How Cal AI grows

Base rate of $350-$450 for four posts, plus a couple of unlockable view bonuses. Cap bonuses, usually at 1M views: profit comes from the one or two viral videos a month, so you need to keep their upside; people don't perceive much difference beyond a million; and very viral views reach a broad, less-targeted audience that converts worse.

Take the creator's 20 most recent videos, pick the 5 (or 10) worst performers, average their views, and base the CPM price on that worst-case average. Be careful with very recent videos that may still be growing.

When a creator says they can 'easily get a million views', agree and add a minimum view clause a couple hundred thousand below that (e.g. 800K, or 700K after checking their page), framed as 'just for our safety' and 'so it's not stressful for you'. Payment is tied to hitting the floor each month. Check their actual numbers first so the floor is realistic and hit every month.

Started with ~5 marketing assistants, grew to ~25, each pushed to contact 100 influencers a day (~2,000/day; real output 40-70 on bad days). Assistants hired through an outside staffing company. Outreach is by email, not DMs (DMs are rate-limited and work mainly with a big personal brand). Creators in the US, UK, France, Germany, Spain; not picky as long as the creator could fit the app into their video at a decent CPM. Assistants send a Calendly link for a manager call; managers close. Signing goals of 50+, later 100 creators a month. Funnel: ~10% reply, a few book a call, ~1 in 1,000 signs. Outreach tracked in an internal system.

Message signed creators monthly: 'Do any of your friends want brand deals?' Pay ~$100-200 to the creator if a referred friend signs. Referred creators send a personal phone number, so you call the influencer directly, sometimes bypassing their management.

Always ask influencers to cross-post. Offer the deal (e.g. '$400 for four posts'), then add 'just cross-post it on both platforms' (Instagram and TikTok) as if it were nothing. If they push back, downplay it: they're already making the video, so posting it twice costs them nothing. Making it sound like a big deal makes them treat it as one.

Set a base rate for a package (about $350-450 for four posts), then let creators unlock a couple of view bonuses so they are incentivized to go viral. Cap the bonuses, usually at the 1M-view tier, and pay nothing beyond it. Reasoning: most videos lose money, and the profit comes from the one or two a month that go viral, so you need to keep that upside; creators don't feel much difference between 1M and 2M views, a video that hits 1M often keeps growing to 1.3-5M, and very viral views reach a broad, less targeted audience that converts worse.

Very early after launch, when there is little background noise, watch downloads against each influencer video going live: Cal AI had zero downloads on days with no video, and later a baseline of ~100 downloads an hour that jumped to ~200 when a video posted. Note which creator types cause spikes, what their comment sections look like, and the content format, then generalize those patterns ('this type of content converts like this; this kind of comment section is a good sign') to judge videos later, once millions of old videos keep getting views and per-video attribution is impossible.

Cal AI ad seen in the Meta Ad Library: 9 seconds long; hook 'best way to track calories' ("Wait, so is this literally all you have to do to track your calories?"), shows food then the app in use, ends with the App Store link. Started June 3 and still active in early October.

Thesis: people who track calories most are in health and fitness, which has millions of creators but few brands to work with them (protein powder, athleisure), so many had never had a brand deal. These creators already posted 'what I eat in a day' / 'to look like this you have to eat like this' videos about once a week, so the ask was simply to scan their food with Cal AI on camera. Jake's test for whether this transfers: huge creator supply, few competing brands, and content that naturally fits the app (an astrology app fails all three, and its few creators may be locked into exclusivity deals).

Cal AI's demo was a three-beat 'magic moment': scan, analyze, result. The streak feature popped up right after the first scan of each day and added a fourth beat, so creators were told not to film their first scan of the day.

Views and followers can lie; comments can't. Niche level: read the comments on the big creators in a space and check whether people are asking for a solution your app provides. Creator level: compare comment sections, e.g. a leg-day video whose comments are all men posting fire/sweating emojis versus one where viewers write 'thank you, I wasn't sure how to work my hamstrings'. The second kind converts. Look for a cult-like following, not just a following.

Set the rate so the creator's average views roughly break even or make a little profit (the most likely outcome). Real money comes from the occasional mega-viral video, and with a flat fee all of that upside is profit. Avoid per-view pricing where possible. Bonuses and scaled deals were also used on top.

Work out revenue per thousand views (RPM) within the niche. Early on, with no other marketing, measure it directly: sales on a day a creator posts vs zero sales on days nobody posts. Later, keep reading smaller spikes. Never pay a CPM above that RPM; then set each creator's rate from that profitable CPM times their expected views. Accept that many creators will say no.

Public in-app affiliate offer: anyone (including creators who wanted a promo code) can sign up and earns $10 per paid signup, not per download. One-time payment, about a third of a ~$30 annual sale, so no lifetime renewal liabilities.

Don't force formats or rules on influencers: keep them making the content they always make (e.g. 'what I eat in a day') and slide the app into it. Only give general guidelines: show the app in a certain way, have it come in within a set number of seconds, and include a tag in the caption; otherwise full creative control. Because the video matches the creator's usual content, you can estimate their average views per video with confidence and price the deal (CPM) on that. The failure mode: pricing on a creator's ~1M usual views, then forcing an infomercial-style 'let me tell you about Cal AI' video that gets ~50K views and puts the brand thousands of dollars in the red.

Started with the app integration required at a later second mark so the video wouldn't feel like an ad and would go more viral. Then tested bringing it in earlier and earlier across influencer videos until finding the earliest point that didn't hurt views: 20-30 seconds in for Cal AI. Earlier integration helps conversions, later helps views; the right timestamp is unique to each app and must be tested, not copied.

Picked the health and fitness niche, which is oversaturated with creators but has few brands (mostly protein powder and athleisure), so many creators had no way to monetize. Pitched them to show the app inside content they already make (what I eat in a day, losing weight, building muscle): before eating, scan the food with Cal AI on camera. Easy for creators and didn't disrupt their schedule. Then reached out to thousands of creators to sign them.

Don't force formats or scripts on influencers: only general guidelines on how to show the app, how many seconds in it should appear, and a tag to include in the caption. Otherwise full creative freedom. Reason: if a creator deviates from their usual format (infomercial-style 'let me tell you about Cal AI'), views collapse (e.g. 50K instead of the 1M the CPM was priced on); keeping the normal format lets you estimate average views with confidence.

Started with a required later second mark for the app integration so it wouldn't feel like an ad, then tested bringing it in earlier and earlier until finding the earliest point that didn't hurt views. For Cal AI that was 20-30 seconds in. A friend's app found 60 seconds. Test your own number.

Offer a deal like $400 for four posts and add, as a casual aside, that each post should be cross-posted on both platforms since the video already exists. Keep it low-key: if you make it a big deal, creators will too.

Managing a 10K-view creator takes as much work as a 1M-view one, so the floor is 25,000 average views per video. Very large creators (millions per video) have more general audiences that follow recommendations less; the sweet spot is 25K-1M views per video, where audiences are cult-like and convert best.

Compare comment sections: a real community (long personal replies, people replying to each other) converts far better than fire-emoji spam. To catch fake engagement, click the profiles of good commenters: bots have zero posts, follow ~10 people and have zero followers, and the same fake accounts show up on every video.

Built an internal tool: one click sends the contract; once signed, the creator is added to the platform and gets a text with the content brief asking which day they will post; the reply is piped into a content calendar; each morning the team gets a batch of texts to send to creators scheduled to post that day.

TikTok and Instagram block messaging after a certain number of DMs per day, so Cal AI created about 20 extra Cal AI accounts, one per outreach specialist, each reaching out to hundreds of creators a day.

Outreach accounts carry a person's name so creators know they aren't talking to a faceless brand. Instead of a wall of text, send a voice memo so it feels like a real person; record one generic memo and copy-paste it to every creator.

Sideshift is the easiest source (post a job, creators apply) but ~99% of applicants aren't good. Preferred: type 'UGC creator' into the explore page and scroll for people who feel real, not scripted. Pay a base of ~$25-30 per video for all videos (~$600/month) plus a view bonus; one 1M-view video a month brings the effective CPM to ~$1.50-2.

When a creator replies 'what's your budget?', don't lead with price. Explain the deal first: seamless videos, long-term partnership, no script, 'keep doing what you're doing and sneak our app in'. Once they seem interested, ask to jump on a call to finalize; discuss rates only on the call. Manager runs the same script on every call, starting by getting to know the creator. Deals are declined if the creator won't come down to a profitable price.

Pick creators who can fit the app's 'golden moment' (snap a photo of food to log calories) into their normal video. No script and no heavy ad read; creators often just show themselves scanning a meal without naming the app. The app must appear within the first 15 seconds.

Sign large creators who post day-in-the-life vlogs. They show their day and quickly scan a meal with the app, often without saying its name. Aim for four videos per month per creator so followers see it repeatedly. Track with promo codes. Example: Jessi from The Secret Lives of Mormon Wives.

With Jessi (The Secret Lives of Mormon Wives), timed a couple of posts just before season 3 was released and a couple just after, when everyone was visiting her page. Deal landed through a team member's relationship with her influencer manager.

Monthly competitions: prize (cash or voucher) for the assistant who contacts the most influencers, and for the one whose referrals (tracked by 'referred by' on signed deals) sign the most.

Discount offer used as an extra placement (on opening the app a second time, on transaction abandonment, or after a trial cancel). Instead of a plain '80% off' paywall, the user sees an animated spin wheel that stops on a discount ('You got 80% off. Tap to get it'); tapping continue opens the discounted paywall. Idea: add excitement and make the discount feel earned. Borrowed from e-commerce popups.

Ignore generic 'good CPM' benchmarks. For each influencer video, work out how much revenue it made relative to its views to get your RPM (revenue per thousand views, e.g. $5), then only pay creator rates that put your CPM under that number. Expect a lower affordable CPM than paid ads (no direct link, more friction), and lower still for UGC accounts with no audience trust. Apps with low order value and LTV (e.g. $30 / $50) can't match the CPMs that clothing or telehealth brands with far higher LTV pay.

Dawson Gibbs, one of the first creators contacted, said yes and was willing to post more, iterate and try different angles and formats without charging per extra request. Cal AI reciprocated with unprompted bonuses and a real friendship. Once a format worked with him, it was copied and pasted to other fitness creators.

Cal AI made a build of the app specifically for creators so that while they scanned food on camera, both the Cal AI name and the logo were visible.

For creators whose integrations were subtle, videos carried an on-screen caption 'tracked with Cal AI' to drive the brand home. For creators whose integrations were already obvious, the caption was left off because it would hurt views. Part of constant ongoing testing of small details.

Thesis: UFC fighters track food meticulously when cutting weight, so a photo calorie tracker is useful and interesting to them and could open a new niche of 1,000 more creators. Cal AI signed a couple of big UFC creators.

Judge content quality, not current views: a cult-like following is a lagging indicator. Creators without a track record can be signed on cheaper deals. Jake signed a funny, charismatic creator (roughly his 12th-15th signing) getting 10-12K views; kept a friendly relationship through two quiet months; in month three a video hit seven million views.

Once 50-70 influencers posted per day and several went viral the same day, spikes could no longer be read one by one. Jake built a 'renewal score' combining many metrics (engagement such as comments/likes/saves alongside views), plus incrementality checks comparing the demographics of a creator's following with where the spike showed up.

Build personal relationships with creators, especially early when there are few. Pay discretionary bonuses ('you crushed it this month, here you go') even when the deal had no bonus. Handle creators you can't afford with kindness. Good treatment leads creators to refer other creators.

When a creator demands a number (e.g. $1,000 a month), they care less about deliverables once the cash is met: agree to the fee and raise the number of posts so the effective CPM stays profitable. Get on calls, be a regular person rather than a 'sleazy agent', and meet in the middle.

Thousands of messages to creators, kept up every day (on the order of 100 a day) for 18 months. Most didn't reply; many who did asked for rates too high to afford, and every negotiation was hard. Jake's view: being willing to do this grind is the edge, and it is harder now because creator rates have risen with more brands competing.

Organic videos swing for a viral hit with a subtle integration; paid pays for every view, so every view should make clear what the product is. Cal AI invested in dedicated paid creative with a hook related to the product (not a random scroll-stopper) and a quick, interesting value prop. Jake learned the craft from friends at Speechify.

Used Tribe, where creators make ad creative for free and get paid a percentage of the ad spend that goes behind their videos, aligning their pay with what works.

Keep messaging congruent from ad to app. In onboarding, reiterate the pain points the marketing hit ('you're here because this resonated'), drive home what that pain has caused, offer the easier way and what it helps achieve, then ask what solving it is worth, and present a modest price ($30 a year) after several minutes of onboarding.

Despite running many price experiments, co-founder Blake Anderson insisted on optimizing for mind share, not profit: the most popular app is the easiest to buy, which means the lowest price. About $30 a year vs MyFitnessPal's ~$70. Fit the audience: young users with little disposable income who haven't felt the pain long enough to pay much to fix it.

Ignore target CPMs; compute RPM (revenue per 1,000 views) from past creator videos, then price each influencer deal on expected views so CPM stays under RPM. Paid ads can afford the highest CPM (direct link, least friction), influencers need a lower CPM (viewer must go search the App Store), UGC accounts lower still (no audience trust). High-LTV categories like clothing or telehealth can outbid a typical consumer app on CPM.

At launch, watch which creators and formats cause download spikes and what their comment sections look like, then use those patterns to judge content later. Early on there were no downloads on days without a creator video; later a ~100/hour baseline would jump to ~200 when a video went live. At scale, old videos keep getting views, so use data analysis and incrementality tests.

Ignore follower counts; judge creators by average views per video. Target creators who average huge views but have few followers (e.g. new accounts going viral): they're not used to big brand-deal fees because brands pay on followers, so they accept reasonable rates.

UGC creators open new TikTok/Instagram accounts dedicated to the app (e.g. jake.eats, jake.tracks) where every video is about Cal AI. Unlike influencers, micromanage them and copy formats already proven to go viral. New accounts are shown mostly in the creator's own country, so hire creators in the country you target.

Add paid ads once cash flow allows, because influencer/UGC views are volatile while Meta spend gives steady ROAS. At first, reused influencer/UGC videos as ads (the only content they had). Once funded, built a paid ads department with dedicated ad creators: ads bring the product in early and hard-sell, since you pay for every view and there is no algorithm boost to protect.

Where an influencer lives doesn't matter; where their audience is does. Ask for audience demographics when signing; skip a creator with ~1% of views from your target country.

At launch the app was unknown, so aim for the lowest CPM to reach as many people as possible, assuming the first exposures won't convert ('seen seven times' rule). As more creators promote it and viewers recognise it, raise what you pay per deal. Goal: sign as many influencers as possible and saturate the fitness space.

Split fitness into sub-niches: bodybuilders, gym bros, women's fitness, weight loss. Then tested mom influencers (expensive because they know they convert), and comedy/viral creators (e.g. the 'no door, no problem' drive-thru guy, signed to scan fries at McDonald's). Some niches only needed one video or one creator.

Worked with recipe, normal cooking and mukbang creators on the assumption that food viewers think about calories. Cut them early; healthy-meal creators were kept but converted only moderately.

Team member built a relationship with an influencer manager for the Mormon Wives cast, which led to deals with Jessi. When working through agents, push to have the influencer added to the shared group chat so you build a direct relationship, even though agents often refuse. Keep in touch with creators long-term.

After one creator paid $20K for a month drove $120K of signups (~$100K profit), signed another creator in the same niche.

Four co-founders each owned one domain: CEO (Zach), co-founder/investor/advisor (Blake), CMO/COO for marketing and operations (Jake), CTO managing the tech team and product (Henry). Complete trust to handle their area; team said this avoided fights.

Shipped a groups feature (community feed) where friends log food and stay accountable together, with leaderboards showing longest streaks; later added public topic groups (weight loss, bulking, recipes and meal prep), inspired by Strava and Ladder. Aim: retention plus a network effect that the many Cal AI clones can't copy.

Product-led growth features: progress photos users can post to Instagram stories showing weight lost/gained; shareable meal cards showing calories tracked with Cal AI; milestone badges for consecutive days logged (e.g. a full year) to post on stories.

Because Cal AI grows mainly through influencer videos, and every video shows the same three screens (camera, loading screen, food detail page), design work focuses on making those three screens as easy to understand on camera as possible.

Main paywall has a free-trial toggle; turning it off does not change the price, it just lets users who want to buy now do so and feel in control. Guest uses this for high-intent apps (health and fitness, weight loss) and the discounted version for lower-intent or younger audiences; advises testing both.

Cal AI pays many creators (and puts spend behind some posts) for TikTok day-in-the-life videos: workout, come home, snap a photo of a meal, get calories, move on. Shows the core differentiator (logging by photo) as part of normal life rather than as an ad.

Scaled to more than 2,000 influencers. The host stresses this was an influencer model, very different from paying zero-follower creators to make UGC.

Mukbang creators eat 10,000+ calories in one sitting; the idea was a 'wow factor' of showing how easily the app tracks all that food before they eat it.

Using management-consulting habits, Jake built systems and automations in Google Sheets (his 'Magnum office') to track deals, posts and payments for hundreds of creators, since existing tools disappointed him. He later turned it into his own software.

A couple of months in, Cal AI started paid ads (Meta) to diversify risk and because paid takes less work per dollar than influencers. The first creative was recycled influencer content.

The Cal AI team shared successes and failures on Twitter while building. This invited copycats, but Jake believed clones lacked the obsession behind many small compounding improvements. Viral threads about Cal AI clones' revenue kept pointing people to Cal AI.

Dawson, a fitness creator with ~200K followers, partnered with Cal AI as its first influencer and fronted its own TikTok/Instagram brand page for ~5 months while also posting on his page. Because the app itself was viral, videos just flashed the app on screen rather than pitching it with his authority.

Dawson used his fitness-niche network to recruit creators and influencers into Cal AI's program (including creator sub-accounts), paid a referral fee per person while working with the marketing team.

After health and fitness, kept testing new creator sub-niches; new moms worked. Continuous testing ('always be testing').

Tested mukbang creators and UFC fighters as new sub-niches for the calorie app.

Built an internal system where, after an assistant sends the first outreach email, AI handles the replies and initial negotiation/persuasion, then hands the creator off to a manager for a call.

Did a couple of day-in-the-life videos with UK Love Island's Harry Cooksley. Tried to also sign his partner Shakira through him, but it never happened.

Early on, a creator (Dawson) with his own personal brand made UGC and posted on the Cal AI page. Stopped once influencer deals gave better CPMs. Now restarting UGC because agents have pushed influencer prices up. Guest would run UGC and influencers side by side for a new app: UGC gives cheaper views but likely lower conversion.

Zach, with childhood friend Henry, sent a DM to Blake, who had already built AI apps, and they formed Cal AI; later offered a COO role to Jake after seeing his work at StudyBuddy. Blake says he would not have replied to a copycat pitch.

At end of 2024 the team received low eight-figure offers; co-founders called each other constantly and reached a collective decision not to sell because they saw more growth ahead. Later sold for an undisclosed larger amount.

MyFitnessPal acquired Cal AI not for its tech but for its top-of-funnel skill (Zach and team are strong distributors), aiming to keep new users coming in and eventually graduate them to MyFitnessPal's fuller feature set. Guest's reading, prompted by the host.

Focus on getting users through Cal AI's 3-day trial without cancelling: fix bugs and redesign the screens people touch all the time when logging a meal (food database, camera, food detail page).

Added streaks so users come back daily to log meals, modeled on highly retentive apps like Duolingo.

Cal AI's main growth is influencer marketing with fitness creators: there are very many, they are reasonably priced, and a calorie tracker doesn't conflict with the coaching they sell. Contrast with Sway, where dating coaches sell profile feedback themselves, and beauty creators, who are expensive because of makeup brand deals.

Started with a scrappy app that did not fully do what the marketing claimed, sold it through strong distribution, then built out the underlying tech. Priced at $29.99/year.

Cal AI hit a major inflection when it seriously ramped paid ads on top of influencer marketing; same pattern at Sway. No detail on platforms or spend.