
This week Cag Man(@CagManThing) joins Tiny(@Tiny415), Mike(@AssaultSuit) and Aaron(@Ind1fference) to talk about: Mario Kart 8, Disney Infinity 2.0, Nintendo @ E3, Quiznos, PS4 1.7 firmware, Skylanders, American Girl Store/Bistro, indentity theft, Udraw, Hook, Mercenary Kings, TitanFall, Vagrant Story, Yaiba Ninja Gaiden, OctoDad, 2DS, Assault Android Cactus, Bob Hoskins(RIP), Thomas Was Alone, Bit Boy Arcade, Ouya playcast, We Are Doomed, Child of Light, Cel Damage HD, MOGA controllers, Tom Sparks and the Quakes of Ruin and more.
If you like the show please leave us an itunes/Zune review, a tweet, an email or a voicemail (202-573-7686). Download the GE iOS / WP apps and check out GameEnthus.
Show Length: 145 minutes Direct Download
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Show Links
*Don’t forget to follow Cag Man on PSN and XBL @ Zaran123*
New videos at GameEnthus.com
Community Info
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Show Music
Intro – Lord Finesse – Hip 2 da game instrumental
Break 1 – Smif n Wessun – Bucktown instrumental
Break 2 – Baltimora – Tarzan Boy
Break 3 – Naoki Kodaka/Nobuyuki Hara – Batman NES ThemeÂ
Break 4 – Rygar Theme
Break 5 – De La Soul – Keepin’ the Faith instrumental
Break 6 – Angie Stone – Wish I Didn’t Miss You
Outro – Stevie Wonder – I Believe(When I fall in love)
Showcap – De La Soul – Sunshine instrumental


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I appreciate how you include both theoretical knowledge and practical applications.
Your content is always so valuable.
Interesting perspective, definitely worth considering.
Quality content as always. Looking forward to more posts.
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The shift towards “entity-based” indexing is real. Your strategy seems to leverage that by building entity associations rather than just keyword matches. Smart.
Finally, someone said it. The old school “blast and pray” method is dead. Precision and camouflage are the new standard.
This is a solid breakdown. One thing I’d add is that the impact of these updates often lags by 2-3 weeks. We tracked this across multiple projects and found the recovery phase is where most people give up too early.
Just wanted to say thanks for the detailed case study. It’s rare to see actual data backing up these claims. We’ll be adjusting our Q4 roadmap based on some of these insights.
I’d love to see a follow-up post on how this integrates with social signals. We feel there’s a multiplier effect there that isn’t being fully utilized.
This complements the “Entropy” theory perfectly. If you don’t introduce randomness, you’re just painting a target on your back. Glad to see others advocating for smarter engineering.
The analogy of the “immune system” is perfect. You need to build resistance before the virus (update) hits. Too many people react instead of prepare.
One minor correction: the update rollout was actually 14 days, not 10. But that doesn’t change your main point—the volatility window is getting wider.
Just wanted to say thanks for the detailed case study. It’s rare to see actual data backing up these claims. We’ll be adjusting our Q4 roadmap based on some of these insights.
Does this apply to non-English markets as well? We’re seeing conflicting signals in our EU campaigns compared to what you’ve described here. Would love to hear your thoughts on regional variance.
The shift towards “entity-based” indexing is real. Your strategy seems to leverage that by building entity associations rather than just keyword matches. Smart.
Is there a specific tool you recommend for tracking the velocity? We’ve been doing it manually but it’s becoming unscalable.
Is there a specific tool you recommend for tracking the velocity? We’ve been doing it manually but it’s becoming unscalable.
The depth here is impressive. Most guides just skim the surface of link velocity, but your point about “natural variance” hits the nail on the head. It’s exactly what we preach to our clients.
Thanks for the transparency. It’s refreshing to see a strategy that doesn’t rely on black-hat churn and burn. Sustainable growth is the only way forward.
Brilliant articulation of the problem. The industry has been too focused on metrics like DA/DR instead of actual traffic flow and user behavior.
I’m sharing this with our content team. We’ve been struggling to explain why “quality over quantity” isn’t just a cliché, and this illustrates it perfectly.
I bookmarked this for my team. The section on avoiding footprints is crucial. We recently audited a site that got hit exactly because they ignored that principle. Good catch.
I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
This aligns with the “Signal Noise” theory we’ve been developing. You need enough noise to mask the signal, but not so much that you lose authority. delicate balance.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.
I bookmarked this for my team. The section on avoiding footprints is crucial. We recently audited a site that got hit exactly because they ignored that principle. Good catch.
I’ve been following this topic for a while, and your analysis on the structural shifts really adds a new perspective. We’ve noticed similar patterns in our internal data at SignalLayer, specifically regarding the volatility timeline.
I’d love to see a follow-up post on how this integrates with social signals. We feel there’s a multiplier effect there that isn’t being fully utilized.
I’ve been following this topic for a while, and your analysis on the structural shifts really adds a new perspective. We’ve noticed similar patterns in our internal data at SignalLayer, specifically regarding the volatility timeline.
The shift towards “entity-based” indexing is real. Your strategy seems to leverage that by building entity associations rather than just keyword matches. Smart.
Does this apply to non-English markets as well? We’re seeing conflicting signals in our EU campaigns compared to what you’ve described here. Would love to hear your thoughts on regional variance.
For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.
I’d love to see a follow-up post on how this integrates with social signals. We feel there’s a multiplier effect there that isn’t being fully utilized.
We’ve been A/B testing this exact hypothesis. Group A (your method) is outperforming Group B by 40% in terms of ranking stability. The data speaks for itself.
Brilliant articulation of the problem. The industry has been too focused on metrics like DA/DR instead of actual traffic flow and user behavior.
I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
I’m sharing this with our content team. We’ve been struggling to explain why “quality over quantity” isn’t just a cliché, and this illustrates it perfectly.
This complements the “Entropy” theory perfectly. If you don’t introduce randomness, you’re just painting a target on your back. Glad to see others advocating for smarter engineering.
For anyone reading this, pay attention to paragraph 4. That subtle distinction between “diversity” and “randomness” is what saves you during a Core Update.
Thanks for the transparency. It’s refreshing to see a strategy that doesn’t rely on black-hat churn and burn. Sustainable growth is the only way forward.
The analogy of the “immune system” is perfect. You need to build resistance before the virus (update) hits. Too many people react instead of prepare.
Great read. It reminds me of the strategy we deployed last quarter. The focus on foundational stability really pays off when the algorithm shifts. Thanks for compiling this.
I’d argue that the content relevance is even more critical now. We’ve seen perfectly good links get devalued just because the semantic match wasn’t tight enough.
Finally, someone said it. The old school “blast and pray” method is dead. Precision and camouflage are the new standard.
I’m curious about the sample size for these conclusions. We saw a 15% deviation in our own datasets, but the overall trend aligns with your findings. Good work.
The analogy of the “immune system” is perfect. You need to build resistance before the virus (update) hits. Too many people react instead of prepare.
I’m skeptical about the timeline you proposed, but I’m willing to test it. If this holds up, it changes how we structure our entire outreach program.