Sava Vacic is most useful for helping e-commerce brands hire an in-house performance video editor.
Best for
A DTC brand building in-house performance creative for Meta and TikTok ads.
Not for
A paid LinkedIn sponsorship, impressions-led campaign, or agency retainer media buy.
Key takeaways
Test editors on a real brief rather than relying on their portfolios.
Performance editors make variations from UGC, product footage, testimonials, then test hooks and offers.
Vacic argues creative variety matters more than audience segmentation in Meta advertising.
Check first: Ask how candidates are scored, and request measurement details behind performance and cost claims.
Main ideas
Judge editors by ad performance, not showreels · An in-house performance editor can beat per-video hires and agency retainers · Meta rewards creative variety, so brands need more ads
Sava Vacic writes about building creative teams for e-commerce advertising, especially hiring in-house video editors who can make and test ads aimed at sales.
The posts explain the work, from trying candidates on a real brief to producing varied concepts and improving them with performance feedback.
They argue that creative variety matters more than audience segmentation in Meta advertising.
A personal post about moving to a larger office offers a perspective on team growth: provide people with a shared vision, tools, and information.
Follow them for practical views on performance-focused editing and creative operations, alongside occasional reflections on leading a team.
Vacic connects hiring decisions to the work an editor must actually do.
One post describes testing candidates on a real brief; buyers should ask how candidates are scored.
Another lays out the role: make variations from UGC, product footage, testimonials, and other assets; test hooks, offers, and formats; then iterate using results and feedback.
Their broader argument is that a steady supply of genuinely different creative concepts can help DTC brands compete on Meta.
The posts include performance and cost claims, including an 8% ad-quality improvement and one client’s reported savings; buyers should ask for the measurement details behind them.
An office-move reflection shifts from advertising to team capacity and motivation.
Sava Vacic's recurring argument is that what matters in video advertising is whether an editor can produce ads that sell—not whether the edits look polished or where the editor lives.
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They define performance video editing through hooks, pacing, offer, retention, creative testing, and AI-assisted processes.
They argue brands can outperform one-off freelancers, agency caps, and local-hire assumptions by building an in-house, full-time performance editor function.
They link editor skill to a broader creative-volume strategy on Meta: the algorithm rewards genuinely different concepts, so brands need daily output and weekly testing.
Their posts also describe an AI-first production loop for DTC formats and a management priority of giving teams capacity, vision, tools, and information.
The posts offer no guest perspectives; these are Vacic's own arguments.
Judge editors by ad performance, not showreels
Sava Vacic treats performance video editing as distinct from general video editing.
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They say many editors know how to make videos look good or handle short-form organic content, but few understand how to make direct-response ads that sell.
The skills they name are hooks, pacing, offer, retention, creative testing, and AI workflows.
They also say they skip portfolios when sourcing editors because they can be faked, and instead test candidates with a real brief and tasks for a specific brand.
On sourcing editors: "If they can perform, they're in.
If they can't, I move on."
The same post says a portfolio can be faked, but real performance cannot.
An in-house performance editor can beat per-video hires and agency retainers
They argue US e-commerce brands often hire editors locally, expecting them to understand the market, then pay high per-video rates or salaries and still get underperforming ads—losing money on both the editor and Meta.
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Their proposed fix is not about location but skill: hire a full-time performance video editor who works directly with the brand team, understands the brand, moves fast, and helps generate more revenue without large overhead costs. They say the real problem is that most editors are not performance video editors, even in the US.
A client in Los Angeles was paying $500 per video and, in Vacic's account, losing money testing those videos.
After bringing one performance video editor in-house, the post says, the cost was five times lower and the editor produced ads that performed.
Meta rewards creative variety, so brands need more ads
They argue Meta's algorithm now ranks creative variety above audience segmentation or lookalikes.
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They cite Andromeda, Meta's next-gen AI, as delivering an 8% improvement in ad quality for brands that gave it a broad portfolio of distinct creatives.
In their view, winning brands have full-time performance video editors in-house, producing daily, testing weekly, and learning constantly.
They warn that brands bottlenecked on creative output are losing to competitors with more ads, not just better ads.
They contrast brands relying on one agency with a monthly cap, a founder editing ads at 11pm, or a team cycling through freelancers every three weeks with brands that have an in-house editor producing distinct concepts at volume. Ask for the source and measurement details behind the 8% figure.
AI-first production and a defined set of direct-response formats
In a hiring post for a DTC brand, they describe an e-commerce video editor role producing multiple short-form ad variations every week from UGC, raw footage, product clips, testimonials, voiceovers, and AI-generated assets.
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Listed formats include UGC, mashup, product demo, testimonial, founder, and short-form VSL ads across Meta, TikTok, Instagram, and YouTube.
AI tools run throughout asset creation, voiceovers, editing, and creative iteration.
The editor tests new hooks, angles, offers, formats, and calls to action, then iterates on winning ads using performance data and feedback.
This is their operational definition of a performance editor.
The role calls for someone who understands that the goal is not just to make videos look good but to help e-commerce brands sell more. Testing and constant iteration are part of the job, not separate steps.
In a personal post, they describe deciding to move to a bigger office and say the new space changed how the team thought about its capacity.
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They argue people will go as far as the capacity and vision they are given, and that providing people, tools, and information matters more than pressure. They describe fulfillment as helping team members grow toward what they can become and achieve.
After the move, team members began talking about working weekends to sustain the new level, the post says. Vacic connects the physical space to a larger vision and says the team will pursue it because of what it means for their careers.
Wondering how Sava Vacic evaluates video-editor candidates?
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This post explains the practical test they use: give candidates a real editing task, then judge their performance.
Vacic argues that portfolios can be faked and describes testing editors with work for a specific brand. The post favors demonstrated task performance over polished samples; ask how the test is scored.
For brands planning a campaign
For a brand hiring an editor, build a paid or otherwise clearly scoped test around a representative brief. Define the evaluation criteria in advance.
Want to know what Vacic means by an AI-first e-commerce video editor?
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This hiring post lays out the role's formats, weekly work, tools, and iteration expectations.
The role is broader than cutting footage: it includes making variations from UGC, product clips, testimonials, voiceovers, and AI-generated assets; testing hooks, angles, offers, formats, and calls to action; then iterating using performance data and feedback. The post names Meta, TikTok, Instagram, and YouTube as channels.
For brands planning a campaign
Use this as a starting point for a role brief when a brand needs ongoing direct-response creative production, not just occasional editing. Assess both production range and comfort with testing and revisions.
Considering whether to hire locally, use an agency, or bring editing in-house?
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This post makes Vacic's case for hiring around performance skills rather than the editor's location.
Vacic contrasts expensive editing that does not perform with an in-house editor who can understand the brand, work directly with its team, and move quickly.
They cite one client example: a Los Angeles brand paying $500 per video, followed by a claim that an in-house editor was five times cheaper and produced ads that performed.
Ask for the underlying performance and cost data.
For brands planning a campaign
For a brand weighing team structure, compare total cost and ad results—not location or production polish alone. Treat the single-client savings figure as an example to investigate, not a guaranteed outcome.
Trying to understand Vacic's view of modern paid-social creative?
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This post explains why they see a steady supply of distinct concepts as important to DTC advertising.
Vacic argues that Meta's algorithm rewards creative variety more than audience segmentation, and frames creative volume as a way to give the system more distinct concepts to work with.
They contrast that approach with teams limited by an agency's monthly output, a founder's spare time, or short-term freelancers.
The post cites an 8% ad-quality improvement; ask for the source and measurement details.
For brands planning a campaign
If testing this idea, plan a portfolio of meaningfully different concepts rather than many minor edits to one ad. Set a cadence for reviewing results.
Looking for Vacic's perspective beyond hiring and ads?
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This personal post shows how they connect a larger office and a bigger vision with team capacity and motivation.
Vacic recounts deciding to move into a bigger office and says the expanded space changed how the team thought about its capacity.
They present a shared vision, tools, and information as part of supporting people's growth.
The post is a personal reflection, not evidence that an office move or weekend work improves performance.
For brands planning a campaign
For a brand scaling a creative team, the post raises a management question: what resources and direction will let people do the work well? It is less directly useful for choosing an ad concept or editor.
Vacic treats performance video editing as distinct from general video editing.
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In one post, they say most editors can make videos look good or handle short-form organic content, but few understand hooks, pacing, offer, retention, creative testing, and AI workflows for direct-to-consumer ads. In another, they describe sourcing editors through a real brief and tasks rather than portfolios: a portfolio can be faked, but task performance cannot.
Paid or live task built around the brand's actual ad brief; use the portfolio only after performance is demonstrated.
For brands planning a campaign
A brand evaluating Vacic should test candidates on paid-ad performance, not showreel quality. Ask for the campaign objective and scoring criteria, and include hooks, offer, retention, and iteration in the evaluation.
Building an in-house editing function instead of buying one-off videos
Vacic argues that US e-commerce brands often pay high per-video rates or salaries for local editors and still get poor ad performance, losing money on both the editor and Meta.
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They position the fix as hiring a full-time performance video editor in-house to work directly with the brand team, move fast, understand the brand, and make more money without large overhead. For example, an LA client paying $500 per video lost money testing those videos; after bringing in one performance video editor in-house at roughly five times lower cost, the editor produced ads that performed.
For brands planning a campaign
Assess Vacic for roles that build a repeatable in-house ad production function, not isolated edits. Compare total cost with agency retainers or per-video freelancers, and ask about volume, iteration cadence, and team integration.
Creative volume as the new targeting lever on Meta
Vacic says Meta's algorithm now ranks on creative variety rather than audience segmentation or lookalikes.
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They cite Andromeda, Meta's next-gen AI, as delivering an 8% improvement in ad quality only for brands with a broad portfolio of distinct creatives.
In their view, brands that can feed the system have full-time performance video editors in-house, outputting daily, testing weekly, and learning constantly.
They warn that brands bottlenecked on creative output lose to competitors with more ads, not just better ads.
Daily output and weekly testing as the operating cadence for a creative portfolio.
For brands planning a campaign
For a DTC brand scaling Meta, the key question is whether Vacic's approach can supply enough genuinely different ad concepts to feed the algorithm. Build the campaign plan around concept volume, distinct angles, and a weekly test-and-learn loop, not a single campaign asset.
AI-first production and the formats a DTC brand can evaluate
In a hiring post for a DTC brand, Vacic lists a role editing multiple short-form ad variations each week from UGC, raw footage, product clips, testimonials, voiceovers, and AI-generated assets.
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Formats include UGC, mashup, product demo, testimonial, founder, and short-form VSL ads across Meta, TikTok, Instagram, and YouTube. The workflow uses AI tools for asset creation, voiceovers, editing, and creative iteration, testing hooks, angles, offers, formats, and calls to action, then iterating on winners based on performance data.
For brands planning a campaign
Evaluate whether Vacic's team or candidates can produce these formats and run AI-assisted iteration at volume. Specify the formats and platforms that matter, and ask about the AI workflow, revision process, and performance feedback loop.
In a post about moving to a bigger office, Vacic links output to the capacity, vision, people, tools, and information a team is given.
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They say team members began discussing weekend work after the move and frame the goal as building a team that pursues the vision for what members can become and achieve. This is a management and culture observation, not an ad tactic.
This post focuses on office and team culture, not performance advertising or hiring criteria.
For brands planning a campaign
If a brand is considering Vacic for team building or managed capacity, expect an emphasis on environment, vision, and member growth. Treat this as context on management style, not evidence of ad performance.
Sava Vacic’s posts name no client, employer, sponsor, or owned business.
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They cite Meta, whose creative-variety ranking supports their argument for in-house editors, and Upwork, the freelancer marketplace they say leaves brands short of ad variations.
The client and hiring brand in their examples are unnamed.
Vacic presents themselves as the person who recruits and places performance video editors, and their hiring requests call for ads on Meta, TikTok, Instagram, and YouTube.
Ask about the client identities and any compensation arrangement.
Meta
Mention
Vacic argues that Meta’s advertising system has made targeting the algorithm’s job and rewards creative variety.
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They say Andromeda delivered an 8% ad-quality gain for brands that feed it many distinct concepts, making the case for full-time in-house editors who produce and test ads daily.
No sponsorship or client relationship with Meta is stated; it appears as the platform the service operates on.
Vacic’s hiring requests call for ads on Meta, TikTok, Instagram, and YouTube.
Vacic names Upwork as the marketplace where brands cycle through freelancers every three weeks, illustrating the creative-output bottleneck they say in-house performance editors solve.
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The post states no commercial relationship with Upwork.
Sava Vacic's work is easiest to explore through one thread across several posts: what separates an editor who makes video look good from one who makes direct-response ads sell.
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Start with the editor-hiring posts, where they describe testing candidates on a real brand brief instead of relying on portfolios.
Then turn to the posts on in-house performance editors and Meta creative volume, which argue that brands need many genuinely different concepts rather than one polished campaign asset.
An AI-first hiring post adds the operational layer: short-form UGC, mashup, demo, testimonial, founder, and VSL formats produced and iterated at volume.
A post on office space and team capacity offers a glimpse of management style.
Readers looking for adjacent voices can compare Vacic with creators focused on direct-response editing craft, UGC and affiliate creative operations, or Meta creative strategy for DTC brands.
Both distinguish ordinary video editing from direct-response ad editing.
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Ganzina explains that a polished editor may not know how to make an ad convert, then breaks down the job: stop the scroll, introduce the problem, make the product and value obvious, build trust, use social proof, handle objections, and finish with a reason to act. That complements Vacic's argument that most editors can make videos look good, but few understand hooks, pacing, offer, retention, and creative testing.
Ganzina stays close to the craft of editing and the decisions inside a single ad, while Vacic focuses more on sourcing and testing talent and building an in-house editor function that can feed Meta with volume.
Both work in DTC performance creative and creator-produced ad content.
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Schroën's hiring post seeks editors for short-form and long-form paid-social ads, UGC, VSLs, and performance creatives, and asks them to improve based on performance data.
Another post connects UGC and creator content to AI-driven product recommendations and affiliate programs.
The overlap is a practical focus on producing social-native creative that can perform in paid acquisition.
Schroën's posts lean toward UGC and affiliate creator networks, as well as AI visibility, while Vacic's center on editor testing and in-house production capacity for paid social.
Both argue that DTC brands need creative variety and a system for producing and testing it.
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Healy warns against copying bottom-funnel ads from big brands whose audiences already know the product, and describes apparel brands that scale by building a bank of different styles, formats, and energies while systemising creative production. Vacic makes a related case: Meta rewards many genuinely different concepts, not audience segmentation alone.
Healy focuses on creative strategy and media buying, with attention to buyer stage and apparel aesthetics; Vacic focuses on editor hiring and the in-house production function behind creative volume.
For a DTC brand scaling in-house performance video editors, Vacic’s LinkedIn profile supports a targeted follow-up rather than a verified match.
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Their profile showed 5,936 followers as of 9 October 2026, and their posts target e-commerce teams hiring and managing performance creative: in-house editor hiring, performance ad skills such as hooks, pacing, retention, and creative testing, and Meta’s shift toward creative volume.
The subject matter gives people in those professional circles a plausible reason to follow, but the profile provides no post engagement counts, demographic breakdown by geography, age, or gender, or audience survey covering employer, occupation, or seniority.
Consider Vacic for a test campaign aimed at creative-side reach into DTC/e-commerce circles; before treating the audience as a precise match, ask for recent post impressions or engagements and any audience survey or platform demographics.
For employer, occupation, or seniority, ask whether they have an audience survey or another source, since standard platform demographics would not verify those attributes.
Sava Vacic's visible commercial offer is helping e-commerce brands hire a full-time performance video editor in-house, not providing a sponsorship package, media kit, or published rate card.
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Treat this as a recruitment and placement engagement, not a sponsored post.
Vacic says they test editors with real campaign requirements and tasks rather than relying on portfolios, so a brand should be ready to supply sample campaign requirements, real product or creative context, and a way to assess whether the editor can produce and iterate on direct-response ad variations.
Vacic argues that the stronger model is an editor inside the brand's team, producing daily and testing weekly, rather than an agency monthly cap or rotating freelancers.
Ask Vacic for an official partnership or inquiry page before publishing a link.
In-house performance video editor placement
Buyer requirement
A brand needs a full-time editor who can work directly with its team, produce short-form direct-response ad variations across Meta, TikTok, Instagram, and YouTube, and use performance data to iterate on hooks, pacing, offers, retention, and creative testing.
Vacic describes this as cheaper than paying roughly $500 per video or a large salary for an editor who does not understand performance advertising.
The buyer must be ready to provide real briefs, assets, brand context, and ongoing test feedback.
Proceed to a scoped test, after settling the placement details. Sava Vacic's posts show them working directly on this problem, making a campaign that needs this kind of work a credible fit.
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Brief
A DTC e-commerce brand spending on Meta and TikTok wants to replace one-off agency videos and rotating freelancers with an in-house performance creative function.
It needs a full-time video editor who can produce several short-form ad variations each week from UGC, raw footage, product clips, testimonials, and AI-generated assets, then use performance data to iterate on winning hooks, angles, offers, and calls to action.
The brand wants help finding and vetting that editor, and will judge the engagement by whether the ads sell.
Reasons
Vacic describes the brand's bottleneck: US e-commerce brands pay roughly $500 per video or a large full-time salary for editors who do not understand performance advertising, losing money on both the editor and Meta. That is the decision the brand is already weighing.
Sava Vacic's posts offer recruitment and placement, not a media buy: helping a brand hire a full-time performance video editor who works directly with its team, moves fast, and understands the brand. That fits an in-house build, not an agency retainer.
Vacic's sourcing method asks the brand to provide a real brief and tasks rather than rely on portfolios. A brand that can share product context and judge direct-response output can use this process to assess editorial fit before hiring.
The formats and workflow in Sava Vacic's hiring post fit a campaign that needs this kind of creative: multiple short-form variations weekly, including UGC, mashup, product demo, testimonial, founder, and short-form VSL ads across Meta, TikTok, Instagram, and YouTube. The editor uses AI tools and iterates based on performance feedback.
Vacic argues that Meta creative volume depends on distinct concepts feeding the algorithm, daily output, and weekly testing, and that brands bottlenecked on creative output lose to competitors running more ads. The brand can use that logic to set its own operating cadence.
Watch for
Ask for details behind the single Los Angeles client example: the $500-per-video spend, the roughly five-times-lower cost, and the claim that the in-house editor produced ads that performed. The post gives no underlying cost or performance data, so treat the figures as an example to investigate, not a benchmark.
Ask how the test task is scored and how the hire decision is made. Vacic says real tasks beat portfolios, but the posts do not explain the evaluation process.
Confirm the placement's commercial terms and official inquiry route. Sava Vacic's posts show no rate card, package, or verified inquiry page; do not publish a link.
Set measurable expectations for creative volume. Sava Vacic's posts establish neither a winning number of concepts per week nor a guaranteed performance outcome.
Before assessing reach, ask for the dates of the five posts, the source and measurement details for the 8% ad-quality figure, and engagement and audience-composition figures. The posts provide none of these.
When to choose a specialist
Reject or substantially reframe an impressions-led sponsorship campaign. Sava Vacic's posts show no sponsorship offer, and their audience information does not support an impressions-based buy.
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Brief
A DTC or B2B brand wants to buy a paid LinkedIn thought-leadership placement from Vacic: a series of sponsored posts promoting the brand to their roughly 5,900 followers, priced from a published media kit and judged primarily on impressions, follower growth, and engagement rate.
Reasons
Sava Vacic's posts contain no sponsorship package, media kit, or published rate card. The visible commercial offer is editor recruitment and placement—a hiring engagement, not paid brand distribution to an audience.
The audience section provides no engagement counts for any posts, geographic, age, or gender breakdown, or audience survey covering employer, occupation, or seniority. A buyer cannot price or forecast an impressions-based placement on that basis.
Sava Vacic's posts address e-commerce operators hiring and managing creative. A sponsored post series aimed at a broad buyer audience would be judged against a following whose professional profile the posts do not establish.
Creative production leadership and distribution are different needs. Sava Vacic's posts support the first, not the second; treating them as the same purchase would misprice the engagement.
Watch for
If the brand still wants to work with Vacic, reframe the ask around the demonstrated offer: hire or place an in-house performance editor, or commission a candidate-testing process built around the brand's brief.
If reach into DTC and e-commerce circles is central, ask Vacic for recent post impressions, engagement figures, and any audience survey before committing spend. Without that data, the placement cannot be forecast.
The absence of a sponsorship offer in Sava Vacic's posts does not prove they would never accept one. The posts simply do not document such an offer.
A worked campaign example
Brief
A direct-to-consumer skincare brand spending $300,000 monthly on Meta has hit a creative ceiling: its agency delivers eight new ads a month, the founder edits on nights and weekends, and the team has cycled through three Upwork freelancers in a quarter. The brand wants 30 meaningfully different concepts a month and a weekly test-and-learn loop.
Campaign angle
Use Vacic for a two-stage engagement rather than a single hire. First, pay for a test brief: the brand provides two products, existing winning ads, and a one-week paid task, and Vacic evaluates at least three named editor candidates against it. Then place one full-time performance video editor inside the brand, with direct access to the media buying team, a defined first-90-day output target, and weekly reviews of which concepts to scale or cut.
Next steps
Send Vacic the brief and ask them to confirm the placement scope, timing, and commercial terms in writing.
Define the test brief and scoring criteria before evaluating candidates, and document the scores.
Ask for the underlying numbers behind the $500-per-video versus in-house example so the brand can size its own comparison.
Set the first-90-day target and weekly review cadence with the media buying team before the editor starts.
If reach rather than production is the real need, raise it early and ask for a sponsorship offer, engagement metrics, and an audience survey.
Success measures
Count genuinely different concepts shipped per week, not variations on one ad.
Compare the cost per shipped concept with the brand's current $500-per-video or agency-retainer cost.
Track the time from a winning ad to the next iteration built on it.
Check whether the placed editor is integrated into the brand's team and performance data loop or still working through a middle layer.
Why it holds
The test-task stage matches what Vacic says about sourcing: real tasks for a specific brand, portfolio second. The in-house placement matches the core argument in their posts: the fix is a full-time editor working directly with the brand's team rather than an agency's monthly cap or a rotating freelancer. The volume cadence matches the Meta creative-variety argument, where distinct concepts, daily output, and weekly testing feed the algorithm.
Choose Nikita Ganzina when the creative itself is the bottleneck rather than the hire.
Read more
The posts work through what makes an ad convert — stopping the scroll with a hook, naming the problem quickly, making the product and its value obvious, using social proof, handling objections, then closing with a reason to act — and argue that cheaper AI production and bigger UGC libraries still fail when the editing is weak or the first seconds give no reason to care.
A brand already producing ads that will not sell gets more from that lens than from another placement.
It also fits a brand that intends to keep production on its own terms and set the editing standard internally, because the posts are about editing decisions and output rather than about who supplies the editors.
Sava Vacic's posts do not say anything about recruitment, vetting, or placement offers.
A brand that needs someone to find and test editors still has to run that process itself, and Ganzina's posts do not describe a candidate-testing method the way theirs do.
Ask for examples of their broader work and their commercial terms.
Choose Jim Schroën when the brand wants the ads produced for it rather than hiring one editor into its own team, or when the creative question is really a distribution question.
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One post advertises full-time remote editor roles inside a team of editors and creative strategists working on DTC brands spending over €100,000 a month on paid social — a pod with the strategist layer already attached, which suits a brand that cannot or will not build the function internally yet.
The other post goes further upstream: it argues that creator and affiliate content is what AI tools cite when recommending products, and offers a guide on building an affiliate program through a comment-and-DM request.
A brand whose paid social is working but whose products are invisible in AI answers has a reason to talk to Jim Schroën that has nothing to do with editor hiring.
The pod sits inside Schroën's organisation, so the brand gets output through a supplier relationship instead of owning the editor — the opposite of what a brand trying to build its own editing team wants.
The posts describe hiring at that organisation rather than a package the brand can buy directly, and the affiliate guide arrives through a comment-and-DM mechanic rather than a published resource.
Ask for the pod's terms and the affiliate offer's scope.
Choose Jessie Healy when the brand has to decide what its ads should be doing before it decides who edits them.
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One post audited five e-commerce brands and found their ads all written for the bottom of the funnel — "Shop now," "Back in stock" — assuming an audience that already knows the brand, and argues that smaller brands need ads that create interest, explain the problem, and answer objections before asking for the sale.
The other applies that thinking to apparel, where the aesthetic and the person on screen carry more than the message, and where the fix is a systemised creative pipeline: a bank of different styles, UGC that looks unplanned, creator films, polished statics, behind-the-scenes and founder content, and a testing cadence that keeps fresh looks in the account.
A brand that wants a volume engine but has not settled its creative strategy gets a useful frame here first.
Healy's posts are analysis and advice, not a hiring or production offer; they do not say that they take on a brand's creative output or supply editors.
They come before editor placement, so a brand that only needs an editor sourced quickly may find the strategy lens too slow.
Ask whether they take on production or supply editors, and what their engagement model is.
This page describes five LinkedIn posts by Sava Vacic.
They cover editor sourcing, an e-commerce video editor hiring need, in-house performance editing, Meta creative volume, and team capacity.
The posts do not state publication dates, so they cannot be ordered or tracked over time.
The posts contain no engagement counts, audience breakdowns, or published sponsorship offer; cost and performance figures are reported as stated in the posts, without independent verification.
The posts do not name clients or employers.
The absence of a published sponsorship offer does not prove that sponsorships are never accepted.
