Lindzi Cox works with talent-acquisition teams on recruiting workflows, automation, and candidate experience. Cox says they spent 15 years in agency recruiting and joined Humanly.
Lindzi Cox is most useful for explaining recruiting workflows, candidate experience, and hiring process redesign to talent acquisition teams.
Best for
Humanly or an aligned non-competitor planning a co-marketing webinar on AI-enabled recruiting workflows.
Not for
A competing recruiting automation vendor seeking vendor-neutral analysis, guaranteed reach, or a performance fee.
Key takeaways
Cox says the candidate experience problem is silence, not AI.
Cox warns teams not to pave the cowpath by automating an inherited hiring funnel.
Cox says structured hiring can address vague role requirements, like-me bias, and overlooking capable candidates.
Check first: Confirm sponsorship terms, external webinar participation, approval process, and audience data before contacting them.
Main ideas
The candidate experience problem is silence, not AI · Automation should show up in hiring throughput, not just tooling · Don't pave the cowpath: redesign the hiring funnel
Lindzi Cox writes about recruiting operations, candidate experience, and how talent-acquisition teams use automation.
They say they spent 15 years in agency recruiting and now work with TA teams.
Their posts connect recruiters’ day-to-day workload with a broader question: should teams simply automate the hiring steps they already have, or rethink the process around more continuous, conversational interactions?
Cox combines practical recruiting frustrations with a case for changing how hiring works.
In one post, they describe candidates being ignored, then contrast silence with a structured interview and a real conversation.
In another, they challenge teams to stop “paving the cowpath”—automating an inherited funnel without asking whether its steps should exist.
They also highlight structured hiring as a way to address vague role requirements, like-me bias, and the risk of overlooking capable candidates without impressive credentials.
The mix is useful for readers interested in recruiting processes and candidate experience: it moves from a concrete operational problem to questions about fairness and process design.
Some posts promote Humanly; ask for evidence behind the operational results they cite.
Cox's recurring argument is that recruiting's core problems are process and attention, not technology.
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They push teams to respond to candidates instead of leaving them in silence, measure automation by hiring outcomes, question inherited funnel steps rather than speed them up, and free recruiters from the wrong work so they can interview and lead.
Their posts mix practitioner framing from 15 years in agency recruiting with Humanly product positioning and customer claims.
They also amplify outside experts, especially Mads Faurholt-Jorgensen on structured hiring and bias, and treat those ideas as a starting point for recruiting practice.
The candidate experience problem is silence, not AI
Cox argues that companies created the candidate experience problem by ignoring applicants, not by adopting AI.
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Their framing: the real conflict is not humans versus AI but AI versus the candidate being ignored.
Most applicants apply and hear nothing, while the best candidates accept offers elsewhere.
Cox prioritizes a real conversation over a form or keyword filter, and describes a structured, scored interview as the way to deliver it.
In a Humanly-promotional post, Cox says every candidate should get a real conversation and invites readers to try a 12-minute, fully scored Humanly interview from the candidate side. Because this is vendor material, ask for independent evidence of outcomes.
Automation should show up in hiring throughput, not just tooling
Cox draws on their agency recruiting experience to make automation concrete through operational measures.
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They say they spent 15 years in agency recruiting and know the Monday feeling of being buried in admin while a hiring manager asks why the pipeline is slow. Their reasoning: when scheduling, screening, and coordination burdens fall, the same recruiters can interview more, connect more, and hire more.
Cox cites Valet Living: 25,000 hires a year, 20,000 applications a month, and 3.5 days just to schedule a phone screen.
After working with Humanly, the post reports scheduling falling to 19 hours, hires per recruiter per month rising from 75 to 140+, and screen-to-offer conversion moving from 50% to 75%, with no new headcount.
Don't pave the cowpath: redesign the hiring funnel
Cox warns against using AI only to speed up inherited processes.
Read more
They ask what people would build if they started with a blank page today.
In talent acquisition, that means letting go of the rigid, linear funnel rather than automating each existing step.
Cox wants hiring to feel more continuous and conversational, less like a gauntlet for candidates and a bottleneck for teams.
Cox repeats the phrase 'Don't pave the cowpath' and says the most interesting work they see is quietly building something different rather than optimizing the old thing.
Cox argues that recruiting teams struggle not because the work is too hard but because too much of it is the wrong work: scheduling, screening, chasing candidates, and answering the same questions repeatedly.
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When those tasks run automatically, teams stop reacting and start leading.
They interview more, connect more, and hire better.
The underlying claim: high-performing recruiting teams do not work harder; they work on the right things.
This short post names no customer or metric. It invites readers to see the approach in practice and uses hashtags for Recruiting, RecruitingAutomation, TalentOps, and HRLeaders.
Cox amplifies Mads Faurholt-Jorgensen's TEDx talk, which argues that nobody taught us how to recruit and that people spend 10% of their time recruiting and 90% making up for recruiting mistakes.
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Cox selects three problems from the talk: hiring managers want someone good at everything instead of the best goalkeeper and best striker; people confuse a good employee with an employee like themselves; and resumes screen out strong performers without traditional pedigree.
The talk proposes structure, tools, and even algorithms—not to dehumanize hiring but to make it fairer and more effective.
Cox adds that interviewers already run biased mental algorithms that cannot be debugged or improved.
Cox highlights the talk's 'whispering talents' concept and asks readers about the most expensive recruiting mistake they have made or seen. The framework and concepts are Faurholt-Jorgensen's; Cox offers a recruiting interpretation and emphasis.
This is Cox's clearest statement of the central recruiting problem: candidates apply and hear nothing.
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Read it to understand the candidate-experience argument they bring to AI recruiting conversations.
Cox reframes the AI debate as “AI vs. the candidate being ignored,” not humans vs.
AI.
The post says most applicants get no response or next step, then presents Humanly as the opposite: “Every candidate gets a real conversation.
Not a form.
Not a keyword filter.”
It describes the conversation as a structured interview and invites readers to try a real Humanly interview in 12 minutes, fully scored, to see what a recruiting team would see.
The post promotes Humanly but offers no independent evidence for its product claims.
For brands planning a campaign
For a co-marketing webinar on AI-enabled recruiting workflows, lead with candidate silence and response rates, not generic AI efficiency. A 12-minute candidate-side demo or scored interview walkthrough could be the live hook; label it as a vendor demo, not neutral research.
This post connects Cox's agency recruiting background to a vendor case study, with concrete before-and-after numbers.
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It shows why a recruiting team might trust their claims.
Cox opens with the feeling of starting a Monday buried in admin while a hiring manager asks why the pipeline is slow.
They cite Valet Living: 25,000 hires a year, 20,000 applications a month, and 3.5 days just to schedule a phone screen.
After working with Humanly, the post claims scheduling fell from 3.5 days to 19 hours, hires per recruiter per month rose from 75 to 140+, and screen-to-offer conversion rose from 50% to 75%, with the same team and no new headcount.
Cox says this is why they joined Humanly.
The post does not independently verify the numbers.
For brands planning a campaign
Use this as the operational proof narrative for a webinar: one recruiter-level pain point, one before-and-after metric, and a walkthrough of what changed. Attribute the Humanly outcomes to Cox's post; don't present them as independent benchmark data.
This is Cox's clearest argument for redesigning recruiting instead of speeding up inherited steps.
Read more
Read it for the more conceptual side of their AI and talent-acquisition thinking.
Cox repeats the phrase “Don't pave the cowpath” and asks what people would build “if we started with a blank page today.”
In talent acquisition, they say, that means letting go of the rigid, linear funnel rather than automating each existing step.
They ask whether hiring could be “more continuous, more conversational, less like a gauntlet for candidates and a bottleneck for teams,” and note that the most interesting work is quietly building something different rather than optimizing the old thing.
The post is an idea prompt, not a product claim or case study.
For brands planning a campaign
This offers a stronger thought-leadership frame for a webinar: redesign the process around conversation and candidate experience instead of just making the old funnel faster. Ask attendees to name one inherited step they would remove, not automate.
This short post states Cox's diagnosis of recruiter overload and the shift they promise through automation.
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It's a quick starting point for the “wrong work” argument.
Cox says recruiters are drowning not because the work is too hard, but because too much of it is the wrong work: scheduling, screening, chasing candidates, and answering the same questions repeatedly.
Automating those tasks, they say, lets teams stop reacting and start leading, interview more, connect more, and hire better.
The post invites readers to see it in practice and uses hashtags for Recruiting, RecruitingAutomation, TalentOps, and HRLeaders.
It offers no named example or metric.
For brands planning a campaign
Use this as a short opening pain point for a TalentOps or HR-leader audience. Pair it with a concrete case or demo from another post; this post lacks specifics and isn't proof.
This post shows which recruiting ideas Cox amplifies and how they turn an external talk into a practical discussion.
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Read it to understand the structured-hiring argument behind their automation views.
Cox summarizes a TEDxWarwick talk by Mads Faurholt-Jorgensen around the line "Nobody taught us how to recruit," and the statistic "People spend 10% of their time recruiting, 90% making up for recruiting mistakes."
Cox highlights three points: hiring managers often want someone good at everything, but teams need the best goalkeeper and the best striker; people confuse a good employee with an employee like themselves, so analytical people hire analytical people and optimize for comfort rather than performance; and resumes screen out "whispering talents" who perform well without pedigree.
Cox says the solution is structure, tools, and even algorithms, not to dehumanize hiring but to make it fairer and more effective, and notes that people already run biased mental algorithms that cannot be debugged.
Cox links to the 18-minute talk and asks readers about their most expensive recruiting mistake.
This is Cox's summary of the talk, not a transcript of the talk itself.
For brands planning a campaign
This supports a webinar segment on structured hiring: role scorecards, separating must-have skills from nice-to-haves, and reducing like-me bias.
Attribute the framing to Cox's summary of Faurholt-Jorgensen's talk.
If the webinar needs direct quotes, ask for the original video transcript.
Approach: product-led commentary grounded in agency experience5
Candidate experience as an operational failure, not an AI problem1
Recruiting automation measured through before-and-after hiring metrics1
Automate the wrong work so recruiters can lead1
“Don’t pave the cowpath”: rethink the hiring funnel rather than speed it up1
Structured hiring, bias reduction and “whispering talents”1
Candidate experience as an operational failure, not an AI problem
Lindzi Cox argues that AI didn’t create the candidate experience problem; ignoring candidates did.
Read more
The post describes applicants hearing nothing while top candidates accept offers elsewhere, then contrasts that silence with Humanly’s promise of a real conversation and a structured, scored interview rather than a form or keyword filter.
A direct contrast and product demo invitation: “It’s not humans vs.
AI.
It’s AI vs. the candidate being ignored.”
This post promotes Humanly and includes a trial link; use it for positioning, not independent proof of outcomes.
For brands planning a campaign
A co-marketing webinar on AI-enabled recruiting workflows could use this as the candidate-experience segment: response time, communication gaps and structured interviews. Humanly’s demo link shows intended positioning, so treat product claims as vendor material, not neutral evidence.
Recruiting automation measured through before-and-after hiring metrics
Cox says they spent 15 years in agency recruiting and draws on that background to frame a Valet Living customer story: 25,000 hires a year, 20,000 applications a month and 3.5 days just to schedule a phone screen.
Read more
After Humanly, the post reports scheduling time falling to 19 hours, hires per recruiter rising from 75 to 140+ per month, and screen-to-offer conversion increasing from 50% to 75%, with no new headcount.
Practitioner perspective and a before-and-after case study with concrete operational metrics.
The metrics come from one customer story and are presented as Humanly results. Ask for evidence before treating them as generalizable outcomes.
For brands planning a campaign
The webinar could focus on measurable automation outcomes—time to schedule, recruiter capacity and conversion—and discuss how those metrics are defined and verified. Cox’s agency background makes them a credible practitioner voice, but the figures are company-reported outcomes.
Cox says recruiters are drowning not because the work is too hard, but because too much of it is the wrong work: scheduling, screening, chasing candidates and answering the same questions.
Read more
The post says automation lets teams stop reacting and start leading, interviewing more, connecting more and hiring better.
Problem reframing: “High-performing recruiting teams don’t work harder. They work on the right things.”
For brands planning a campaign
A webinar could focus on capacity shifts and change management: ask attendees to identify the wrong work in their process, then show where automation frees recruiters to interview and connect with candidates. This is a strong discussion prompt, not a standalone ROI claim.
“Don’t pave the cowpath”: rethink the hiring funnel rather than speed it up
Cox cautions against using AI only to speed up inherited processes.
Read more
The post asks what teams would build from a blank page today and applies that question to talent acquisition: let go of the rigid, linear funnel, question whether its steps should exist, and move toward hiring that feels more continuous and conversational. Cox says the most interesting work they see involves quietly building something different rather than optimizing the old thing.
Metaphor and open-ended question: “Are you paving, or are you starting over?”
For brands planning a campaign
The webinar could contrast automating an existing funnel with redesigning the hiring process. That gives the session a strategic frame beyond tooling and positions structured, conversational interviews as a process-design choice.
Structured hiring, bias reduction and “whispering talents”
Cox comments on a Mads Faurholt-Jorgensen TEDx talk and highlights three recruiting problems: teams struggle to identify actual role needs, confuse “good employee” with “employee like me,” and screen out strong candidates without traditional pedigree by relying on resumes.
Read more
The post advocates structure, tools and even algorithms—not to dehumanize hiring, but to make it fairer and more effective—and notes that interviewers already run biased mental algorithms that cannot be debugged or improved.
Commentary on another speaker’s talk, selecting resonant points and translating them for recruiting practice.
The core concepts come from a third-party TEDx talk; Cox offers the recruiting interpretation and emphasis, not the original framework.
For brands planning a campaign
A webinar could cover structured evaluation, role-need definition and bias reduction, alongside an honest debate about where algorithms help and where they need scrutiny. Cox is synthesizing another speaker’s framework, so attribute the ideas to the original talk and position Cox as the practitioner commentator.
Approach: product-led commentary grounded in agency experience
Cox combines practitioner framing from agency recruiting with Humanly product positioning, customer outcomes, and commentary on broader recruiting ideas.
Read more
They use short LinkedIn posts to mix direct arguments, before-and-after metrics, thought-leadership commentary, and calls to try a Humanly interview or ask for a demo.
Short-form social proof and argument: personal history, customer story, contrast and call to action.
For brands planning a campaign
For a co-marketing webinar, Cox can bridge practitioner frustration and vendor solution framing. The strongest angle is a conversation about why recruiting teams are stuck doing the wrong work and how structured, automated workflows change the candidate and recruiter experience.
For the practical argument, start with the posts on candidate silence and recruiters drowning in the wrong work: both argue that recruiting problems stem from process and attention rather than AI itself.
The Valet Living post offers the case-study side, with before-and-after hiring metrics attributed to Humanly, the recruiting software company they promote.
For the conceptual side, read the "don't pave the cowpath" post, which asks whether the inherited hiring funnel should exist at all, and the commentary on Mads Faurholt-Jorgensen's TEDx talk, which highlights role definition, likeness bias, and screening out strong candidates without traditional pedigree.
Readers focused on structured hiring and bias reduction will find the most substance in the TEDx commentary; those seeking automation evidence and vendor positioning will find it in the metrics and candidate-experience posts.
They write short LinkedIn posts that mix personal agency-recruiting history, product promotion, customer outcomes, and commentary on other people's work, so expect promotional framing alongside the argument.
Donner writes about the same territory Cox covers from inside a recruiting software company: how candidates are treated during hiring, why companies lose good applicants, and what a more candidate-centred process would look like.
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Both treat silence and poor feedback as a brand problem, not just an administrative one.
Donner's argument is more confrontational about the profession itself: they call for moving away from the term human resources and from recruitment toward candidate sales, and for giving candidates concrete rejection feedback. Cox stays closer to recruiting operations and tooling, framing automation as the fix without pushing to rename or redefine the HR function.
Lokey treats the candidate and employee experience as a human moment that recruiters and hiring managers can easily degrade through distraction or haste, warning that the damage affects how people see the employer's brand.
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That concern for how the process feels to the person on the other side also runs through Cox's candidate-silence post.
Lokey writes reflective, story-led pieces, using the starfish parable and cited research to argue that managers and human advisers still matter more than AI career tools. Cox writes shorter product-and-metrics posts about recruiting operations, making Lokey the better follow for career development and empathy, and Cox the choice for recruiting automation.
Jain builds and writes about AI recruiting software, covering the same broad shift Cox describes: AI moving from single tasks such as notes or screening into larger parts of the hiring process.
Read more
Both explain that shift through their own company's product history and what customers said they needed.
Jain concentrates on sourcing and search: finding passive or adjacent-experience candidates, searching an agency's own database, ranking shortlists, and covering industry funding moves.
Cox focuses on candidate experience, interview structure, and scheduling and screening volume.
Follow Jain for sourcing mechanics and market watching; Cox for candidate-facing process and throughput claims.
Cox has not published sponsorship or partnership formats.
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They promote Humanly, a recruiting automation company, with an invitation to try a Humanly interview and an offer to show the product in practice.
A Valet Living customer story supports Humanly’s recruiting results.
For a co-marketing webinar, treat them as a possible Humanly-side subject-matter voice, not an independent creator with a published sponsorship menu.
Before planning, ask whether they participate in external webinars, who handles approval, and what audience reach, content assets, or promotion commitments they can provide.
Good fit if the company is Humanly or an aligned non-competitor, and Lindzi Cox appears as a practitioner subject-matter voice rather than an independent creator with a published sponsorship menu.
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Brief
A talent acquisition software company wants a co-marketing webinar on AI-enabled recruiting workflows.
Reasons
Cox's posts address the brief directly: candidate silence, recruiting automation, scheduling bottlenecks, recruiter capacity, funnel redesign, and structured hiring.
Cox brings an agency recruiting background: their post says they spent 15 years in agency recruiting and connects that experience to a before-and-after recruiting operations story.
Cox has a clear point of view to carry a webinar, not just a product panel: 'Don't pave the cowpath,' 'high-performing recruiting teams don't work harder, they work on the right things,' and 'AI vs. the candidate being ignored.'
Cox's posts offer concrete webinar material: 3.5 days to 19 hours for scheduling, 75 to 140+ hires per recruiter per month, and 50% to 75% screen-to-offer conversion. The figures are company-reported in Cox's post and could prompt discussion if labeled as vendor-reported outcomes.
Cox also amplifies third-party recruiting ideas, such as the Mads Faurholt-Jorgensen TEDx talk, supporting a structured-hiring segment rather than a pure product pitch.
Conditions
Cox promotes Humanly in their posts, including a trial link and a demo invitation. A competing recruiting automation vendor should treat this as a conflict, not neutral creator inventory.
Cox's posts don't publish a sponsorship policy, rate card, or history of external webinars. Ask whether they participate in external webinars, who approves participation, and what promotion or content assets they can provide.
Audience composition and post engagement aren't documented in Cox's posts. Don't promise reach or audience quality without separate evidence.
When to choose a specialist
Poor fit based on Cox's posts.
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Brief
A recruiting software company wants Lindzi Cox to act as an independent, vendor-neutral analyst comparing five AI recruiting platforms in a buyer's guide, with guaranteed audience reach and a performance fee.
Reasons
Cox's posts promote Humanly rather than offer vendor-neutral analysis. One invites readers to try a Humanly interview; another says Cox joined Humanly.
The outcome numbers in Cox's posts come from their coverage of one customer story; they aren't independently verified there.
Cox's posts don't provide sponsorship terms, a rate card, an inquiry route, or audience data. They don't support a performance fee or reach guarantee.
The reviewed format is short LinkedIn commentary, not long-form comparative research or analyst-grade platform evaluation.
Cox's third-party commentary offers useful interpretation, but it summarizes another speaker's talk rather than independently testing recruiting platforms.
A worked campaign example
Angle
Open with the candidate-experience problem, move from measurement to workflow redesign, and close with structured evaluation. Ask attendees to examine one inherited hiring step and decide whether to automate, remove, or redesign it.
Call to action
Invite attendees to bring one current workflow step and leave with a decision: automate, redesign, or remove. Offer a candidate-side interview walkthrough as an optional follow-up, clearly labeled as a product demo.
Format
45-minute live webinar: a 20-minute practitioner segment by Cox, a 15-minute process or product walkthrough, and 10 minutes of audience Q&A. Label the walkthrough as a vendor demonstration, not neutral research.
Next step
Before planning, confirm whether the sponsor is Humanly or a non-competitor, whether Cox can join external webinars, who approves participation, and what audience, content, or promotion commitments they can make. If the sponsor competes directly with Humanly, treat this as a poor fit unless you agree on a different, non-promotional role.
Segments
Evidence
Cox argues that AI didn't create the candidate experience problem; ignoring candidates did. Most applicants hear nothing, and strong candidates accept offers elsewhere.
Ask attendees where their own process goes silent: application received, screen scheduled, interview feedback, or offer decision.
Evidence
Cox cites a Valet Living customer story: 25,000 hires a year, 20,000 applications a month, 3.5 days to schedule a phone screen, then 19 hours after Humanly; hires per recruiter rose from 75 to 140+ per month, and screen-to-offer conversion from 50% to 75%.
Treat these as company-reported figures, not benchmark data. Discuss how attendees define time-to-schedule, recruiter capacity, and conversion—and where those definitions differ.
Evidence
Cox says recruiters are drowning in the wrong work: scheduling, screening, chasing candidates, and answering the same questions repeatedly.
Ask attendees to list the repeated tasks in their week and mark which should run automatically, which should be redesigned, and which should stay human.
Evidence
Cox warns against using AI only to speed up inherited processes. They ask what teams would build from a blank page today and describe a more continuous, conversational hiring process instead of a rigid linear funnel.
Pick one step in the current hiring funnel and ask whether it should exist at all. This shifts the webinar from tooling to process design.
Evidence
Cox highlights three recruiting problems from a Mads Faurholt-Jorgensen TEDx talk: teams struggle to identify actual role needs, confuse a good employee with someone like themselves, and screen out strong candidates without traditional pedigree.
Attribute the framework to the original talk, then have Cox translate it into recruiting practice: role scorecards, must-have versus nice-to-have skills, and structured interviews.
Title
From silence to structured conversation: where AI recruiting should start
When the sponsor wants a recruiting agency operator's perspective on candidate experience and process change rather than an AI workflow specialist.
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Donner argues that HR often treats candidates poorly, rejected candidates deserve concrete feedback, and recruiting should shift to a candidate-centred sales approach.
A webinar on fixing candidate silence and rejection experiences before introducing automation would make good use of these ideas.
Donner also details Neohunter's tool stack, including Recruit CRM, Notion, Slack, Loom, and Zapier, offering a practical recruiter-tooling segment.
Donner's posts, dated 2020 and 2023, discuss candidate feedback, HR culture, and agency hiring practices—not scheduling automation, AI screening, or interview agents.
Donner promotes Neohunter, a recruitment-as-a-service agency, so a software vendor should check for a service conflict.
The material leans philosophical and agency-focused rather than offering a ready-made co-marketing session; the sponsor would need to build the AI workflow bridge.
When the webinar focuses on AI as a career-advice tool, the manager development gap, and candidate empathy.
Read more
Lokey's 2026 post argues that public AI tools fill a gap when managers cannot help with career development, and that organizations need internal AI career support grounded in performance data and human judgement.
The 2025 post uses the starfish story to argue that every candidate interaction matters.
This suits a sponsor whose TA software addresses internal mobility, career development, or candidate communication—not only sourcing and scheduling.
Lokey's AI commentary focuses on career decisions and manager support, not recruiting workflow automation.
The sponsor would need to shift the webinar away from screening, scheduling, and sourcing agents.
Posts from December 2025 and February 2026 do not demonstrate recruiting software operations or a webinar track record.
No vendor conflict appears in Lokey's posts; ask for examples of sponsorship or co-marketing experience before booking.
When the sponsor wants a current, product-led view of AI recruiting agents and platform strategy.
Read more
Jain's posts, dated September and October 2026, cover Metaview's $110M raise, Jack & Jill and Juicebox funding, and Fabric's evolution from interview notes to a full-stack hiring platform. This directly addresses AI-enabled recruiting workflows and would suit a webinar on where recruiting tech is heading and how agents are taking over sourcing, research, outreach, and scheduling.
Jain represents Fabric, a recruiting tech vendor, creating a direct competitive conflict for a talent acquisition software company.
The posts offer vendor-authored market commentary and product narratives, not neutral analysis, so the sponsor would need to label the session as a vendor perspective.
The content focuses on platform-level strategy rather than a recruiter's hands-on workflow redesign, and assumes an audience already tracking AI recruiting funding and product roadmaps.
Five full LinkedIn posts from Lindzi Cox cover candidate experience and candidate silence, recruiting automation, before-and-after hiring metrics for one customer, hiring funnel redesign, recruiter workload, and structured hiring and bias.
The post texts carry no publication dates; the account's status is current as of October 9, 2026.
No transcript of the Mads Faurholt-Jorgensen TEDx talk Cox summarizes appears in the posts here, so that talk is described only as Cox presents it.
Hiring and customer-outcome figures such as scheduling time and hires per recruiter come from Cox's own posts and are not independently verified here.
Cox's posts do not say whether they have a signature book, show, or earlier public work.
Product positioning, fit judgments, and similar-creator comparisons appear in sections on this page.
