Most crypto teams go looking for a vouch at the exact moment it's worth the least. Why? Early on, a vouch is the only proof you've got. No users, no volume, nothing anyone can check. So one credible person saying "I've used this, it's good" does the job your numbers will do a year from now. But most teams save the big names and the KOL budget for after the raise or right before TGE. By then there's plenty of proof around, and one more endorsement barely moves anyone. We wrote up the full version on our Telegram, including the two things that decide whether a vouch helps you or backfires t.me/theagiclub/83

If you are winning every impression, are you overpaying? Your dashboard is green. Your quarter lost money. Both are true. Delivery is full. Budget is spending. Acquisition cost is up maybe fifteen percent over two quarters, and everyone blames the platform, the season, or an aggressive competitor. But nobody blames their own bids. We've watched a few teams unknowingly walk right into this. They win almost every auction they enter, and winning is exactly how they end up paying more for a customer than that customer is worth. Every time your ad could show, Meta or Google runs a quick auction for that one slot. Every advertiser chasing the same person puts in a bid, and a bid is really a guess at what that person is worth to them. On most accounts the platform places that bid for you, working back from a target cost someone set months ago. It weighs the bid against how good it thinks each ad is, but a bigger bid wins more often. The person is worth roughly the same to everyone bidding. Nobody knows the real number, so everyone bids their own guess. The company that wins isn't the one that valued the customer correctly. It's the one that overestimated the most. Economists call it the winner's curse. It came out of oil lease auctions, where the firm that won a block was reliably the one that had guessed highest about what lay underneath. The winning bid was a prediction, and it was wrong in a predictable direction. Picture three companies on one segment worth about forty pounds a customer. They bid > thirty, > forty, and > fifty-five. Fifty-five wins everything, acquires at fifty-five, and reports full delivery and healthy volume. They're fifteen pounds down on every customer and nothing in the account shows it. The fix sounds backwards. Bid what a customer is actually worth to you, and let yourself lose the auctions priced above it. A win rate well under 100% isn't the account failing. It's you refusing to pay fifty-five for something worth forty. Crocs played a different game. They reported roughly $52.4 million through TikTok Shop in a year, and their chief brand officer credited a test, fail, scale mindset instead of any single hero campaign. Run enough shots and the auction stops deciding your quarter, because you're no longer betting the year on one correct bid. The distinction for your next planning cycle: > a channel you bid for is a position, and > a channel nobody can outbid you in is an asset.

people often ask, “who are the best KOLs?” i think that is the wrong question the better question is: which KOL fits this goal, audience and stage of the campaign? if the product is unknown, you need KOLs who can create awareness and hype if people know the product but take no action, you need conversion-focused KOLs if the product is difficult to understand, you need strong educators if you want early adopters, you need alpha callers with a trusted audience these are different jobs. treating every KOL the same usually leads to wasted budget and poor results i have worked with hundreds of KOLs over the past two years at @Growgami. i have managed campaigns for top protocols and tier-one projects i have seen the posts. more importantly, i have seen what happened behind them reach does not always produce users good content does not always create hype strong conversion does not always come from the biggest account the operator’s job is not to gather popular names the job is to know who can produce the result that matters.

"Demis Hassabis says AI could push us into a new golden age of discovery within 20 years, curing diseases we've never been able to touch. Optimism or overpromise? @demishassabis"

The second edition of our Growth: Growgami series: the Outreach System

we generated 161 lines of pure ai slop on purpose, on the same topics as 1,391 real tweets you can't stay different from an average nobody ever counted

We were actually quite early in the AEO/GEO space Saw the opportunity before it was even given that official name We called it ASR, AI Search Results

SEO competes for position AEO and GEO compete for mentions But AEO and GEO are built from SEO

OpenAI’s first-ever influencer brand trip didn’t go over well with the general public (via @opinion) bloomberg.com/opinion/newsle…

🎉 Congrats to @MiniMax_AI on releasing the open weights for MiniMax H3! Day-0 support in vLLM-Omni! One model reads text, images, video, and audio as a single context and returns video with native stereo audio. Text-to-video, first/last-frame, and multi-reference generation, 4 to 15 seconds at up to 2K and 24 FPS. The MP4 comes back with H.264 video and a synchronized stereo track already muxed in. It serves over the OpenAI-compatible /v1/videos endpoint, synchronous or async with job polling. 🔊 The video ⬇️ was made with H3, served on vLLM-Omni.

1,522 AI stories moved between July 27 and August 3. We kept seven. Four of them are about open weights.