Marc Okeon works in executive recruiting, helping companies hire senior marketing leaders. Their posts discuss defining the role, keeping hiring teams aligned, and using AI to support recruiting without losing focus on people.
Useful for executive recruiting content on hiring senior marketing leaders, role definition, stakeholder alignment, and AI limits.
Best for
A talent-acquisition software vendor co-marketing to startup founders and hiring teams.
Not for
Consumer-facing or non-recruiting brands wanting paid creator campaigns at scale with reach guarantees.
Key takeaways
Late-arriving decision-makers can stall a search after a likely hire is identified.
Involve people with veto power early and use an agreed role brief.
AI can speed recruiting but should not handle quality assurance, client communication, or candidate outreach.
Check first: Confirm audience data and recent post performance before committing budget.
Main ideas
The slow part of an executive search comes after the shortlist · The client is the variable recruiters cannot control · AI changes recruiting, but Okeon draws a line at certain human touchpoints
Marc Okeon writes about executive recruiting, especially hiring senior marketing leaders for startups.
Across six LinkedIn posts, they focus on the decisions that shape a search: defining the role clearly, aligning stakeholders, and keeping the hiring process moving.
They also argue that AI can make recruiting faster without replacing the human judgment and communication the work depends on.
Okeon makes recruiting-process problems concrete.
In one post, a chain of late-arriving decision-makers shows how a search can stall even after a likely hire is identified; their proposed remedy is to involve people with veto power early and use an agreed role brief to keep later feedback relevant.
Other posts turn familiar tensions into practical distinctions: a startup can need a hands-on CMO rather than a lower-level title, and a client must respond promptly for a search to succeed.
Their AI argument has a boundary too: the posts support using AI to improve recruiting, while cautioning against using it for quality assurance, client communication, or candidate outreach.
Not every post is a process lesson: an Inkitt example describes using a show trailer to help attract candidates by making the company’s work compelling.
Readers interested in how executive hiring works—and where hiring teams can help or hinder it—will find specific examples and a consistent focus on execution.
Marc Okeon works in executive recruiting for senior marketing roles, and their posts return to one argument: finding candidates is not the hard part of a search.
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Okeon says their firm identifies the person who ultimately gets hired within two weeks in most searches; the real difficulty lies with clients — stakeholders re-arguing the role, hiring teams that go quiet or keep changing the spec, and fees and habits inherited from a slower era.
They see AI as changing what good recruiting looks like, not replacing recruiters, and name specific tasks they keep away from it.
Two further priorities recur: seniority does not tell you whether a hire will actually do the work, and a client's product is often its strongest pitch to candidates.
The slow part of an executive search comes after the shortlist
Okeon says their firm identifies the person who ultimately gets hired within two weeks in 84% of searches, so sourcing is not the bottleneck.
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The delay comes from the chain of people who want to weigh in — the CEO, then the COO, then the board chair, then a lead investor's operating partner.
Their method is a written pitch document spelling out exactly what the company is hiring for.
When a new stakeholder raises a weakness, Okeon points back to the agreed criteria instead of reopening the search.
They treat a genuinely evolving spec as legitimate, but distinguish it from late opinions that stall a strong candidate.
A stakeholder objects to a finalist on a point the role never required. Okeon replies that the role called for four specific things and the candidate has shown they can do them well.
The client is the variable recruiters cannot control
Okeon says every search depends on three things: their team, the talent market, and the client.
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The first two are known quantities: the firm says it completes 90% of searches in four to six weeks, and past volume lets it predict candidate supply and response rates from a spec.
The client, by contrast, is unpredictable.
As in a relay race, if the client goes quiet, takes two weeks to give feedback, or keeps changing the spec, the baton drops no matter how fast the recruiter runs.
Okeon contrasts clients who are prepared, responsive, objective, and quick to move on a strong candidate with those whose delays erase the advantage of a fast pipeline.
AI changes recruiting, but Okeon draws a line at certain human touchpoints
Okeon does not expect AI to take over recruiting, but expects it to change what successful recruiting looks like.
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They pitched a conference session built on a framework tested with more than 100 senior marketing leaders, covering how their team uses AI and, just as importantly, where it deliberately does not: quality assurance, client communications, and candidate outreach, which they identify as human touchpoints.
In 2026, Okeon published the pitch for an SXSW session, 'Why Your AI Strategy Is Actually a Talent Strategy,' framing AI as a way to make recruiting faster and smarter without losing focus on people.
The traditional 33% fee is a leftover from a slower era
Okeon argues that paying a recruiter 33% of a candidate's total cash compensation is a rip-off in 2026.
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They cite market figures — Korn Ferry up 25% that year, Heidrick & Struggles taken private for $1.3 billion, and the top 50 executive search firms at $6.7 billion in fee revenue — as proof of demand, not fair pricing.
They trace the 33% figure to an era of phone-based sourcing, faxes, and heavy overhead.
With candidates on LinkedIn and AI-assisted identification, Okeon argues, clients should share the efficiency gains, not just recruiters.
Okeon reads the industry's growth not as validation of its pricing, but as evidence that clients are paying a legacy rate.
Okeon's cost argument sits in tension with their other stance: they frame AI as a reason fees can fall, yet insist it should stay out of quality assurance, client communications, and candidate outreach.
Seniority does not tell you whether a hire will actually do the work
Okeon says almost every startup asks for a 'hands-on player/coach,' usually because a previous big-company manager disappointed them.
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They then overcorrect, asking for a senior manager or director while describing a CMO- or VP-level function.
Okeon argues the conventional mapping — senior manager or director as hands-on, CMO or VP as hands-off — is simply wrong: plenty of senior executives are comfortable doing the work.
Because résumés rarely show the difference, their team screens for operating ability by knowing which companies tend to produce hands-on operators and making the role's scope explicit to candidates before they reach the client.
Okeon's shorthand for a hands-on senior hire: if the CRM breaks on Tuesday, they can fix it by Wednesday.
A client's product is often the best pitch to candidates
Okeon argues that the best clients have a product that sells candidates on them, so recruiting outreach should show what the company actually makes.
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For Inkitt, an entertainment startup, their team attached a link to one of the company's show trailers when messaging candidates about roles in CRM, AI video production, business operations, and product management.
Candidates reportedly said they had not planned to respond until they saw the video, which prompted a call.
This post directly answers how Marc Okeon thinks about AI in executive search, the core topic of a campaign about executive search.
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Start here to see the framework they pitch and where they draw the line on AI use.
Marc Okeon argues that AI will not replace recruiting but will change what successful recruiting looks like.
They describe a SXSW session pitch built around a framework tested with 100+ senior marketing leaders and informed by their team's use of AI.
They also explain where their team does not use AI: QA, client communications, and candidate outreach.
The post clearly states their public position on AI-assisted recruiting.
For brands planning a campaign
A recruiting or talent tech company could build a co-marketing webinar around this tested framework. The post names the topic and audience, making it a natural collaboration anchor.
This is the clearest explanation of where searches fail and why the client's behavior matters.
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It answers the question 'What does Marc Okeon expect from a hiring team?' before a campaign conversation.
Marc Okeon breaks every search into three dependencies: their team, the talent market, and the client.
They say the first two are known quantities: Right Side Up completes 90% of searches in 4–6 weeks.
The client is the biggest unknown.
They compare recruiting to a relay race: if the client goes quiet, takes two weeks to give feedback, or keeps changing the spec, the baton hits the ground.
Their best clients are prepared, responsive, objective, and quick to act.
For brands planning a campaign
For a startup-founder audience, this post supports content on how to be a good hiring client. A talent tech company could co-create a checklist or webinar around the relay-race metaphor and the three dependencies.
This post lays out Marc Okeon's case for a more efficient, AI-supported search model and offers a starting point for understanding their pricing stance and competitive positioning.
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Marc Okeon says the executive search market is booming — Korn Ferry up 25%, Heidrick & Struggles going private for $1.3B, and the top 50 executive search firms hitting $6.7B in fee revenue — but argues clients should not have to pay the traditional 33% fee.
They call that rate a remnant from when recruiters hired offices of people to work phones and send faxes.
Today, they say, every candidate is on LinkedIn and the smartest recruiters combine market expertise with AI to identify them faster.
For brands planning a campaign
A talent tech company can use this as a debate hook: AI-driven efficiency versus legacy search fees. The post offers concrete market data points for a co-marketing report or webinar.
This explains a common startup hiring mistake and how Marc Okeon screens for hands-on senior operators.
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It answers 'What does Marc Okeon look for in marketing leadership hires?'
Marc Okeon writes that almost every startup says it wants a hands-on player/coach, but usually means its last big-company manager gave it PTSD.
They describe startups asking for a senior manager or director while outlining a CMO- or VP-level function.
They argue that senior manager/director does not equal hands-on, and CMO/VP does not equal hands-off; plenty of CMOs and VPs can fix a broken CRM on Tuesday and have it running by Wednesday.
Their team screens for hands-on operators and knows which companies produce them, even when resumes do not show it.
For brands planning a campaign
For a recruiting or talent tech platform, this post supports content on writing accurate role specs and avoiding overcorrection. A co-marketing webinar could focus on how founders should define the role before searching.
This post shows what happens after the shortlist — the part Marc Okeon says takes the longest.
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It answers 'How does Marc Okeon manage multiple decision-makers?' and shows their process discipline.
Marc Okeon opens with a chain of requests: the CEO, then the COO, then the board chair, then a lead investor's operating partner.
They say 84% of their searches identify the person who ultimately gets hired within two weeks; everything after that takes the longest.
They understand stakeholders need to weigh in, but prefer to get anyone with veto power into kickoff and calibration calls.
When that does not happen, they use a detailed pitch doc spelling out what the role requires.
If a stakeholder later raises an unrelated weakness, they point back to the agreed spec.
Specs can evolve, but bogging down means missing top talent.
For brands planning a campaign
This is a strong co-marketing angle for executive search process alignment. A talent tech company could partner on content that teaches hiring teams to run stakeholder rounds without losing candidates.
Keeping executive hiring teams aligned after the shortlist
Okeon says the fastest part of an executive search is finding the candidate: their firm identifies the person who ultimately gets hired within two weeks in 84% of searches.
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The slow part is everything afterwards, when a COO, a board chair, and an investor's operating partner all want to meet the finalists.
They write a detailed pitch document setting out exactly what the company is hiring for, share it with each new stakeholder, and use it to steer evaluations back to the agreed criteria.
They consider changing a spec legitimate, but distinguish it from letting late opinions stall a good candidate.
A written pitch document defining the role, plus kickoff and calibration calls that ideally include anyone with veto power.
For brands planning a campaign
Useful for a recruitment or talent-software brand as webinar or article material: how hiring teams keep a shared spec and alignment tools intact while AI and faster sourcing compress the front end of the search. It frames software as protecting decision quality, not just speed.
AI in recruiting, with places it should not be used
Okeon does not expect AI to take over recruiting, but expects it to change what good recruiting looks like.
Read more
They pitched an SXSW session, “Why Your AI Strategy Is Actually a Talent Strategy,” built on a framework their team has tested with more than 100 senior marketing leaders. The session covers both how Right Side Up uses AI and where it deliberately does not, naming quality assurance, client communications, and candidate outreach as human touchpoints.
A framework tested with more than 100 senior marketing leaders and presented in a conference session format.
For brands planning a campaign
The posts offer a clear collaboration hook: Okeon has a tested framework and a speaking format on AI-assisted executive search. Their “where we don't use AI” angle gives a co-marketing webinar or content series a differentiated, human-centred position rather than generic automation messaging.
Okeon says almost every startup their firm works with asks for a “hands-on player/coach,” usually because a previous senior hire from a large company was a professional manager rather than a doer.
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They argue that the common equation of senior manager or director with hands-on, and CMO or VP with hands-off, is wrong. Résumés rarely reveal the difference, so their team screens for it by knowing which companies tend to produce hands-on operators and ensuring candidates understand the role's scope before they reach the client.
Screening based on which companies tend to produce hands-on operators, plus explicit scope conversations with candidates before client introductions.
Okeon notes that many large-company CMOs and VPs can hire and build teams but cannot do the work themselves, while others are entirely comfortable doing it.
For brands planning a campaign
A talent platform, assessment vendor, or sourcing tool could build content around calibrating the role spec and screening for operating ability at senior level. Okeon also says they will push back on a client's stated role requirements, which matters if a partner expects an endorsement of an assessment or sourcing product.
Okeon argues that the best clients have a product that sells candidates on them.
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One example is Inkitt, an entertainment startup with $117 million raised and backing from Khosla, Kleiner Perkins, and NEA.
Inkitt's model tests ebook manuscripts against 1,200 signals, and they say a new title crosses $1 million in sales every seven days.
For open roles across CRM, AI video production, business operations, and product management, Right Side Up attaches a link to one of Inkitt's show trailers in candidate outreach.
They say candidates have replied that the video was why they agreed to a call.
Including a produced show trailer in outbound candidate outreach to convey the client's product quality.
For brands planning a campaign
Supports a case study or co-created content piece with a video, employer-brand, or recruiting-marketing platform on how produced assets lift candidate response rates. Ask for examples beyond the one named client relationship.
Client responsiveness as the unpredictable part of a search
Okeon describes every candidate search as having three dependencies: their team, the talent market, and the client.
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They say their team completes 90% of searches in four to six weeks, and that past volume lets them predict candidate supply and response rates from a spec.
The client is the variable they cannot control.
They use a relay-race analogy: if the client goes quiet, takes two weeks to give feedback, or keeps changing the spec, the baton drops no matter how fast their team runs.
Relay-race analogy for the handoff between recruiter and client, supported by Right Side Up's reported search volume and completion times.
For brands planning a campaign
A ready-made argument for hiring-process software: feedback tools, scheduling, and spec management as the client-side half of the race. For a partnership, the product can be positioned as complementary to Okeon's sourcing work rather than competitive.
Okeon argues that paying a recruiter 33% of a candidate's total cash compensation is a rip-off in 2026.
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They cite market figures — Korn Ferry up 25% that year, Heidrick & Struggles taken private for $1.3 billion, and the top 50 executive search firms at $6.7 billion in fee revenue — as evidence of demand, not fair pricing. They trace the 33% figure to an era of phone-based sourcing, faxes, and heavy overhead, and argue that with candidates on LinkedIn and AI-assisted identification, the efficiency gains should reach clients as well as recruiters.
For brands planning a campaign
An alternative recruitment model, talent marketplace, or sourcing tool has an obvious co-marketing angle: Okeon is publicly contesting incumbent pricing and willing to make the market argument. Their framing of AI primarily as cost reduction may not suit a premium product positioning.
Marc Okeon's posts show a business affiliation and a named client.
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They write as part of Right Side Up, the recruiting firm behind the executive searches they describe, and name Inkitt as a startup their team is actively hiring for. A separate post pitches a SXSW session, a proposed appearance rather than an established partnership.
Right Side Up
Employment
Okeon writes as part of Right Side Up, the recruiting firm behind the searches they describe.
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They refer to "my team at Right Side Up" and to the firm's track record: "We've filled 100s of roles... completing 90% of searches in 4-6 weeks."
Okeon describes Inkitt as a client their team is hiring for, naming open roles in CRM, AI video production, business operations, and product management.
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They explain how the team uses an Inkitt show trailer in candidate outreach, and relay Inkitt's funding and use of AI to evaluate manuscripts.
Marc Okeon writes about executive recruiting, mostly for senior marketing roles at startups and growth-stage companies.
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Their posts argue that finding candidates is not the hard part: their firm identifies the eventual hire within two weeks in most searches, while the real difficulty lies on the client side, where stakeholders re-argue the role, feedback stalls, or the spec keeps changing.
Start with posts about keeping a hiring team aligned behind a written spec and the three-dependency framing of a search.
Then read their views on where AI belongs in recruiting, the argument against the traditional 33% fee, the case that seniority tells you nothing about whether a hire will do the work, and using a client's own product for candidate outreach.
Two ideas recur: hiring failures are usually decision failures rather than sourcing failures, and technology's efficiency gains should reach clients, not only recruiters.
Jain writes about the same core recruiting bottleneck as Okeon: the best candidates for a hard role are usually not the ones who apply.
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Both argue recruiters have to search beyond the inbound pile and the obvious keyword match, and describe AI as a tool that changes sourcing rather than replacing recruiters' judgment.
Jain's examples come from niche and technical hiring in India, where the problem is a specific skill such as ObjectARX or a particular ERP implementation, and only a small set of companies employ it at scale.
Okeon works on senior marketing and executive roles in the United States.
While Jain is extending sourcing into a full hiring platform, Okeon draws a line around quality assurance, client communications, and candidate outreach as work that should stay human.
Flesher treats hiring as a process problem rather than a sourcing problem, close to Okeon's argument that the candidate was usually findable and the process is what fails.
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Both offer concrete operational advice: define the criteria up front, screen consistently against them, and pay attention to why people leave.
Flesher writes from inside the hiring process, covering screening buckets, interview coordination, and exit-interview patterns for HR and hiring managers.
Okeon writes from the outside as a search firm, focusing on stakeholder alignment at the finalist stage, fee economics, and how a client's own product sells candidates.
Flesher's posts offer practical process guidance from 2024; Okeon's provide market and pricing commentary from 2026.
Trieu writes about shifts in the hiring market and what employers should do in response, territory Okeon also covers when arguing that changed conditions should change fees and process.
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Both publish structured, list-driven takes on where recruiting is heading and explore how AI is reshaping applications and screening.
Trieu takes a macro view: how a prolonged geopolitical conflict would reallocate headcount toward cybersecurity, energy, and supply chain, and how AI-generated applications push hiring toward work samples and skills verification. Okeon focuses on the search itself, asking who controls the decision after the shortlist and what a fee should cost.
The LinkedIn account shows 8,838 followers, recorded on 8 October 2026 — a modest following for a B2B creator, and the only audience number available.
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Posts published from 7 July to 5 October 2026 address startup founders, their hiring teams, and recruiting or talent leaders.
Topics include defining a senior marketing role before a search starts, keeping a multi-stakeholder hiring group to the original spec, the value of hands-on operator experience at VP and CMO level, why a 33% search fee is obsolete, and where AI should and should not be used in recruiting.
Buyers hiring executive marketing talent will recognize their concerns in these posts, but the content does not establish who makes up the follower base.
Before committing budget, ask Okeon for audience survey results or platform data on geography, age, and gender, plus recent post-level performance on executive search and AI-assisted recruiting.
If professional role, employer, or job seniority matters, ask specifically for survey results or another source covering those attributes.
LinkedIn followers
8,838
LinkedIn profile for Marc Okeon, as recorded in the account data · 2026-10-08
The posts do not describe a sponsorship or paid partnership offering from Marc Okeon.
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Their content is recruiting commentary and client work, including work for entertainment startup Inkitt: helping fill roles in CRM, AI video production, business operations and product management, and visiting Inkitt’s San Francisco office.
This is a client-service relationship, not a bookable influencer sponsorship package.
No pricing, deliverable specs, media kit or official partnership inquiry route appears in the posts.
For a recruiting or talent tech company seeking startup-founder reach through a webinar or content collaboration on executive search and AI-assisted recruiting, ask Okeon directly whether they take on co-marketing and request any available pricing and materials.
Campaign A: a talent-acquisition software vendor wants to reach startup founders and the hiring teams staffing their first senior marketing roles through a co-marketing webinar or short content series on AI-assisted executive search.
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Marc Okeon is a strong fit for this campaign, with one structural caveat.
They already own the topic.
Their posts include a framework tested with more than 100 senior marketing leaders and pitched as an SXSW session, “Why Your AI Strategy Is Actually a Talent Strategy,” built around how Right Side Up uses AI and where it deliberately does not — quality assurance, client communications, and candidate outreach.
That gives a technology partner a differentiated, human-centred position instead of generic automation messaging, with talking points the partner would not have to provide.
They also write directly for the buyer.
The posts address founders and hiring teams on defining a senior marketing role before the search opens, the post-shortlist round where a COO, board chair, and investor’s operating partner all want to weigh in, and the relay-race argument that client responsiveness is the one variable a recruiter cannot control.
Any of those could anchor a webinar segment.
The concrete material — pitch-document discipline, the four-to-six-week search window, and screening for operators rather than professional managers — belongs on an agenda a talent-tech vendor would sponsor.
Reach is modest: 8,838 LinkedIn followers, recorded 8 October 2026.
There are no demographics, audience survey, engagement figures, or per-post performance in the posts, and only one channel.
Plan this as a segment-targeted collaboration built on subject authority, not a volume play.
Build the collaboration as a co-marketing conversation rather than a booking: no sponsorship formats, rate card, deliverable specification, or partnership inquiry route appears in the posts, and no formats are listed in the partnerships section.
One caution: their public attack on the 33% fee as a fax-era leftover is a strong hook, but a vendor selling premium search software should decide in advance whether it wants that argument attached to its brand.
When to choose a specialist
Campaign B: a consumer-facing brand, or a non-recruiting business, wants a paid creator campaign at scale — sponsored posts with a defined reach target, an audience-demographic guarantee, and CPM or view commitments.
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The posts do not support this campaign.
There is nothing available to buy: no sponsorship formats, pricing, deliverable specification, or inquiry link, so the campaign would have to be invented from scratch rather than matched to an existing package.
The only audience figure in the posts is a LinkedIn follower count of 8,838.
With no demographics, audience survey, engagement, or per-post performance data, a buyer cannot confirm that the following matches a consumer target or meets a reach threshold.
The posts are on a single channel — LinkedIn text posts — with no video, audio, or visual work by Marc Okeon; the one produced asset in the posts is a client’s show trailer attached to candidate outreach, not the creator’s media.
The topical mismatch is the bigger problem.
The posts concern executive search for startups and how hiring teams make decisions: keeping stakeholders to an agreed spec, screening senior candidates for hands-on ability, where AI belongs in recruiting, and one client case.
A consumer campaign has no subject overlap with that writing, and a reader arriving from it would find no material a general lifestyle audience could act on.
This is a reasonable creator for a talent or recruiting-marketing campaign and a poor fit for mass-reach sponsorship.
Reject it for this campaign rather than test it at low budget.
A worked campaign example
Worked campaign angle for Campaign A — a co-hosted webinar and two-post content series titled “Why your AI strategy is actually a talent strategy.”
Audience: founders, CEOs, and first talent or people leads at seed-to-Series-B startups, the group Marc Okeon’s writing already addresses. Format: one 45-minute live session co-hosted by Okeon and the vendor’s founder or head of product, followed by two LinkedIn posts from their account summarising the session and linking to the recording.
Session structure, using the posts as source material.
Open on the mismatch: most startups treat AI hiring as sourcing automation, when the scarce part is what happens after the shortlist.
Okeon states that 84% of the firm’s searches identify the person who is ultimately hired within two weeks, and that the long stretch is the sequence of stakeholder rounds that follows — attribute the claim to Okeon on air rather than present it as independently audited.
Second segment: the client-side half of the search, built on the relay-race framing — the recruiter runs one leg, and a client who goes quiet, takes two weeks to give feedback, or keeps changing the spec drops the baton.
The vendor’s product fits naturally here: spec management, structured feedback, and scheduling keep the client’s leg moving, complementing Okeon’s sourcing work rather than competing with it.
Third segment: where AI should not be used — quality assurance, client communications, and candidate outreach — the line Okeon already draws publicly and the part that makes a vendor’s automation pitch credible.
Close on defining the role before searching: the overcorrection from a bad senior hire into an under-levelled job title, and screening senior candidates for hands-on ability rather than résumé titles.
Takeaway asset: a one-page senior-role spec template derived from Okeon’s pitch-document practice, hosted by the vendor as the registration follow-up and completed by attendees with their own senior-role requirements. That ties the session to the vendor’s product surface without presenting it as a live control.
Next step: no partnership route appears in the posts, so the vendor should open a direct conversation and ask for Okeon’s audience survey results and recent post-level performance on executive-search and AI topics.
Before recording, decide whether the 33% fee argument — the sharpest market hook in the posts — belongs in the session script or stays out; it may read as an attack on premium pricing generally.
The Inkitt employer-brand example is usable only lightly: it is one named client relationship, not a repeatable programme.
Jain is the stronger host if the vendor’s buyer shifts from the startup founder to the recruiting-operations or staffing leader.
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Both posts tackle the same buyer task from the recruiter’s side: how to fill niche roles that attract little good inbound, why searching the existing candidate database and adjacent experience beats waiting for applicants, and how sourcing, screening and outreach tools now sit inside a single hiring platform. A vendor selling sourcing automation or database search can put its product on screen early and demonstrate a concrete workflow—harder to do in a webinar built around executive-search judgement.
The startup founder hiring a first senior marketing leader is not the audience Jain writes for in these posts, so the premise would need to be rewritten rather than re-hosted.
The posts offer category commentary and workflow advice, not close readings of individual hiring decisions, so there is no ready-made segment on stakeholder alignment, spec discipline or judging a senior candidate’s hands-on ability.
They also discuss competitor funding and the shape of the recruiting stack, which a vendor sponsor may not want associated with its brand.
Flesher is the better choice if the campaign moves away from AI and executive-search framing and targets the fundamentals of employer-side hiring: writing a posting that explains why a candidate should want the job; running structured screening with defined deal-breakers; sorting applicants and checking salary expectations before interviewers invest time; and treating retention and exit-interview patterns as the real source of recruiting problems.
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An HR-technology vendor whose product covers screening checklists, interview structure or retention analysis, and whose buyers are smaller or non-tech employers, would give its audience practical material to use the same week.
The posts were published in January and February 2024 and say nothing about AI-assisted recruiting, executive search or startup talent markets, so they cannot carry the vendor’s current product story without a new frame.
They also name no client or candidate outcome and do not address a marketing-leader audience.
The vendor would need to supply the connection to its software rather than draw it from the creator’s existing arguments.
Trieu is the better host for a campaign built on macro risk or skills-based hiring.
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The posts lay out what happens to hiring during a prolonged geopolitical shock—slower expansion headcount, longer approval chains, more quiet roles and candidates prioritizing institutional durability over brand prestige—and argue that resumes are losing ground as employers test work samples and skills directly. A vendor positioning its product around workforce planning, skills verification or hiring under uncertainty would get a ready thesis, a numbered structure to reuse on screen and a candidate-behaviour angle that most recruiting content does not cover.
Neither post concerns startup executive search or senior marketing hires, so the proposal’s central campaign decision would need a new audience and promise.
The writing offers scenario analysis—a hypothetical war scenario and an industry trend—but no named clients, search outcomes or hiring-team decisions to examine.
The skills-based hiring argument overlaps with the AI-in-recruiting topic, but addresses a different question: what evidence employers should accept, not where AI belongs in a search.
This profile draws on six LinkedIn posts by Marc Okeon.
They cover executive-search process and late stakeholder involvement, the client side of a search, where AI belongs in recruiting, retained-fee pricing, hands-on senior hiring, and the use of a client's own product in candidate outreach.
The posts discuss 2026 market conditions.
Performance figures are Okeon's own stated numbers and are not independently verified: identifying the eventual hire within two weeks in 84% of searches, completing 90% of searches in four to six weeks, and a framework tested with more than 100 senior marketing leaders.
The SXSW session is a submitted pitch, not a delivered talk, and the posts do not include the client show materials named in the Inkitt example.
Comparators are posts by three creators writing on adjacent recruiting ground: Mehul Jain, Vicki Flesher, and Phong Trieu.
The posts do not describe sponsorship formats and pricing, a partnership inquiry route, audience demographics and per-post engagement, or any book, show, or earlier-career source.
Each module is considered on its own, but the page has not been tested with readers as a whole, compared in search, or checked in a browser.
