For the most part songs in playlist are in order we played them in-ish.

That one Song

It's Awesome.

Forgot to make this public 4 months ago. Everything has a purpose. Beautiful performance by Kat.

El Gallo

Space Jam (with Lyrics)

4.30.2017

Take a walk on the wild side (Lou Reed Cover)

Ashes to Ashes (David Bowie Cover)

Channeling

A couple of other tracks from our 4.30.2017 session, all covers.

Creep (Live - Radiohead Cover) 4.30.2017

Corona (Live 4.30.2017)

Close To Me (Live - Instrumental 4.30.2017)

Not Space Jam (Live - Instrumental 4.30.2017)

Something Wickedly Cm

A little band from Chicago. 
Contact: fasterpanda[at]att[dot]net
Spotify: https://open.spotify.com/artist/049DJiERhHd968eY0bOqzW
Facebook: bit.ly/fasterpanda
Catering Info: bit.ly/panda_diet
-----------------------------
| Juan Bonfante (Percussion/Sound Engineer)
| Alex Mizicko (Guitar/Vocals)
| Evan Sierminski (Guitar/Vocals) 
| Tony Mizicko (Bass) 
| Kat Prush (Vocals) 
| Da Panda (Imaginary/Muse/Pet/Producer/Brand) 
-----------------------------
We primarily use magic and the most lo-fi recording process we can imagine and not pay for (so far). But as we continue to have to sell our gear off to feed our pet *Panda's bamboo addiction; soon we may have to just conference call into a WebEx using our phones and have someone monitor it from a few doors down in order to find that right balance of reverb and delay we've now been searching for, as of, whenever I end this paragraph with a period.

*Seriously 50lbs of Bamboo a day! This guy is a big beautiful (and Imaginary) beast! Bamboo is also not cheap, especially the imported stuff our fictitious pet likes to eat.*
 
--- All jokes aside we actually do love Panda's (the wild super fast ones) and completely support the efforts of the World Wildlife Fund (wwf.panda.org), however we are in NO WAY affiliated with them, or sponsored by them in any way!!!
(unless they want to send us free panda related stuff...)

**we also have a MySpace page... from 10 years ago, we can't remember how to log in **

Faster Panda

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