Moni Oloyede works in marketing operations and writes about how B2B marketing teams should adapt their roles, technology, and methods—including marketing automation, account-based marketing, and the changing skills companies seek.
Moni Oloyede is useful for practitioner-led discussion of B2B marketing operations, ABM, and marketing automation changes.
Best for
A marketing automation or AI-for-marketing platform seeking a practitioner voice for webinar and LinkedIn posts.
Not for
Conventional MQL, lead-scoring, nurture-email, gated-download, or volume-based pipeline campaigns.
Key takeaways
They say marketing operations job titles obscure the problem companies are hiring to solve.
They argue ABM is not demand generation pointed at 50 named accounts.
They ask what becomes the center of the MarTech stack and what AI replaces.
Check first: Confirm deliverables, fee, usage rights, audience data, and the longer job-description analysis.
Main ideas
AI is resetting the marketing operations playbook · Marketing operations job titles obscure the problem companies are hiring to solve · ABM is not demand generation aimed at named accounts
Moni Oloyede writes about how B2B marketing teams should adapt as their roles, technology and methods change. The work connects shifts from AI and marketing automation to account-based marketing with practical questions for marketers and job seekers: What problem needs solving, and what should change to solve it?
Oloyede makes shifts in B2B marketing easier to understand by distinguishing between problems often lumped together.
Drawing on roughly 100 job descriptions, they separate Marketing Operations, GTM Engineering and Marketing Engineering by the needs each role addresses, and advise job seekers to look beyond job titles.
On ABM, they argue that pointing a demand-generation program at 50 accounts is not enough: the strategy must shift from individual leads and volume toward accounts, relationships, signals and revenue.
A post about AI and marketing automation takes a more exploratory approach, raising questions about the future of the marketing operations role and technology stack rather than resolving them.
Together, these examples offer a practical way to think about where B2B marketing is changing and what those changes may mean for marketers’ work.
Moni Oloyede argues that AI is reshaping B2B marketing operations and that inherited habits and job titles are no longer reliable guides.
Read more
Across three posts, they question legacy metrics like MQLs, lead scoring, and attribution; argue that marketing operations job titles obscure the problem a company is hiring to solve; and say account-based marketing works only when teams abandon demand-generation habits and build around accounts, people, relationships, signals, and revenue.
AI is resetting the marketing operations playbook
Moni Oloyede argues that lead scoring, weekly batches of emails billed as nurturing, attribution as a standalone concept, and the MQL feel increasingly out of date.
Read more
In this framing, AI is both a revolution and a burden.
The version of marketing automation many careers were built around is changing, and Oloyede says that is no longer up for debate.
The open questions: what becomes the center of the martech stack, what AI actually replaces, and what the marketing operations job becomes.
Moni Oloyede promoted a MarTech Conference panel on November 4 titled "Marketing automation is dead.
Long live marketing automation!" with Frans Riemersma, Eric Dates, and Milt Hwang, pointing to free registration and panel details.
The post is a position statement and event announcement; the detailed answers are in the panel.
The title holds a deliberate tension: marketing automation is declared dead and told to live on. The reversal captures the argument: old practices are fading, but the discipline is not disappearing.
Marketing operations job titles obscure the problem companies are hiring to solve
After looking at roughly 100 marketing-operations-related job descriptions, Moni Oloyede found that companies hire for Marketing Operations, GTM Engineering, and Marketing Engineering but do not always distinguish between them.
Read more
The practical advice: look past the job title and identify the problem the company is trying to solve.
Complexity creates demand for operations; the need for more automation and leverage creates demand for GTM Engineering; and the limits of off-the-shelf technology create demand for Marketing Engineering.
The skills employers seek change with those problems.
Moni Oloyede opens with a single listing that asks for Marketo, Salesforce, attribution, lifecycle, lead scoring, data governance, reporting, APIs, AI, automation, enrichment, SQL, and maybe Python. The post links to a longer write-up breaking down skills by role; ask for it to review the full breakdown.
ABM is not demand generation aimed at named accounts
Moni Oloyede argues that taking a demand generation program, aiming it at 50 accounts, and calling the result ABM does not work.
Read more
The approach requires letting go of things B2B marketing has spent years optimizing for: MQLs, lead scoring, form downloads, individual leads, and volume as the goal. ABM asks a different set of questions and builds around accounts, people, relationships, signals, and revenue.
Moni Oloyede promoted a DC Marketing Tech Talks event on October 15, 6–8 PM ET, at Red Clay Creative in McLean, Virginia. The event is aimed at people putting ABM on their 2027 plans, with a registration link.
It answers the question a newcomer is most likely to have about Moni Oloyede's point of view: what does the marketing operations job become when AI gets involved?
Read more
The post frames the shift in the field in their own words before explaining anything else.
Oloyede argues that the tools and habits behind many marketing operations careers are going out of date: lead scoring, sending a batch of emails every week and calling it nurturing, attribution, and the MQL.
In their framing, AI arrives as both a revolution and a burden.
The post lists the open questions they intend to address, including what becomes the center of the martech stack, what AI actually replaces, and what the marketing operations role turns into.
It then announces a MarTech Conference panel on November 4 with Frans Riemersma, Eric Dates, and Milt Hwang, titled with the same “dead / long live” reversal, and links to free registration and panel details.
The post is a position statement and public appearance announcement; the panel is where the answers will be explored.
For brands planning a campaign
A strong starting point for campaigns about the future of the martech stack, AI and marketing operations roles, or conference tie-ins. Use it to gauge the themes Oloyede wants to be associated with.
Rather than opining about the job market, Oloyede sampled roughly 100 marketing operations job descriptions and reported the pattern they found.
Read more
For readers seeking evidence of original research, this is the clearest example here.
The post opens with a familiar job-hunting complaint: a single listing asks for Marketo, Salesforce, attribution, lifecycle, lead scoring, data governance, reporting, APIs, AI, automation, enrichment, SQL, and Python.
Oloyede concludes that companies are hiring for three different things—Marketing Operations, GTM Engineering, and Marketing Engineering—without consistently distinguishing them.
The practical advice is to look past the job title and identify the problem the company is trying to solve: complexity creates demand for operations, the need for automation and leverage creates demand for GTM engineering, and the limits of off-the-shelf technology create demand for marketing engineering.
The post links to a longer write-up with a breakdown of skills per role.
For brands planning a campaign
Useful for campaigns about martech hiring, skills, or careers; it demonstrates firsthand analysis rather than commentary. The post only summarizes the detailed breakdown, so ask for the linked write-up if the brief depends on the full table of findings.
It is the clearest sample of Oloyede's account-based marketing argument, showing their teaching style—a blunt correction followed by a short list of what has to change—in a single read.
Read more
Oloyede's point is that taking a demand generation programme, aiming it at fifty accounts, and calling the result ABM does not work.
The approach requires giving up things B2B marketing has spent years optimising for: MQLs, lead scoring, form downloads, individual leads, and volume as the goal.
Instead, the post says ABM asks different questions and needs to be built around accounts, people, relationships, signals, and revenue.
It announces a DC Marketing Tech Talks event on October 15, 6–8 PM ET at Red Clay Creative in McLean, Virginia, aimed at people putting ABM on their 2027 plans, with a registration link.
For brands planning a campaign
A direct fit for an ABM-focused brief, especially one arguing that account-based motions require different measurement and content. The post establishes Oloyede as someone who pushes back on demand-gen habits, useful to know before commissioning commentary.
Marketing operations and the AI-driven MarTech reset
Moni Oloyede argues that familiar marketing operations practices—lead scoring, weekly nurture sends, attribution as a standalone concept and the MQL—feel increasingly outdated as AI enters the stack.
Read more
The post asks what will become the center of the MarTech stack, what AI actually replaces and what the marketing operations job becomes.
They promoted a MarTech Conference panel on November 4, titled “Marketing automation is dead.
Long live marketing automation!”, with Frans Riemersma, Eric Dates and Milt Hwang.
A question-led frame calls conventional practices outdated, then turns to the operational questions the panel will address.
For brands planning a campaign
Brands selling marketing technology, AI tools or operations services could consider Moni Oloyede for a strong-opinion perspective on where the stack is heading and how AI is changing marketing operations. They’re best suited to panels, webinars and thought-leadership campaigns that need a practitioner to challenge accepted metrics, not just describe them.
The marketing operations job market and the rise of GTM and marketing engineering
After reviewing roughly 100 marketing-operations-related job descriptions, Moni Oloyede found that companies hire for Marketing Operations, GTM Engineering and Marketing Engineering but do not always distinguish among them.
Read more
The argument: look beyond the job title to the problem the company is trying to solve.
Complexity creates demand for operations; the need for more automation and leverage creates demand for GTM Engineering; and the limits of off-the-shelf technology create demand for Marketing Engineering.
The skills employers ask for vary with those problems.
Original analysis of approximately 100 job descriptions, broken down by role and the skills appearing in each.
For brands planning a campaign
Brands in marketing technology, recruiting or professional development could work with Moni Oloyede on role definitions, skills gaps and the changing nature of operations work. They could interpret hiring patterns or anchor content on what companies need from marketing operations, GTM engineering and marketing engineering hires.
ABM is not demand generation pointed at named accounts
Moni Oloyede argues that account-based marketing means letting go of habits B2B marketing has spent years optimizing: MQLs, lead scoring, form downloads, individual leads and volume as the goal.
Read more
ABM instead centers on accounts, people, relationships, signals and revenue. They promoted a DC Marketing Tech Talks event on October 15 at Red Clay Creative in McLean, Virginia, to explore what ABM looks like when it is not a repurposed demand generation program.
Event promotion paired with a direct repositioning argument: define what ABM is not, then name the account, relationship, signal and revenue focus that replaces it.
For brands planning a campaign
Brands with ABM software or services, and organizers of regional B2B marketing events, could consider Moni Oloyede for education that moves buyers beyond demand-generation thinking. The post points to an in-person community format and a willingness to confront common ABM misapplication, making them a potential fit for event sponsorship or ABM-focused content campaigns.
A post promotes an October 15 marketing technology event at Red Clay Creative in McLean, Virginia, focused on building ABM programs around accounts, people, relationships, signals, and revenue rather than demand generation volume.
Read more
The post calls it "our next DC Marketing Tech Talks event"; ask whether Moni Oloyede organizes, hosts, or speaks at it.
A useful way to read Moni Oloyede is to move from the most concrete piece to the broadest argument.
Read more
Start with the job-description analysis, which pulls apart roughly 100 marketing operations listings and distinguishes Marketing Operations, GTM Engineering, and Marketing Engineering by the problem each role is meant to solve.
It's the most practical item for hiring managers and job seekers.
Next is the account-based marketing post, the sharpest of the three: it says ABM is not demand generation aimed at 50 named accounts, then describes what replaces it—accounts, people, relationships, signals, and revenue.
The marketing automation post is the broadest, a position statement arguing that lead scoring, weekly batch nurture, attribution as a standalone idea, and the MQL are fading while the discipline itself continues; the detailed answers are in the panel they promoted.
Two posts also invite readers to live events, offering those near Washington, DC, or attending the MarTech Conference a chance to follow the ideas in person.
Rizzo covers the same territory from a different angle: who owns the go-to-market technology stack, how marketing operations work is changing, and what vendor moves mean for the people running it.
Read more
Their posts ask why RevOps became sales operations with a dashboard, much as Oloyede asks how job titles can hide the real problem a company is hiring to solve. Both treat marketing operations as the place where strategy becomes measurable technology, and publish dated, specific alerts rather than general commentary.
Rizzo's posts are field reports: observations from dozens of conversations at an industry event and a video update on Marketo API deadlines, AI partnerships, and regulatory changes.
Oloyede's focus is role analysis and practice arguments about hiring, ABM, and automation.
Rizzo emphasizes ownership and technical governance; Oloyede examines how the profession should reinterpret its own playbook.
Silvestri argues that marketing operations professionals who connect systems, clean data, and build automation are routinely underestimated, and that AI is elevating the role rather than eliminating it.
Read more
That conclusion is close to Oloyede's claim that the automation many careers were built on is changing, not disappearing. Both explain the role to an outside audience and focus on what operations can prove about revenue.
Silvestri's posts focus on metrics: pipeline sourced by marketing, CAC versus LTV, marketing ROI, lead-to-customer conversion, and the clean-data problem behind them.
Oloyede's focus is hiring and practice: distinguishing role types and arguing about how ABM and automation should be run.
Silvestri teaches through measurement; Oloyede through definitions and role boundaries.
Hove writes for fellow marketing operations professionals, turning collected career notes into a post series on how to succeed in the role: be analytical, process-oriented, and collaborative.
Read more
That coaching approach aligns with Oloyede's focus on where the community's work is heading. Both address the same professional audience rather than buyers.
Hove's posts combine a personal lessons series with a recruiting referral, offering advice on how to operate and find roles. Oloyede analyzes the field's direction, from job-description patterns and ABM practice to AI's impact on the stack, and ties the posts to conference and community events.
Moni Oloyede's LinkedIn following is 6,385 people as of 7 October 2026.
Read more
The three posts here target marketing operations practitioners and adjacent GTM/marketing engineering roles, covering the changing MOps job market, ABM program design, and the future of marketing automation ahead of a MarTech Conference panel.
The account could suit a campaign about future MarTech stack trends seeking people who work in or hire for marketing operations.
The posts do not establish that the audience includes executives or budget holders.
Ask whether they have audience survey results or another documented source for professional attributes such as employer, occupation, and seniority.
Also request recent results for comparable posts, including depth and formats; the posts provide no per-post views, likes, comments, or video performance data.
Moni Oloyede's posts mention no partnership or sponsorship offer.
Read more
The three most recent posts cover commentary and event promotion; they state no sponsored-post, newsletter or paid-appearance terms and link to no rate card, audience specification or brand-partnership page.
The closest commercial activity is promotion of events they take part in: a MarTech Conference panel on marketing automation on November 4 and a DC Marketing Tech Talks session on account-based marketing on October 15.
Both offer free registration, not sponsorship terms.
Ask Oloyede to confirm available formats and terms before including them in a plan.
Campaign need: A marketing automation or AI-for-marketing platform wants a practitioner voice for a 30-minute webinar and two LinkedIn posts on how AI is changing the marketing operations job.
Read more
Decision: good fit.
Oloyede argues that lead scoring, weekly nurture sends, standalone attribution and the MQL are losing their grip, and asks what becomes the center of the MarTech stack, what AI replaces and what the MOps job becomes.
That is the question this webinar needs answered in public.
Their job-description post adds a concrete, original frame: companies hire for Marketing Operations, GTM Engineering and Marketing Engineering without distinguishing them; the better move is to identify the problem the company is solving.
The campaign can use that three-role distinction as the webinar’s spine and as a worksheet for viewers.
The October 15 ABM event and November 4 MarTech Conference panel show Oloyede is already speaking to these audiences, making a panel or webinar closer to their existing work than a scripted product ad.
Before using the full skill breakdown, ask to review the longer write-up behind the 100-job-description analysis.
Confirm deliverables, fee and usage rights directly; the posts do not state sponsorship terms or a rate card, or provide audience demographics.
When to choose a specialist
Campaign need: A demand generation agency wants a creator to front a lead-scoring and nurture-email optimization campaign, with MQL targets, gated form downloads and volume-based pipeline goals.
Read more
Decision: poor fit.
Oloyede’s public position runs against the campaign’s goal: they call lead scoring ridiculously out of date, weekly nurture sends silly, attribution a joke with no punchline, and the MQL on life support.
Their ABM post says a demand generation program pointed at named accounts is not ABM, and lists MQLs, lead scoring, form downloads, individual leads and volume as habits to drop.
Asking Oloyede to promote the opposite would create a credibility problem for both creator and brand.
If the agency wants a challenge to its own demand-gen assumptions, that is a different campaign need and could fit.
For a conventional MQL campaign, use another creator.
A worked campaign example
Worked campaign angle for the good-fit campaign: Bring your job description to the AI reset.
Format: a 30-minute panel-style webinar, one follow-up LinkedIn post and a one-page worksheet.
Opening: Oloyede names the four practices that feel out of date, then asks what becomes the center of the stack and what AI actually replaces.
Middle: they present the three-role distinction from the job-description analysis—Marketing Operations, GTM Engineering and Marketing Engineering—and ask viewers to read one live job description and decide which problem the company is really solving.
Close: the worksheet turns that into a hiring or tooling checklist, and the follow-up post carries the same three-role frame.
Next step: ask Oloyede to confirm the panel format, whether the linked write-up can be reviewed and cited, and the commercial terms.
The posts do not state audience demographics or post performance, so avoid promising executive reach or benchmark engagement; measure registrations and worksheet completion as first-party campaign data.
Choose Mike Rizzo when the campaign is about ownership of the go-to-market technology stack and turning platform churn into dated action items.
Read more
The posts make ownership the point: ask a CMO and a CRO who owns the GTM tech stack.
If you get two different names or none, that is the problem.
The second post turns a month of vendor news into concrete work — Salesforce and Anthropic's Claudeforce launch, Marketo REST API token and large-list failures with named deadlines, the EU AI Act transparency rules, Integrate's acquisition of CaliberMind, a Marketo UI refresh, HubSpot's Agent Hub — and closes with an audit of Marketo API calls.
For a webinar focused on system ownership or a live platform-risk checklist, this material is a closer fit than a role-level argument.
A campaign built around the marketing operations career question loses the distinction among three roles.
Mike Rizzo's posts argue about a function and its owner; they do not distinguish Marketing Operations, GTM Engineering and Marketing Engineering, or ask viewers to read a live job description and identify the problem a company is solving.
They also focus more on vendors and platforms than career change.
For a session helping practitioners understand how their roles are shifting, pair this material with Oloyede's job-description analysis.
Choose James Silvestri when the campaign needs a measurement and business-case angle in the AI-in-MOps conversation.
Read more
The posts argue that the role is undervalued because no one sees the plumbing, that AI elevates rather than eliminates operations, and that specialists who shift toward strategic analysis will be the most valuable people in marketing next.
The metrics post gives the session its numbers: pipeline sourced by marketing, CAC versus LTV, marketing ROI and lead-to-customer conversion.
It also notes that clean data is painful enough that teams track clicks instead.
For a session aimed at proving operations' revenue contribution to a CFO or CRO audience, this framing is ready to use.
The trade-off is the stack and architecture question.
James Silvestri's posts present AI as a force that raises the status of analysis and strategy; they do not ask what becomes the center of the MarTech stack, what AI replaces in automation, or where lead scoring, nurture, attribution and orchestration fit.
A campaign for an audience seeking a platform-level reset — and the hiring distinction among operations, GTM engineering and marketing engineering — gets the metrics discipline, but not the stack argument, from these posts.
Choose Sonnia Hove for a campaign on foundational operations craft or hiring and team-building, rather than forward-looking trends.
Read more
The post series lists the habits the role rests on — analytical thinking about where technology can solve a problem, rigor about process, and the ability to lead without direct reports — while the other post offers a detailed recommendation of a martech recruiter who understands the marketing-and-technology cross-section. For a session on building or staffing an operations function, this is directly usable material.
For a campaign about how AI is changing the marketing operations job, these posts are a dated base: they were published in April and August 2021, before today's AI-driven stack questions, and do not address AI, the MQL and lead-scoring debate, attribution or recent platform changes.
One of the two is a recruiter recommendation rather than an argument about the field.
For a brand seeking a practitioner to speak to 2026 trends, ask for current examples and framing to complement these pre-AI fundamentals.
This profile discusses three LinkedIn posts by Moni Oloyede: an analysis of roughly 100 marketing operations job descriptions, an argument about what account-based marketing requires, and a position statement on AI and the future of marketing automation.
The posts carry no publication dates; two reference live events on October 15 and November 4.
The longer article linked from the job-description post was not available, so its role-by-role skill breakdown cannot be described.
Three other marketing operations writers each have two LinkedIn posts.
Moni Oloyede's posts do not include sponsorship terms, pricing, audience demographics, or post-level engagement figures, so campaign fit is judged on the arguments in the posts rather than on performance data.
