226 Photos and videos
This post is a goldmine for founders who try to build a company with high trust: buffer.com/resources/salary-….
Salary should not be linked to bargaining power, as this is unfair to those who may struggle with negotiation yet are performing excellent work.
Make your salaries transparent.
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Profit sharing is an effective strategy for retaining talent in a bootstrapped company without plans for a significant exit. This approach allows everyone to benefit from the company's revenue growth, rather than just the investors, as seen in hypergrowth startups.
For reference, Buffer team distributed 15% of their net profit as profit share bonuses in 2024, 40% of the pool equally across the team, 40% of the pool weighted by salary, and 20% of the pool weighted by tenure.
A great incentive mechanism to encourage team effort, level of impact and long-term commitment.
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Reading Buffer CEO @joelgascoigne's posts is truly inspiring. joel.is/posts/ You can begin with a side project and grow it into a company filled with talented people, all while maintaining the principles you established from the start.
Bootstrapping founders often fear hiring and managing people. But for a business to truly take off and grow, bringing in talent is always part of the job.
Choosing not to hire for the sake of staying small is self-limiting. When the timing and cadence is right, hiring only strengthens the team and allows you to focus on what truly matters.
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For bootstrapping founders who're hesitant on whether to take VC money, wonder if this is a one-way door decision, and fear you may never go back, the @buffer team showed you a way out. This is a playbook in detail on how to handle difficult situations where your company's mission shifts from market dominance (growth) to sustainable operation (profitability). buffer.com/resources/buying-…
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Company culture I really like and hopefully to build a team like these myself: @linear, @buffer, @obsdmd, @37signals, @posthog, @todoist, @craftdocs
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compared to steep growth curves like this, I like more of those products that have steady growth over 2-3 years but at a much lower growth rate.
the former is usually built on hype and fomo, but the latter is built on sustained demand.
Jun 10
If you want to know how to build and scale apps, Cedric is the guy to follow.
loved having him on the channel right as he was blowing up!
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bring your own token is definitely the future
Jun 8
Today we’re introducing Builder, a new MagicPath plan for people working with Codex, Cursor, Claude Code.
For $10/month, get unlimited external-agent calls and a multiplayer canvas with visual editing, design systems, live links, Figma export, and more.
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if you don’t use your own product, it’s highly likely that no one else will.
Jun 5
Validate your idea locally.
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Earned content like YouTube and 3rd party review articles will be even more important.
Jun 2
In the last 6 months at @Ahrefs, we analyzed over 1 billion data points across 14 studies. Here's what we learned about AI search optimization:
1) "Best X" blog listicles are the single most prominent content format cited by AI chatbots. They make up 43.8% of all page types cited by ChatGPT specifically.
2) 67% of ChatGPT's top 1,000 citations come from sources marketers can't influence: Wikipedia (29.7%), homepages (23.8%), app stores (6.6%). Only 32.3% are influenceable content like educational pages, reviews, news, and blog posts.
3) 28.3% of ChatGPT's most-cited pages have zero Google organic visibility. These pages get cited repeatedly by ChatGPT despite not ranking in Google at all. A completely separate discovery layer.
4) ChatGPT only cites about 50% of the URLs it retrieves. It fetches dozens of pages per query but uses half as background context without attribution. This means that being retrieved and being cited are very different things.
5) Adding schema markup had zero meaningful impact on AI citations. AI Overviews actually dipped −4.6%, while AI Mode ( 2.4%) and ChatGPT ( 2.2%) showed changes indistinguishable from zero.
6) YouTube mentions have the highest correlation (0.737) with AI brand visibility out of all the factors we studied (including all the conventional SEO metrics like backlinks, page count, DR, etc). This held true for both Google-owned and OpenAI products.
7) AI Overviews reduce clicks to the #1 result by 58%. That’s up from 34.5% just 10 months earlier. The trend is accelerating.
8) 99.9% of AI Overviews appear on informational intent queries. Transactional, navigational, and local searches are almost entirely AIO-free. Shopping triggers AIOs just 3.2% of the time.
9) For a given search query, Google’s AI Mode and AI Overviews reach the same conclusions 86% of the time — but cite almost entirely different sources (only 13.7% citation overlap).
10) AI Overviews change every 2.15 days on average, with 70% of content differing between consecutive observations. But semantic similarity stays at 0.95. The words, sources, and entities constantly shuffle, but the actual meaning barely moves.
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