Kevin Viet Tran

They report writing ten scripts a week under two mentors, logging a stated hypothesis for each test and reading the numbers on every ad.

• That feedback loop, not course material, was the training that mattered.
• Of the standard copywriting canon, Kevin says they read only The Boron Letters in full and abandoned Breakthrough Advertising after fifteen pages because it was boring.
• They recommend one focused hour a day: one idea, one piece of copy and one ad breakdown.

Kevin's entry into the field is the illustration: with no ad experience and a fired 9-to-5 behind them, they went all in on a test task for an e-commerce company.

• Mentorship came later.
• A CMO at a growth agency and the CEO of a well-known German creative agency, who had mentored the CMO, made Kevin write scripts, hooks and VSLs personally and without AI, with plenty of failures along the way.

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A good hook now takes about a minute, and a really good seven-to-eight-minute unaware video sales letter takes about thirty minutes, excluding research; their first five-minute VSL took three hours.

• People Kevin is currently training stall on hooks for twenty minutes or more.
• They attribute that gap squarely to repetition.

Kevin's post compares a one-minute hook with trainees spending twenty minutes or more on the same task. The stated difference is how many times each person has done it.

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Their proposed method: find the people who own brands, write example campaign plans and scripts for their actual product, show how the campaign plan was built and why it should work, then offer to write their next scripts free for a one-week test and ask for the chance to prove they perform. Then repeat: send lots of outreach, new campaign plans and videos every day until the brand sees someone worth investing in.

Kevin says the volume of work and work ethic — not a portfolio or experience — led to a full-time role at an eight-figure brand. The brand saw potential, and they went all in once inside.

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They say the deciding factor is whether a candidate is all in on the brand's vision and shares the company's goals.

• Given the choice, they prefer someone with no skills and no experience whose commitment is clear over a technically stronger candidate without it, and say a gut no ends the process.
• Kevin has hired wrong several times, describing the result as expensive, stressful and unending; they also note that some people working on the side take the brand's learnings and leave.
• The hunger filter is a personal rule formed under those conditions.

Kevin's image of an applicant worth backing is a junior who sends free work every day, breaking down briefs and scripts for a real product, rather than someone with a nice CV. In the same post, they point to weak hires they attribute to candidates who were only in it for the income.

Kevin says the argument that got them hired as an inexperienced junior is the same reason they now back inexperienced juniors.

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They warn that outsourcing the thinking that makes money brings later costs in time and headaches — scripts, hooks and test hypotheses stay human work.

• Their hiring posts show AI as a required production skill, not a substitute for judgement: the editor they recruit is expected to be fluent in named AI tools and work across AI cartoon, claymation, movie-style and Suno-music ads.
• The two positions fit together: AI multiplies the number of ad variants that can be produced, while strategy and test reasoning remain manual.

The performance video editor posting for an eight-figure e-commerce brand asks for editing experience at seven-to-eight-figure brands, an understanding of what makes an ad perform, and fluency in HeyGen, ElevenLabs and Higgsfield. Its German-language counterpart repeats those tools and adds native German plus a portfolio containing German-language AI cartoon ads, pointing to work aimed at the German market.

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Start here for the fullest account of how Kevin works and says they built the skill.

Kevin describes landing a first e-commerce creative-strategist job with no ad experience, then focusing on the test task rather than the CV.

• They say the training that mattered came from a CMO at a growth agency and an agency CEO who had them write everything personally—scripts, hooks and VSLs, no AI—at roughly ten scripts a week, recording a hypothesis for every test and reviewing the data on every ad.
• They report never watching a copywriting course, reading one book properly, The Boron Letters, and quitting Breakthrough Advertising after fifteen pages.
• The figures are specific: a first five-minute VSL took three hours, while a seven-to-eight-minute unaware VSL now takes about thirty minutes, excluding research; a good hook takes about a minute, while people they train stall on hooks for twenty minutes or more.
• They attribute the gap to repetition and recommend a daily hour spent on one idea, one piece of copy and one ad breakdown.
• They also report a best-performing ad that spent around 300k, consistent ads spending 10k a month, and smaller profitable ones.

For brands planning a campaign

Useful for judging how quickly a creative partner can turn around hooks and VSLs, and whether their method fits a brand's testing cadence. Kevin frames output speed as a function of feedback volume and hypothesis-driven testing, not tooling—a claim to check against your own creative review cycle.

Start here to see how Kevin reasons about people and output, not just ad craft.

Kevin argues that a CV is worthless for a junior creative strategist with no experience because an empty page never convinces a brand owner to take a bet.

• Their proposed route: find brand owners, write example campaign plans and scripts for their products, explain how each plan was built and why it should work, then offer to write the next scripts for free for one test week.
• They say a full-time role at an eight-figure brand came from the volume of work and work ethic, not a portfolio.
• From the hiring side, they call hiring the most important thing a brand or agency owner does, describe bad hires as expensive, stressful and recurring, and say some people working on the side take the learnings and leave.
• Their stated rule is to hire hunger over skill: someone with no skills or experience who is fully committed and shares the company's vision, with a gut no overriding everything.

For brands planning a campaign

Directly relevant to a brand looking to scale ad output with junior talent. Kevin's approach suggests auditioning candidates on unpaid test work and filtering for commitment and vision fit rather than credentials—a route to weigh against your hiring and contractor policies before adopting it.

Start here for a concrete view of the tools and skills the operation expects from an editor.

Kevin posts a remote opening for a performance video editor for an eight-figure e-commerce brand.

• Requirements include editing experience with seven-to-eight-figure e-commerce brands, an understanding of what makes an ad perform, and fluency with AI tools named as HeyGen, ElevenLabs and Higgsfield across formats including AI cartoon, claymation, movie-style and Suno music ads.
• Applicants also need a portfolio containing AI cartoon ads in German.
• The offer includes pay that grows with performance, work alongside experienced editors and marketers, and a front-row seat to how an eight-figure brand builds and iterates its ads.
• A German-language version of the same posting (https://www.linkedin.com/posts/kevin-creativestrategy_wir-suchen-einen-performance-video-editor-activity-7495781914985885696--Afk) asks for native German and names HeyGen, ElevenLabs and Higgsfield.

For brands planning a campaign

Useful as a benchmark for an in-house or agency editor job description and for testing whether a creative partner can produce AI-assisted ad variants at volume. The explicit German-language requirement points to German-market work, which matters if that is one of your campaign territories.

They report writing ten scripts a week, analysing the data on every ad and recording a hypothesis for each test, with feedback from named mentors as the correction loop.

• They say the only copywriting book they read in full was The Boron Letters, and they stopped reading Breakthrough Advertising after fifteen pages because it did not move the needle.
• The same post credits this approach with a best ad that spent around 300,000 and consistent 10,000-a-month spenders—figures they state without third-party confirmation.

Kevin recommends a daily practice: one idea, one piece of copy and one ad breakdown in a focused hour, early, with distractions cut.

For brands planning a campaign

A brand hiring Kevin Viet Tran is buying an output-driven operator, not a credential-led one.

• Expect a high volume of scripts and hooks, each tied to a stated test hypothesis.
• Ask for the ad data behind the spend claims before treating them as benchmarks.

Examples: Source 1

Their first five-minute VSL took three hours. They say trainees get stuck on hooks for twenty minutes or more, framing that gap as a visible difference in experience rather than talent.

For brands planning a campaign

Fast drafts suit a brand that needs a high volume of paid-social variations to test.

• The claim measures drafting time, not performance.
• Run a pilot comparing the hooks and VSLs with the brand's existing creative before scaling to that cadence.

Examples: Source 1

They describe landing a full-time role at an eight-figure brand through the volume of that outreach and their work ethic rather than experience.

For brands planning a campaign

Brands hiring junior creative talent can lift the template directly: ask applicants for product-specific briefs and scripts, then run a time-boxed test week before committing. The approach also signals that Kevin's team hires based on demonstrated output rather than portfolios.

Examples: Source 1

They prefer someone with no skills or experience over a stronger technical candidate without that commitment. They describe repeated wrong hires as expensive and stressful, say a gut no ends the process, and note that some people working on the side take the brand's learnings and leave.

Kevin says the approach has produced wrong hires several times, making the hunger filter a personal rule rather than a tested hiring method.

For brands planning a campaign

If a brand works with Kevin or their agency on creative hiring, expect trial tasks and a values screen alongside skill checks. Treat the hiring philosophy as a signal of how their team is likely to be staffed and prepared for campaign needs, not a guarantee of outcomes.

Examples: Source 1

Requirements include editing experience for seven-to-eight-figure e-commerce brands, an understanding of what makes an ad perform and fluency in AI production tools.

• HeyGen, ElevenLabs and Higgsfield are named, alongside Pixar-style AI, cartoon AI, claymation, movie-style ads and Suno.
• The German version additionally requires German as a native language and asks for a portfolio including German-language AI cartoon ads.

For brands planning a campaign

These posts show the creative capacity Kevin builds around: AI-assisted video production for e-commerce, handled by editors who also read performance data. A brand needing video variants can use the stated requirements as a checklist for the skills in demand, and the German-language version as evidence of work aimed at the DACH market.

Examples: Source 1 · Source 2

Their hiring posts align with that position: AI tools are expected in an editor's kit, while scripts, hooks and test hypotheses remain human work in their account of the job.

Kevin treats AI as a production and editing tool while keeping strategy, hooks and test reasoning manual. The two positions are consistent across their posts.

For brands planning a campaign

For brands weighing AI-assisted creative, Kevin's framing supports using AI to increase production volume while leaving script and hook decisions to the strategist. Ask where AI fits in a specific deliverable before briefing.

Examples: Source 1 · Source 2

Timpano influenced Kevin's early ad writing.

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They name the same dividing skills — hooks, pacing, retention and creative testing — and treat AI workflows as part of ad production. Both argue that hiring generalist editors who cannot make ads sell wastes brand money.

Sava's posts approach the problem through recruiting and cost: where an editor is based matters less than whether they can make ads sell, and bringing a performance editor in-house beats paying per video or overpaying an agency. Kevin writes from the practitioner's seat about how strategists build skill through reps and why hiring should prioritize commitment over credentials.

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Like Kevin, Nikita sees cheap AI-driven video volume as worthless without a story and strong opening seconds.

Nikita focuses on editing craft and the small decisions within an edit, such as cutting a beautiful opening shot to reach the point faster or putting a rough customer quote on screen because proof outweighs aesthetics. Kevin focuses on the writing side — scripts, hooks and long-form VSLs — and the repetition that makes drafting fast.

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Both treat AI as part of production, not a replacement for judgement.

Jim's public posts focus mainly on hiring notices and the argument that AI shopping tools cite creator and affiliate content.

• Their focus is agency team-building and AI visibility.
• Kevin focuses on individual skill-building in copywriting and hooks, and on what to look for when choosing a junior strategist.

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Sava Vacic's posts describe US DTC brands paying around $500 per video or a large full-time salary and still not getting ads that perform, and argue the real problem is that most editors, including US-based ones, are not performance editors.

• The proposed fix is to bring one performance editor in-house at roughly five times lower cost, working directly with the brand's team.
• The hiring post sets out what that role covers: multiple short-form ad variations each week built from UGC, raw footage, product clips, testimonials, voiceovers and AI-generated assets; performance ads across Meta, TikTok, Instagram and YouTube; UGC, mashup, product demo, testimonial, founder and short-form VSL formats; AI tools used from asset creation and voiceovers through editing and iteration; and iteration on winning ads from performance data.
• For a brand whose creative spend is the problem and whose strategy layer already exists, this is the more directly applicable half of the same decision.

Sava Vacic's material addresses who edits the ads and what that costs; it does not cover how the hooks, scripts and hypotheses get written.

• Kevin Viet Tran's posts state a weekly practice (ten scripts a week, a written hypothesis for every test, hook and VSL writing speed) and a method for vetting junior strategists, none of which appear in Sava Vacic's posts.
• Choosing Sava Vacic leaves the strategy and hiring-pipeline needs unanswered.
• The reverse also holds: their posts do not discuss editor pricing or the local-versus-in-house cost comparison, so a brand whose margin problem is per-video cost should not expect that answer from them.
• Ask both for ad-account data and verified campaign results.

Examples: Source 1 · Source 2

The posts draw a hard line between making video look good and making a direct-response ad convert, then list what a performance ad has to do in sequence: stop the scroll with a hook, introduce the problem quickly, make the product and its value obvious, give people a reason to trust the storytelling, use social proof, handle buying objections, and finish with a clear call to action.

• They also give concrete editing calls a brand can hold an editor to: cutting a beautiful opening shot because it takes four seconds to reach the point, putting an unattractive customer quote on screen because proof matters more than polish, and making the edit feel native to the feed rather than like a commercial.
• The second post extends this to volume: AI is making production cheaper and fifty variations of an ad easier than ever, but more ads do not automatically mean better ads, and the scarce skill is turning raw material into ads people want to buy.
• For a brief where the creative bottleneck is frame-level judgement and the volume-versus-care question, this is the closer match.

Nikita Ganzina's posts describe editing decisions and the volume problem; they do not describe writing scripts or VSLs, running a hypothesis per test, or recruiting and vetting junior creative strategists.

• Those are exactly the pieces Kevin Viet Tran documents, and they are the pieces a brand needs if it has to build the thinking layer before it can build an editing standard.
• The tradeoff runs the other way too: their posts give quantity and cadence for scripting but no comparable checklist for judging an edit, so a brand that already has scripts and wants a diagnostic for weak ads gets less from that material than from Nikita Ganzina's.
• Ask both for account-level performance information; each relies on the author's own description of their practice.

Examples: Source 1 · Source 2

The hiring post describes a full-time remote editor role inside a team of editors and creative strategists producing winning ads for ambitious DTC e-commerce brands: editing short-form and long-form paid-social ads, turning concepts into winning ads with strategists, editing UGC, VSLs and direct-response creatives, and improving from performance data.

• The stated requirements, including DTC experience, having worked on brands spending EUR100k+ per month on paid ads, and agency or pod experience, function as a public standard a brand can measure a prospective partner or hire against.
• The second post, from GoViral, adds a different job: UGC ads for DTC brands, plus the argument that 58% of shoppers now use AI tools instead of regular search to find products, that 85% of what AI says about a brand comes from other websites including creator content and reviews, and that affiliate, reviewer and creator networks are what get a brand cited in ChatGPT, Claude and Google AI.
• A brand whose brief includes an affiliate or creator-network program, or that wants an agency-side pod rather than an individual, will find more here than in their posts.

Jim Schroën's first post sets a hiring bar; the second is partly a lead-capture offer that asks readers to connect and comment to receive a third-party guide, so it documents the AI-visibility argument and GoViral's UGC work rather than a full service description.

• Kevin Viet Tran's posts, by contrast, document their own output and cadence in more depth (script and VSL volume, hook-writing speed, a written hypothesis per test) and an explicit test-week model for bringing in junior talent.
• A brand that needs to see how the work is actually produced, or that wants to build rather than buy a strategist pipeline, gets less practical detail from Jim Schroën's material.
• Ask both for audience demographics, rate cards and campaign-level results; the choice otherwise rests on operating model and role design rather than measured performance.

Examples: Source 1 · Source 2