It’s not BDUF if you spend detailed time learning who needs this thing and why they need it.
It’s not BDUF if you help every team member know what success looks like.
A common misunderstanding about Agile and “Big Design Up Front”:
There’s nothing in the Agile Manifesto or Principles that states you should never have any idea what you’re trying to build.
You’re allowed to think about a desired outcome from the beginning.
It’s not BDUF if you spend detailed time learning who needs this thing and why they need it.
It’s not BDUF if you help every team member know what success looks like.
It’s not Agile if you increase risk by starting your sprints with complete ignorance.
It’s not Agile if you don’t research.
Don’t make the mistake of shutting down critical understanding by labeling it Bg Design Up Front.
Product management and developers also need to be out with the team, conducting the research.
Shared Understanding is the key objective here.
https://t.co/I8q6rRqxym
I\u2019d recommend that the devs participate directly in the research.
— Jared Spool (@jmspool) November 18, 2018
If the devs go into the first sprint with a thorough understanding of the user\u2019s problems, they are far more likely to solve it well.
Defining all the functionality before coding is BDUF.
Drawing every screen and every pixel is BDUF.
Promising functionality (or delivery dates) to customers before development starts is BDUF.
These things shouldn’t happen in Agile.
It’s important we not lump all possible pre-Sprint 1 activity under the Big Design Up Front label.
We shouldn’t head into Sprint 1 believing we know the solution. Yet, we need to be clear on the problem.
https://t.co/8fJA3QpA0X
For your consideration: https://t.co/CNf3fjZNw4
— Austin Govella (@austingovella) November 19, 2018
More from Tech
The first area to focus on is diversity. This has become a dogma in the tech world, and despite the fact that tech is one of the most meritocratic industries in the world, there are constant efforts to promote diversity at the expense of fairness, merit and competency. Examples:
USC's Interactive Media & Games Division cancels all-star panel that included top-tier game developers who were invited to share their experiences with students. Why? Because there were no women on the
ElectronConf is a conf which chooses presenters based on blind auditions; the identity, gender, and race of the speaker is not known to the selection team. The results of that merit-based approach was an all-male panel. So they cancelled the conference.
Apple's head of diversity (a black woman) got in trouble for promoting a vision of diversity that is at odds with contemporary progressive dogma. (She left the company shortly after this
Also in the name of diversity, there is unabashed discrimination against men (especially white men) in tech, in both hiring policies and in other arenas. One such example is this, a developer workshop that specifically excluded men: https://t.co/N0SkH4hR35
USC's Interactive Media & Games Division cancels all-star panel that included top-tier game developers who were invited to share their experiences with students. Why? Because there were no women on the
ElectronConf is a conf which chooses presenters based on blind auditions; the identity, gender, and race of the speaker is not known to the selection team. The results of that merit-based approach was an all-male panel. So they cancelled the conference.
Apple's head of diversity (a black woman) got in trouble for promoting a vision of diversity that is at odds with contemporary progressive dogma. (She left the company shortly after this
Also in the name of diversity, there is unabashed discrimination against men (especially white men) in tech, in both hiring policies and in other arenas. One such example is this, a developer workshop that specifically excluded men: https://t.co/N0SkH4hR35
Ok, I’ve told this story a few times, but maybe never here. Here we go. 🧵👇
I was about 6. I was in the car with my mother. We were driving a few hours from home to go to Orlando. My parents were letting me audition for a tv show. It would end up being my first job. I was very excited. But, in the meantime we drove and listened to Rush’s show.
There was some sort of trivia question they posed to the audience. I don’t remember what the riddle was, but I remember I knew the answer right away. It was phrased in this way that was somehow just simpler to see from a kid’s perspective. The answer was CAROUSEL. I was elated.
My mother was THRILLED. She insisted that we call Into the show using her “for emergencies only” giant cell phone. It was this phone:
I called in. The phone rang for a while, but someone answered. It was an impatient-sounding dude. The screener. I said I had the trivia answer. He wasn’t charmed, I could hear him rolling his eyes. He asked me what it was. I told him. “Please hold.”
Wish I had the audio of Rush Limbaugh telling me off on the phone on his show when I was six. In the meantime, RIP.
— Shannon Woodward (@shannonwoodward) February 17, 2021
I was about 6. I was in the car with my mother. We were driving a few hours from home to go to Orlando. My parents were letting me audition for a tv show. It would end up being my first job. I was very excited. But, in the meantime we drove and listened to Rush’s show.
There was some sort of trivia question they posed to the audience. I don’t remember what the riddle was, but I remember I knew the answer right away. It was phrased in this way that was somehow just simpler to see from a kid’s perspective. The answer was CAROUSEL. I was elated.
My mother was THRILLED. She insisted that we call Into the show using her “for emergencies only” giant cell phone. It was this phone:
I called in. The phone rang for a while, but someone answered. It was an impatient-sounding dude. The screener. I said I had the trivia answer. He wasn’t charmed, I could hear him rolling his eyes. He asked me what it was. I told him. “Please hold.”
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The YouTube algorithm that I helped build in 2011 still recommends the flat earth theory by the *hundreds of millions*. This investigation by @RawStory shows some of the real-life consequences of this badly designed AI.
This spring at SxSW, @SusanWojcicki promised "Wikipedia snippets" on debated videos. But they didn't put them on flat earth videos, and instead @YouTube is promoting merchandising such as "NASA lies - Never Trust a Snake". 2/
A few example of flat earth videos that were promoted by YouTube #today:
https://t.co/TumQiX2tlj 3/
https://t.co/uAORIJ5BYX 4/
https://t.co/yOGZ0pLfHG 5/
Flat Earth conference attendees explain how they have been brainwashed by YouTube and Infowarshttps://t.co/gqZwGXPOoc
— Raw Story (@RawStory) November 18, 2018
This spring at SxSW, @SusanWojcicki promised "Wikipedia snippets" on debated videos. But they didn't put them on flat earth videos, and instead @YouTube is promoting merchandising such as "NASA lies - Never Trust a Snake". 2/
A few example of flat earth videos that were promoted by YouTube #today:
https://t.co/TumQiX2tlj 3/
https://t.co/uAORIJ5BYX 4/
https://t.co/yOGZ0pLfHG 5/
Nano Course On Python For Trading
==========================
Module 1
Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...
... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit https://t.co/EZt0agsdlV
This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!
In Module 1 of this Nano course, we will learn about :
# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)
# Using Google Colab
Intro link is here on YT: https://t.co/MqMSDBaQri
Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb
You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want
# Importing Libraries
Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.
==========================
Module 1
Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...
... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit https://t.co/EZt0agsdlV
This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!
In Module 1 of this Nano course, we will learn about :
# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)
# Using Google Colab
Intro link is here on YT: https://t.co/MqMSDBaQri
Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb
You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want
# Importing Libraries
Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.
