Most people who follow AI tools from the outside make the same mistake first: they use public excitement as a shortcut for long-term value. You see a massive GitHub number, assume the project is obviously worth following, and keep scrolling. That shortcut feels efficient, but it can waste time, budget, and attention on surface heat.
The msitarzewski snapshot is useful because it breaks that shortcut fast. On June 30, 2026, agency-agents showed 119k stars and 19.5k forks on GitHub [S003]. His GitHub profile also showed 4.6k followers [S002]. But sponsors / msitarzewski showed 5 current sponsors [S001]. That is the whole point in one line: 119k stars still didn't become 5 sponsors.
Stars are spectators. Sponsors are the real conversion. A star usually means this looks interesting. A sponsor means this helps me enough that I want it to keep existing. Those are not the same signal, and beginners get misled because the louder number is the easier number to compare.
That matters even if you are not a developer. If you are deciding which AI tools to learn, recommend, or build around, hype alone is a weak filter. Don't judge an update by how many features it lists. Judge it by whether it changes your next move. The project page tells you what people noticed. The sponsors page tells you who felt enough ongoing value to pay.
There is one more clue in the support language around brew-browser. The pitch is not please watch this. It is closer to: if this saved you time, sponsor it [S004]. That is a harder test than popularity. Attention can spike fast. Financial support is more likely to appear when people feel repeated, practical value.
Boundary line: this is one creator case, not a rule for every open source project. But it is still a sharp filter for ordinary people trying not to fall behind. Before you treat a huge GitHub repo as proof that something has staying power, ask one extra question: does the attention turn into support? If you know someone who keeps mistaking visible hype for durability, share this with them.