Evgeniia Volkova is building Referrio, a hiring-tech startup focused on helping companies find candidates through referrals. Volkova's posts discuss referral programs, recruiting tools, and making hiring more humane for candidates.
Useful for practitioner-led discussion of candidate experience in ATS platforms and referral hiring, based on early Referrio building.
Best for
An HR tech brand improving ATS candidate experience and application status transparency.
Not for
Paid endorsement campaigns needing rate cards, guaranteed lead volume, or technical ATS integration demos.
Key takeaways
Most ATS platforms are built for recruiters, leaving candidates guessing after they apply.
Referral hiring should be open to anyone, not just employees.
AI should speed up recruiting without erasing the human layer.
Check first: Confirm available formats, terms, and recent reach or engagement data before contacting them.
Main ideas
Applicant tracking systems are built for recruiters, while candidates are left guessing · Referral hiring should be open to anyone, not just employees · AI should speed up recruiting without erasing the human layer
Evgeniia Volkova is building Referrio, a hiring-tech startup centered on referrals.
In these posts, they connect practical recruiting-product questions to applicants’ experience: one post argues that ATS silence leaves candidates guessing and suggests showing applicants where they stand in the process.
Other posts describe Referrio’s early development and raise questions about preserving trust, equity, and human judgment in recruiting as AI spreads.
Ask whether books, shows, or earlier work also shape why people search this name.
Volkova makes hiring technology’s effects on people concrete and points to practical changes.
In the ATS post, the comparison with Upwork’s visible application counts shows how transparency can reduce applicants’ uncertainty; the proposal to share how many applied and were shortlisted turns that concern into a product idea.
Other posts add context: Referrio is framed around rewarding referrals beyond employees, while the AI discussion asks how to preserve human connection, trust, and equity.
Follow their work for this combination of early-stage referral-product building and candidate-centered questions about recruiting systems.
Ask for longer-term performance data to assess the work’s reach.
Evgeniia Volkova writes about hiring from two vantage points: as someone building a referral-based hiring startup called Referrio and as someone who has sat on both the hiring-manager and job-seeker sides of an application pipeline.
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The recurring thread is that hiring systems serve the recruiter and the process, while candidates absorb the silence and guesswork.
Volkova’s priorities are practical and opinionated: make application status visible, open referrals beyond employees, and keep human judgment in place as AI tools spread.
Most posts address practitioners directly — a claim, a contrast, and a question inviting replies — rather than offering polished essays or data reporting.
Applicant tracking systems are built for recruiters, while candidates are left guessing
Volkova argues that most ATS platforms are designed around the recruiter’s workflow — sorting, filtering, moving candidates through a pipeline — and that this leaves candidates in silence.
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Job searching already puts people in a vulnerable position, so an unanswered application can feel like a quiet rejection even when it isn’t one.
They point to Upwork as an alternative: applicants can see how many people applied, how many were shortlisted, and how many received a message, easing some of the self-doubt.
The proposed fix is simple and human: tell candidates where they stand and treat transparency as basic respect, not a feature.
Volkova describes applying through the same systems they once used as a hiring manager and hearing nothing back for weeks.
They name Workday, Greenhouse, and iCIMS as platforms optimized for recruiter workflow.
The concrete ask is a status line: “500 people applied.
Referral hiring should be open to anyone, not just employees
Volkova frames Referrio around a specific design choice: referrals should not be limited to a company’s own staff.
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They argue that the way referrals currently work is one of hiring’s biggest inefficiencies, and that opening the loop to outsiders who can vouch for talent — and rewarding them — widens the pool beyond a company’s employees.
The posts target Talent Acquisition managers and directors at larger companies, whom Volkova asks directly about what works and what fails in referral programs.
That makes product research part of the public conversation, with customer discovery happening in the open.
In a post hiring a Head of Growth, Volkova describes Referrio as a platform where anyone, not just employees, can refer great talent for open roles and get rewarded.
They identify the broken referral loop as the problem to solve.
A separate post asks TA leaders for a quick conversation about their referral programs, inviting comments or a direct message.
The earliest post announces that the team is working on the MVP and planning an April soft launch, asking supporters to join an email list. A later post says the MVP is live, companies are posting jobs, and Referrio is hiring a growth lead for both company hiring and referrers — a shift from pre-launch audience building to early traction and team building.
AI should speed up recruiting without erasing the human layer
Volkova’s position on recruiting technology is not anti-automation.
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Sharing an article on AI in recruiting, they accept that smarter tools help teams move faster but argue the harder question is what should stay interpersonal.
Hiring depends on discovering and vetting people through relationships, a nuance automation alone does not capture.
Volkova asks how to preserve the human layer, decide which parts of hiring remain deeply interpersonal, and prioritize equity and trust alongside efficiency.
They invite practitioners to compare notes.
Rather than summarize the article’s findings, Volkova pulls out one line — that AI is changing how we define great talent, not just automating tasks — connects it to their experience building a hiring-tech startup, and asks TA, recruiting, and people-ops readers three specific questions about the human layer, equity, and trust.
Talk to practitioners before making product claims
Across the posts, a consistent method emerges: Volkova uses LinkedIn to interview the people the product is for.
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They ask named audiences — enterprise TA managers and directors, recruiting and people-ops peers — about their experience, invite comments or direct messages, and share development milestones in small updates rather than launch announcements. The result is a public trail of requests for input, early-access invitations, and open questions.
One post opens by asking LinkedIn friends for help and asks TA managers or directors at enterprise companies for a quick chat on referral programs. Another shares a soft-launch timeline and an email list for progress updates, early access, and ways to get involved; the AI post ends by asking people-ops and recruiting readers about their experience.
This is the clearest starting point for a candidate-experience brief.
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It explains how application silence affects people and what a more transparent system could look like.
Volkova writes from both hiring-manager and job-seeker experience.
The post contrasts applicant tracking systems with Upwork, where applicants can see how many people applied, how many were shortlisted, and how many got a message.
It names Workday, Greenhouse, and iCIMS as platforms optimized for recruiters, and proposes that employers show candidates real pipeline numbers: “500 people applied.
40 were shortlisted.
Here’s where you stand.”
For brands planning a campaign
For an HR tech company improving candidate experience in its ATS, this post offers a specific message and proof point: transparency reduces guessing and self-blame. A campaign should lead with visible application status and shortlist numbers rather than generic employer-brand empathy.
This shows the customer Evgeniia Volkova is building for and how they conduct early research.
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It explains who gets asked for input and why.
Volkova asks Talent Acquisition managers and directors at enterprise companies for a quick conversation about referral programs, specifically what works and what does not. The request names the target role and invites comments or a direct message.
For brands planning a campaign
A brand selling referral or recruiting software can see that Volkova is actively seeking practitioner input from enterprise TA leaders. A relevant campaign could offer access to that audience or co-create research.
This gives the product timeline: what Referrio was doing before launch and how it invited early supporters in.
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It shows where the company was in its development.
Volkova says the team is working on the MVP and plans to soft launch in April. The post invites friends, former colleagues, and companies looking for a better way to hire through referrals to join an email list for updates, early access, and ways to get involved.
For brands planning a campaign
For a campaign tied to referral hiring, this post signals an early-stage product and an audience-building phase. Ask for launch scale, customer traction, and paid-promotion plans before committing to a partnership.
This is the best starting point for an AI recruiting vendor.
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It explains how Volkova frames automation and what they think should stay human.
Volkova shares a TechBullion article on AI in recruiting and asks how to preserve the human layer as smarter tools are adopted.
The post asks which parts of hiring should remain deeply interpersonal and how to optimize for equity and trust, not only efficiency.
They connect these questions to building a hiring tech startup and to discovering and vetting people through relationships.
For brands planning a campaign
An AI recruiting company should not pitch pure automation to this audience without addressing trust, equity, and human judgment. This post supports a campaign angle about human-in-the-loop screening or referral-based discovery rather than replacing recruiters.
Format: problem framing, contrast, and open questions5
Referral programs as a broken loop3
Building in public through direct practitioner outreach3
Early-stage startup growth and hiring2
Candidate experience and ATS transparency1
The human layer in AI recruiting1
Referral programs as a broken loop
Evgeniia Volkova describes Referrio as a platform that lets anyone refer talent for open roles and get rewarded, not just employees.
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They call the broken referral loop one of hiring's biggest inefficiencies and say the MVP is live with companies posting jobs. In another post, they ask Talent Acquisition managers and directors at enterprise companies what works and what does not in referral programs.
For brands planning a campaign
Relevant for HR tech and referral-program campaigns that need a founder-operator voice close to early product build. For candidate-experience briefs, this is adjacent rather than direct proof; ask for examples of ATS communication work.
Volkova argues that most ATS platforms are built for recruiters, not candidates, and that silence after applying feels like rejection.
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They compare recruiter-focused platforms such as Workday, Greenhouse, and iCIMS with Upwork, where applicants can see how many people applied, how many were shortlisted, and how many received a message. They call on TA leaders to give candidates real numbers, framing transparency as basic respect.
A first-person reflection from hiring-manager and job-seeker perspectives, followed by a platform comparison and a direct challenge to TA leaders.
The ATS critique is commentary about platforms. Evgeniia Volkova's posts do not say that Referrio has shipped candidate-status features.
For brands planning a campaign
Directly usable for a candidate-communication campaign: the post names the problem, offers a concrete alternative, and proposes a simple change—tell candidates where they stand. A brand can build content around application-status transparency, shortlist visibility, and respectful rejection messaging, using Volkova's framing as a discussion starter.
Volkova shared a TechBullion article on AI in recruiting and focused on the balance between automation and human connection.
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They asked how to preserve the human layer of recruiting, which parts of hiring should remain deeply interpersonal, and how to optimize for equity and trust rather than efficiency alone. The post invites TA, recruiting, and people-ops practitioners to trade notes.
For brands planning a campaign
A fit for thought-leadership campaigns on AI-assisted hiring, candidate trust, and where human judgment should stay in recruitment. Volkova can frame the debate and raise practitioner questions; if a campaign requires deep technical evaluation of ATS tools or AI screening systems, ask for that experience.
Building in public through direct practitioner outreach
Several posts show a first-person, direct-address style.
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Volkova asks LinkedIn friends for help, requests quick chats with TA managers and directors, invites comments or DMs, shares soft-launch progress, and asks recruiting peers to trade notes. The approach favors community research and early customer discovery over formal publishing.
Direct questions, invitations to comment or DM, soft-launch updates, and requests for practitioner experience.
For brands planning a campaign
Useful for roundtables, practitioner interviews, co-created research, and campaigns that need a founder who will ask an audience for input rather than only broadcast.
A brand can provide access to TA leaders or help turn the questions gathered into a public resource.
Calls to action around email lists and DMs suggest conversational formats.
Volkova posted a search for a Head of Growth at Referrio, describing an equity-plus-commission role across B2B company hiring and B2C referrers.
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The post lists ideal experience in pre-seed to early-traction startups, HRTech, marketplaces, or SaaS, plus hands-on acquisition, community building, and partnerships. An earlier post announces MVP work, an April soft launch, and an email list for early access.
For brands planning a campaign
Shows an operator building a hiring-tech startup from an early stage, a fit for pilot partnerships, product feedback loops, and agile campaign tests. The small scale and growth focus mean a brand should expect founder-led decisions rather than a large content or partnerships organization.
Format: problem framing, contrast, and open questions
Volkova often opens with a direct claim, contrasts two experiences or systems, and closes with a question or call to respond.
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The candidate-experience post moves from personal experience to an Upwork-versus-ATS comparison and a challenge for TA leaders.
The AI post moves from an article to open questions.
Referrio posts mix product updates, hiring calls, and requests for input.
First-person claims, compare-and-contrast arguments, lists of questions, and direct calls to comment, DM, apply, or join a list.
For brands planning a campaign
Campaign content can use a sharp problem statement, a before-and-after or platform contrast, and a question that invites practitioners to respond. The style is readable and conversation-driven rather than data-heavy or technical.
The posts present Referrio as Volkova’s hiring-tech startup, but do not specify their formal relationship to the business or disclose sponsorship or payment.
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Ask them to clarify both.
Referrio
Disclosed partnership
Volkova describes working on Referrio, a platform for hiring through referrals, and promotes its launch and growth.
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Ask them to clarify their formal relationship to the business.
Volkova's posts trace one problem from several angles, so start with a question rather than a date.
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Read the post comparing recruiter-focused applicant tracking systems with Upwork's visible application status if candidate communication interests you; turn to the Referrio posts for how referral hiring is being rebuilt and opened beyond employees; then read the post on AI in recruiting for questions about automation and human judgment. Each item is a LinkedIn update written in direct address, and several end with a question, making the comment threads part of the posts.
Cox also writes about recruiting as a practice that was never properly taught, and unpacks inherited hiring habits, much as Volkova questions why applicant tracking systems are built only around the recruiter.
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Both turn practitioner frustration into questions for a talent acquisition audience and make the reply thread part of the argument.
Cox works outward from other people's ideas, quoting a TEDx talk and a borrowed phrase, then reflecting on what they mean for recruiters. Volkova writes from inside a hiring product under development, mixing argument with product updates and direct requests for practitioner interviews.
Rojas covers hands-on talent acquisition problem-solving, including where candidates actually are and how recruiting workflows get in the way.
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That overlaps with Volkova's interest in how candidates enter a pipeline and their argument that recruiters should partner with the business rather than process applications.
Rojas reports from the employer and vendor side through field conversations and case studies featuring named employers and hiring numbers. Volkova focuses on candidates' experience of silence and the design of referral software, asking readers for input rather than presenting completed results.
Carlson advises talent acquisition leaders on building and scaling hiring functions, covering structure, workforce planning, metrics and hiring-manager discipline.
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The audience and the view of recruiting as a business function align with Volkova's direct address to TA managers and directors.
Carlson writes numbered lessons drawn from experience leading TA functions inside companies and closes with an offer to talk. Volkova publishes shorter, single-argument posts while building referral software, making the material more exploratory and focused on a product still in early traction.
Volkova's LinkedIn account shows 3,324 followers as of 11 October 2026.
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Five posts from March 2025 to August 2026 focus on talent acquisition: candidate experience in ATS platforms and the silence candidates get after applying; referral programs and the Referrio product built around them; AI in recruiting and its effect on who counts as strong talent; and a hiring call for a growth lead.
This topic pattern suggests a recruiting- and TA-facing audience, but does not establish who follows or reads the posts.
No post-level engagement, reach or engagement-rate figures are published.
For an HR-tech company improving candidate experience in its ATS, the subject matter closely matches the buyer's problem.
The strongest example is the post contrasting Workday, Greenhouse and iCIMS with Upwork's applicant visibility, which speaks directly to how candidates are told where they stand.
It also addresses two audiences: hiring managers who run pipelines and job seekers who submit into them.
Their value to a campaign differs sharply, and the posts do not show how the audience splits.
Job function, seniority, employer type, geography, age and gender are also unmeasured.
Ask for recent reach and engagement on the two or three posts closest to candidate-experience and recruiting-tools topics, along with any audience survey results or platform demographics covering geography, age, gender, job function or seniority.
These would help assess performance and professional relevance; the follower count alone cannot.
The five posts by Evgeniia Volkova contain no sponsorship offer, media kit, rate card, or disclosed paid partnership.
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Their published activity centers on building Referrio, a referral-based hiring platform; candidate experience in applicant tracking systems; and how AI is changing recruiting.
One post advertises a Head of Growth role at Referrio, paid in equity plus commission—an internal startup role, not a format a brand can book.
Two others ask talent-acquisition contacts for input on referral programs and invite people to join a Referrio email list ahead of an April soft launch.
The posts do not say how a brand could sponsor, collaborate with, or be featured by Volkova, and publish no partnership inquiry route.
Buyers would need to contact them directly and ask about availability, pricing, deliverables, and turnaround.
A good fit for a directly scoped thought-leadership and practitioner-research collaboration, as long as the company does not require a published sponsorship package, guaranteed reach, or proof that Evgeniia Volkova has built ATS features.
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Brief
An HR tech company wants to improve candidate experience in its ATS and needs a practitioner voice to start a public conversation about application status transparency.
Reasons
The strongest matching post argues that most ATS platforms are built for recruiters, not candidates. It contrasts Workday, Greenhouse, and iCIMS with Upwork's applicant visibility and proposes showing candidates real numbers such as "500 people applied. 40 were shortlisted. Here's where you stand." That is the exact problem the brief names.
Volkova writes from both hiring-manager and job-seeker experience, giving the campaign a usable first-person frame rather than a vendor script.
In another post, Volkova asks talent-acquisition managers and directors for their perspectives on referral programs and invites comments or direct messages. That supports a practitioner interview, roundtable, or co-created research format.
Volkova’s AI recruiting post adds a related angle: preserve the human layer, keep some parts of hiring deeply interpersonal, and optimize for equity and trust rather than efficiency alone.
Commercial note: Volkova’s posts do not mention a sponsorship offer, media kit, or rate card. Scope the collaboration directly. Referrio is their own early-stage product, not a third-party brand relationship; the posts do not document paid partnerships.
Audience fit is plausible but unproven. The posts provide no engagement, reach, or demographic data, so treat this as a pilot and measure results through the company’s own channels.
When to choose a specialist
Poor fit.
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Brief
A B2B software company wants a high-volume paid endorsement campaign with a published rate card, guaranteed lead volume, and technical ATS integration demos from a recognized implementation expert.
Reasons
The five posts offer no sponsorship menu, media kit, rate card, or disclosed paid partnership. Ask Volkova directly about available formats and terms.
The posts cover opinions, startup-building updates, and practitioner questions, but do not show technical evaluation, implementation, or product demos of ATS systems. Volkova compares platforms and proposes a communication change; ask for evidence of ATS configuration or feature delivery if those credentials are essential.
The posts provide no reach, engagement, or audience-demographic data, so promised lead volume or precise audience targeting is unsupported. Run a pilot and measure results through the company’s own channels.
The commercial context is early-stage and founder-led. A hiring post for a Head of Growth role offers equity plus commission, while other posts describe MVP work and a soft launch. That does not indicate a large partnerships or content operation.
A campaign requiring a broad consumer or enterprise brand endorsement outside recruiting would lack topical grounding. The posts focus on hiring, referrals, candidate experience, and AI in recruiting.
A worked campaign example
Angle
Run a “show candidates where they stand” campaign built on Volkova’s ATS transparency argument. Sell a candidate communication practice, not a feature list.
Brief
HR tech company improving candidate experience in its ATS.
Deliverables
An anchor post or short article from Volkova: a first-person account from both sides of the pipeline, followed by a comparison of recruiter-first ATS workflows with Upwork-style applicant visibility. It names the silence problem and proposes three status lines employers can send: application received; review stage and shortlist count; final decision and next step.
Live practitioner session: a 30-minute recorded conversation with two talent-acquisition leaders, hosted by the HR tech company. Volkova asks questions raised in their posts: what works and what does not in candidate communication, where automation helps, and which parts of hiring should stay human. The company handles distribution and follow-up.
Practical resource: a one-page candidate-status message template that a TA team can copy. Fields include role, date received, current stage, number of applicants, number shortlisted, expected decision date, and feedback or contact route. The company can add its ATS workflow guidance, without claiming Volkova built the product.
Follow-up post: a short summary of what practitioners said, including disagreements, plus one change the company will make to its own candidate messaging.
Measurement
The posts provide no reach or engagement data, so run this as a pilot. Measure the company’s own post engagement, template downloads, session attendance, and follow-up conversations. Do not promise lead volume from Volkova’s audience.
Next step
Ask for a direct scoping conversation covering one anchor post, one live session, and one resource. Agree on rights, disclosure, timeline, and fees in writing.
Why it works
The angle comes directly from Volkova’s strongest post, uses the compare-and-contrast and open-question formats that recur in their writing, and focuses on a concrete behavior a brand can adopt. It avoids unsupported technical claims and paid-endorsement language.
Choose Lindzi Cox when the goal is to get a talent-acquisition team to rethink a process before any feature is built.
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Cox's posts closest to this task work as synthesis and provocation: one distills Mads Faurholt-Jorgensen's talk into the argument that hiring managers misread role needs, hire people like themselves, and screen out "whispering talents," and endorses structure, tools, and even algorithms as the fix.
Another uses "don't pave the cowpath" to ask whether the linear hiring funnel should exist at all rather than be automated.
For an HR tech company whose problem is a candidate experience built around inherited recruiter-first steps, Cox is a stronger opening voice than a status-transparency poster if the goal is to get TA leaders questioning the funnel itself.
Cox makes the case for change through other people’s frameworks, not a first-person account from both sides of the pipeline.
Volkova’s ATS post names the behavior a campaign about candidate-facing status transparency would want: showing applicants applied, shortlisted and decision counts, compared with Workday, Greenhouse and iCIMS.
Cox’s closest content stays at the level of process philosophy and does not specifically argue for candidate-facing status transparency.
A campaign built on Cox would need the company to supply the concrete candidate-communication proposal, trading a direct on-need argument for a broader reframing that may be harder to turn into a specific deliverable.
Choose Danny Rojas when the goal is to widen the top of the funnel and make recruiters strategic partners, backed by a measured outcome.
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Rojas describes sourcing skilled-trades and diesel-technician talent through unconventional channels such as Craigslist and building training around people who lack the stated experience, and a second post walks through Signature HealthCARE's fragmented recruiting process where simplifying the experience and improving visibility with iCIMS produced a reported 52% rise in nursing applications, 47% in completed applications, and 17% in total hires.
That post also carries the "we weren't partners, we were processors" framing — technology should give recruiters room to become better partners rather than just process more work.
If the HR tech company wants a practitioner who can speak to ATS-enabled gains in application completion and a recruiter-partnership narrative, Rojas has the more concrete operational story.
Rojas’s posts center on a named vendor case study and skilled-trades and healthcare hiring, so a campaign would either echo that vendor frame or risk looking like a copy.
The content focuses on sourcing pipelines and recruiter capacity, not the candidate’s experience of silence after applying—the specific problem a candidate-transparency campaign would address.
Volkova’s argument is narrowly about what candidates are told and when.
Switching to Rojas would shift the campaign from candidate transparency to sourcing and operational outcomes, a different decision with a different audience and measurement story.
Choose Gabrielle Carlson when the audience is TA leadership and the goal is a business-case conversation.
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Carlson writes about building talent-acquisition functions from scratch, listing structure that enables speed, workforce planning over requisition management, metrics that drive decisions, hiring managers as the biggest variable and employer brand starting inside the business.
Another post argues that recruiting drives revenue, while most organizations still measure it as an administrative function through req count, time-to-fill and cost-per-hire.
For an ATS vendor seeking CHRO and TA-leader buyers and positioning candidate experience as a growth lever, Carlson offers the more executive framing.
Carlson’s material addresses people who run TA functions and speaks in terms of function design and revenue.
It does not cover candidate-facing application status or what silence after applying does to a job seeker—the core of a candidate-transparency campaign.
A campaign built on Carlson would make the case to leaders about talent strategy; the company would need to supply the candidate-communication change.
It also shifts the buyer conversation from a candidate-experience problem to a TA-as-revenue-engine problem, so the same platform capability would be sold on different grounds.
Five LinkedIn posts from the account linked to Evgeniia Volkova cover Referrio's progress from MVP work and an April soft launch to a live product and an open growth hire, the case for opening referrals beyond employees, an argument that applicant tracking systems are built around the recruiter while candidates are left without answers, and open questions about keeping human judgment in recruiting as AI spreads.
The posts do not show publication dates, so none are stated.
One referenced TechBullion article was not available in full and is not summarized here.
The posts do not provide engagement, reach or audience-demographic data, and no sponsorship offer, media kit or rate card appears in them, so no bookable formats are described.
The posts do not establish a complete public biography: earlier work, books or shows that might explain why people search this name are not documented in the posts.
The statements are attributed to the posts; the posts do not verify employers, credentials or product status against outside sources.