenized and stale, partly because people who use AI to write cannot tell what good writing looks like.
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Skilled, distinctive human writing will stand out. Their advice: spend the time learning to write well and developing a recognizable tone.
Moore frames the opportunity around craft, not channel: the same structural advantage applies across blogs, books, and thought pieces.
Moore acknowledges the outcome is not guaranteed: a writer can put in years of effort and still be mediocre. The advantage comes only if the writing is actually good.
For brands planning a campaign
A writing test should measure voice, not just correctness. Ask for two samples from different briefs and see whether a reader could identify the writer from the prose alone—the same distinction the agency would want Moore's work to make in a client's feed.
Moore has started writing fiction and argues that tools from novels, such as narrative devices and writing tricks, transfer to conventional B2B campaigns.
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They say AI attempts rarely get past the tone-deaf \"how do you do, fellow kids\" register, leaving room for writers who can build a narrative.
Moore treats fiction as deliberate practice: writing outside marketing channels to learn what makes a story land with a reader.
For brands planning a campaign
For a storytelling-focused brief, ask Moore to take an unglamorous B2B topic and map out its narrative options before drafting. That shows whether their fiction practice transfers to client work or remains a personal interest.
A public, first-person account of a difficult content-marketing job search
One post marks the anniversary of a layoff from a tech job and describes roughly 1,500 applications, about 40 interviews with 20 companies, a four-month contract found through a recruiting agency, and a return to searching.
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Moore says plainly that the effort did not produce a lasting role and that the only paid work came through an agency. The post asks for leads in content marketing, content management, and copywriting.
Moore turns the job search into a narrative, with a changed approach the second time: applying only to roles worth having and spending time with family in the meantime.
The post cites fit and company decisions, not writing quality, as reasons for rejections. Moore says recruiters and hiring managers have affirmed the quality of their work. That is their account, not independent verification.
For brands planning a campaign
Two practical points for an agency considering Moore.
First, they say they are seeking content marketing, content management, and copywriting work; confirm their current availability before scoping.
Second, this post is a useful writing sample, showing how they handle a personal, high-stakes story for a professional audience.
The posts describe Anthony Moore's work history and views on B2B content, but name no employer, client, sponsor, or brand.
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They mention a tech job they were laid off from, a four-month content-marketing contract they got through a recruiting agency, and a first job out of college writing short reviews of elderly rest homes—all unnamed.
They also discuss B2B company blogs, emails, and ads, and brands studied at earlier content jobs, without identifying any of them.
Ask for employer, client, sponsor, or brand names before treating any relationship as documented.
Start with Anthony Moore's post arguing that B2B company blogs, emails, ads and About pages often read as stiff sales copy, while stronger brands tell stories and build communities.
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Then read the two posts on AI and writing: one separates formulaic entry-level work from longform and thought pieces; the other treats audience distrust of AI as a lasting constraint.
A more personal post covers a six-month job search after a 2023 layoff and a shift toward fit and family.
Explore Moore for essay-style arguments about voice, narrative craft and fiction techniques in brand work, not channel tactics or lead-generation checklists.
Ask for longform samples and publishing history before assessing those areas.
Both treat B2B content as a business asset rather than decoration: Kaur maps a four-week content and lead-generation plan and diagnoses a broken lead form; Moore argues that brand content should tell stories instead of sounding like sales copy.
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Kaur's work is tactical and operational, built around funnel stages, search visibility, CRM tracking and lead generation. Moore's is essayistic, focused on narrative quality, voice and why human storytelling resists AI.
Both write from inside content work about how to produce stronger content: Asalm describes a five-step process for writing 21 posts in two days and running founder content; Moore argues for narrative craft and voice against AI homogenization.
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Asalm emphasizes speed, repurposing and repeatable production workflows for founders. Moore focuses on story quality, audience distrust of AI and the limits of formulaic writing.
Both argue that differentiation matters in an AI-saturated content market.
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Longjam contrasts commodity content with signature content through margins and sales-cycle questions; Moore makes a related case through storytelling, audience distrust of AI and craft.
Longjam analyzes content through business-model economics, funnel design and monetization. Moore focuses on narrative technique, fiction craft and the human voice in brand writing.
The only measured audience number available for Anthony Moore is 2,357 LinkedIn followers, observed 9 October 2026.
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The posts here do not provide engagement data, so nothing shows how far a given post travelled or which topics and formats drew the strongest response.
The three posts leave that question open, which matters if you plan to judge reach before booking.
What the writing signals is a reader group rather than a measured segment.
The posts speak to people who make content: writers weighing what AI means for their work, marketers frustrated by stiff B2B copy, and content professionals navigating layoffs and job searches.
A B2B content agency seeking a human, story-driven writer is addressing that same professional audience, so the content appeal points in a relevant direction.
Composition cannot be claimed.
The posts do not document geography, age, gender, employer, occupation, or seniority, so treat any statement about who the followers are as unverified rather than established.
Follower count alone does not tell you whether the people reading are the buyers, editors, or peers you want to reach.
Before committing to a paid placement, ask for post-level results from the last six to twelve months: impressions, comments, shares, and profile views.
That lets you compare the topics, depth, and formats closest to the content you want to sponsor instead of relying on a headline follower number.
If your campaign depends on job titles or seniority, ask specifically whether Moore has audience survey results or advertiser demographic data for the LinkedIn audience.
Moore’s posts do not document sponsorship packages: none of the three sets out a sponsored-placement format, rate card, deliverable specifications or paid brand partnership disclosure.
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A July 2024 post says they are looking for an expert role in content marketing, content management or copywriting and asks readers to pass on leads.
That signals hiring or contract availability, not a sponsorship offer; no terms, pricing or deliverables are stated.
Buyers should ask directly whether they accept sponsorships and, if so, about available formats, rates, deliverables and how to inquire.
A mid-market B2B software company wants six months of narrative-led content: a founder-voice email series, two longform thought pieces per quarter, and a written standard for disclosing AI use in its content workflow.
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Moore is a strong fit.
The company’s core problem—stiff B2B copy that reads as a barely concealed sales pitch—is one they write about directly.
Their proposed fix is to study brands that tell stories and build communities, then borrow narrative devices from fiction for brand work.
Their own breakdown of writing work points the same way: they say AI is already absorbing short, formulaic copy, SEO filler, newsletters, and social captions, with entry-level roles affected first, while AI cannot yet produce longform blogs and thought pieces consistently.
Hiring them for that second category puts the writer where they argue human craft still wins.
Their position on AI disclosure also matters for the policy deliverable.
They treat audience distrust as a lasting constraint, not a temporary one, and say people discount content once they learn AI was involved, even incidentally.
A client using AI assistants internally needs a working answer to that challenge, and Moore has a stated view to start from.
The layoff post also offers a close example of the needed register: a first-person, high-stakes story for a professional audience, the tone a founder-voice email series has to carry.
Before scoping, confirm current availability: Moore is publicly asking for leads on content marketing, content management, and copywriting work.
Request a longform sample; the available set contains three LinkedIn posts and no longform piece, so the case for their longform work rests on their account of craft rather than a sample.
When to choose a specialist
A consumer e-commerce brand wants roughly 40 SEO articles a month, about 90 paid social captions, guaranteed reach of 50,000 views per post, two-day turnarounds, and per-word rates.
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Moore is a poor fit for three specific reasons.
First, the deliverables—high-volume SEO articles and social captions—sit in the category their own argument identifies as most at risk: basic copywriting, content marketing, SEO, email newsletters, and captions.
They say those jobs are already being replaced, with entry-level roles affected fastest, and that writers are least differentiated there.
Nothing in their posts shows they want this work or would be the strongest choice for it.
Second, the reach guarantee is unsupported.
The only measured audience number in their posts is 2,357 LinkedIn followers, observed 9 October 2026; there is no engagement data—no impressions, shares, comments, or profile views for any post—and no other channel mentioned.
A buyer should request post-level reach data before considering a 50,000-view commitment per post.
Third, the commercial structure is undefined.
Their posts contain no sponsored-placement format, rate card, deliverable specification, or verified sponsorship inquiry route, so a buyer would need to define terms from scratch.
The priorities also conflict: Moore argues that craft and voice earn a writer attention, while this brief emphasizes volume and speed.
A worked campaign example
A B2B content agency wants a writer who keeps brand content human and story-driven. A paid two-part test can separate voice from correctness, followed by a scoped pilot.
Step 1: Build the test around a real client problem.
Use a live spec sheet, product page, or bland email a client has already published.
Ask for a 300 to 400 word thought piece or newsletter section, plus a short note explaining the editorial choices.
Keep it long enough for voice to show.
Moore says short ad copy is where the market is weakest and differentiation smallest, so testing there says little about fit for this role.
Step 2: Score voice and specifics.
Look for concrete observations, a point of view a reader could argue with, and prose recognizable as the writer’s from the page alone.
Run a generic AI draft of the same assignment alongside each submission and ask which one a reader would finish.
Moore says AI can occasionally produce a decent longform piece but not consistently; one strong output is weaker evidence than a consistent voice across unrelated assignments.
Ask for two samples from different assignments.
Step 3: Ask how the candidate would handle disclosure to the client’s audience if the agency or its clients use AI anywhere in the work process.
Listen for a workable process, not a blanket refusal or endorsement.
Moore says audiences discount content once they learn AI was involved, even incidentally; the answer has to account for that constraint.
Step 4: Scope and hand off the pilot.
Start with one founder-voice email or one longform thought piece tied to a client’s real audience, and agree on a disclosure standard before drafting.
Judge the output against the existing page it replaces, giving the client a concrete comparison rather than a taste argument.
Step 5: Before commissioning the test, request two longform samples, confirm current availability, and ask for post-level performance data from the last six to twelve months. Moore’s posts do not provide those items, and each affects how the test should be scoped.
That practical emphasis can help a team check whether the problem is its content—or the path from content to inquiry—before commissioning more storytelling.
The examples show a strong focus on lead generation and marketing operations. Ask for samples that show how the creator develops fiction-informed storytelling and a distinctive narrative voice.
Choose Asalm when the priority is a repeatable process for turning client expertise into LinkedIn content.
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In a breakdown of a 21-post process, they describe researching each niche, matching formats to the brand, building each post around one idea, and refining for the client’s voice.
A second post explains a founder-content process built around advance research, kickoff calls, a monthly interview, an ongoing idea repository, and weekly review.
That may suit an agency that needs to capture a founder’s thinking without relying on daily voice notes.
The examples make the research and voice-capture process concrete. Ask for samples of narrative-led longform writing and the storytelling approach Anthony Moore emphasizes.
Choose Longjam when the goal is to structure content around an AI software product’s acquisition and conversion goals.
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In a content-strategy breakdown for an AI SaaS company, they propose a mix of tutorials, comparisons, use cases, monetization content, and thought leadership, then connect it to a cycle from traffic and education through product use and conversion. That system-level view is more directly useful when the main challenge is planning content to support product adoption.
The examples focus on content strategy and commercial structure. Ask for samples that demonstrate founder-voice storytelling and longform craft.
Anthony Moore's three LinkedIn posts cover B2B content and storytelling, which writing jobs AI replaces and which it does not, and a first-person account of a layoff and job search.
The basic profile listing attached to the account shows 2,357 followers, observed 9 October 2026, and is the only audience figure available here.
The posts do not give exact publication dates, so no dates are assigned to them; one post marks the anniversary of a 2023 layoff and describes a six-month search afterward.
No longform samples or engagement data such as impressions, shares, or comments appear in the posts here, and no employer, client, or sponsor names are mentioned.
Where those gaps affect a decision, such as judging writing quality across formats or confirming current availability, they are named in the relevant section rather than filled in.
No signature book, show, or business is documented here.
The posts state the claims about Moore, and nothing beyond them has been verified.
