Working Up

by Dwayne Phillips

We all make mistakes. Some are allowable and some not. There is the mistake budget.

We all make mistakes. The sooner we acknowledge and live that the better we will be (IMHO). Some mistakes, like typographical errors in blog posts, are embarrassing but that’s about the cost. Other mistakes, those that cost a million dollars of taxpayers’ money, are a bit more consequential.

I work with government documents much of the day. The folks who created those documents, the government’s employees, make lots of mistakes. Companies must follow the letter of the law or the letter of those documents. When people see the mistakes, they send questions to the government employees who then send answers. This Q&A costs time and salary money. That money doesn’t just add up, it multiplies. Stating “Friday the 13th” when Friday is the 12th, costs the taxpayers a million dollars. I am not exaggerating; it costs that much.

Now we come to the mistake budget. I learned this from the late author and consultant Jerry Weinberg. He had a few employees. Being people, these employees were mistaken now and then. Jerry would record the mistake and the cost it brought in dollars and cents. As long as the sum of the cost was below a set number (a month’s salary or something), things were fine. If, however, the cost became too high (a subjective but agreed upon number), the employee was no longer an employee as they were unaffordable.

This is all to state that while we all make mistakes, some are allowable and some are not. In government employment, there are no mistake budgets. I think that is a mistake, but that is just my opinion. Note, that there is a tool that we can use or not use. Not using the mistake budget is probably a mistake that itself may be allowable or not. To date, those who manage work in government have decided it is an allowable mistake. Perhaps that may change, but probably not.

by Dwayne Phillips

History repeats itself as the computer can be fully occupied by the efforts of just a few programmers.

There was a time in computing history when there were few programmers. The computers weren’t powerful. A couple of programmers could keep a big computer busy all the time. Then the computers became more powerful. More programmers were needed to keep them busy.

Then the computers became much more powerful, much less expensive, and much smaller. Every person could have their own personal computer. We needed hundreds of millions of programmers to keep all these personal computers busy.

Now we are sort of back to the beginning where the number of programmers needed has shrunk to an alarming level. What happened? I think the really smart programmers put the rest of the programmers into the unemployment line.

A few really smart programmers figured out how to tie a bunch of computers together so they looked like one computer. The Beowolf cluster was one instance of this. There are many others. People let someone else use the CPU cycles of their home computer at night, etc. This sort of falls under Distributed Computing.

Then came the datacenter. I don’t know how many individual computers there are in a datacenter. Probably a million or so. Once you reach a number like that, who knows?

Then some really smart programmer figured out how to run one big program on a million processors in a datacenter. One datacenter—one programmer. One solution to solve all the world’s problems. Well, sort of, but that is a detail.

So we are back to a computer needing only a couple of programmers. Except today, that computer is an entire building full of a million computers. Used to be an entire building filled by one computer. One? A million? what’s the difference (a few zeros).

What’s next? Not sure, but it could be fascinating.

by Dwayne Phillips

Working with text and changing file formats just got a lot easier.

This little essay was written to be posted in a WordPress blog. I have been doing this blog writing bit for a few years and have over 1,800 posts. Seems like a lot, but a couple of posts a week for a few years and it adds up.

From time to time, I take these blog posts and turn them into a more traditional book. Here is one example on Amazon. That used to be quite a chore: download an export from WordPress, run some Python code, convert to HTML, convert to MS Word, convert to some Amazon Kindle format, upload, and on and on.

The hard part for me was the Python code to pull the content from the XML into something that HTML could read. (Pardon my falling down into a pit of endless details.)

Well, it all just got a lot easier (Pardon the collapse of grammar.)

Along comes these chattering bots and their continual improvement. Now I ask one of them (the leading ones all have this capability) to do what I want and viola’, out comes a system that does everything for me. Well, I do have to go the WordPress site and export the blog to an XML file. After that, bing, bang, bong, done.

General tip, if it involves text and file formats, ask a chattering bot to do the work. It is quite amazing but, then again, these chattering bots were built to work with text. Don’t ask them to solve basic math and logic problems, but text and file formats are a breeze.

by Dwayne Phillips

Remembering Chuck Norris and his influence on one American family.

Chuck Norris died a few days ago at age 86. To some, Mr. Norris was an American hero of the last half century. To some, Mr. Norris was a caricature of something funny.

Mr. Norris affected my family in ways that bring fond memories. He starred in a couple (more than that) movies in the late 1970s. I was in college. My younger brother was in high school. My younger brother loved martial arts and studied and practiced them achieving a black belt in something or other. That comment shows my little interest in the topic.

My younger brother had to see the Chuck Norris movies. Okay, so we piled into my little car and drove the ten miles to Hammond, Louisiana to see them. I felt they were crummy movies. He felt they were significant milestones in Hollywood. Regardless, attending those movies together meant something to our relationship for the rest of our lives.

Fast forward to the 1990s and Mr. Norris starred in Walker, Texas Ranger. Okay, it ran nine seasons, so it was a success. Critics didn’t like it…so much for critics. I lived in Lagos, Nigeria with my wife and kids. One night a week, my wife and I would watch an episode on Armed Forces Radio and Television Service. It was a small highlight of the week to see Norris deservedly kick the bad guys and nurture a budding romance. My wife and I enjoyed it. We still talk about it now and then. It was part of our relationship during an otherwise odd part of our marriage.

So, we will miss Mr. Norris. In these and other ways, he played a role in my family. That was something.

by Dwayne Phillips

Another rant about writing that makes no sense (to me).

This system uses three times less (memory, weight, time, space, effort, and whatever) than that system.

I understand what it means to use three times more weight (15 pounds instead of 5 pounds), but what does it mean to use three times less weight? I think this means to use a third of the weight (5 pounds instead of 15 pounds).

There is something wrong about increasing a decrease that makes no sense to me. At first I only saw this peculiar increase of a decrease from journalist and other illiterates who also never understand percent change in anything. Now I am reading this from supposedly well-educated scientist and engineers.

Did I fall into a deep sleep and awaken a century later in a place with a new brand of the English language and a redefinition of mathematics? Enough of an old man ranting. Let’s move on.

by Dwayne Phillips

These new tools, ahem all that AI, are boosting productivity in our work. And then we hit the bottleneck and come to an emergency inducing crisis.

Yesterday and today I have been using one of these new tools (some folks them AI, I don’t). I have accomplished in an hour what would have taken a week. I am not exaggerating on that. This new tool enables 20 or 30 times the work product in the same amount of time. This is amazing. As a side note, it is a commentary on the work I am doing. If it is so easy to do faster, what good is it?

Back to the topic at hand. Whoosh! I’m done with this task. Now I pass the results on to the next person. Maybe they have new tools and WHOOSH they do their task 30 times faster. We are rolling.

And then we stop rolling. We come to the bottleneck. Sometimes the bottleneck is one person. Sometimes the bottleneck is one task for which their is no new gee whiz tool. Whatever, the bottleneck is the bottleneck.

Nothing happens at the bottleneck. Tasks from three different projects are waiting at the bottleneck. It will be a month before the output of my task is considered at the bottleneck. The rest of us, those for whom new tools provide all this speed, twiddle our thumbs or something.

The bottleneck stalls progress so long that… wait, oh no! We have a crisis. We have an emergency. We all need to work all-nighters to make the big final deadline.

Huh? What happened to all that productivity?

I think we can do better.

by Dwayne Phillips

Please tell me what we are doing. Please don’t read from a catalog.

Person beaming with confidence: Look. Here is a block diagram of our system. You see we are using Snowflake, Spark, Databricks, Kafka, Tableau, ThoughtSpot, and toss in a little Excel for good measure.

Person baffled but interested: Interesting. I would like to know what we are doing or what functions we are performing. Do you have something showing that?

Person beaming with confidence: silence

I’ve been in this conversation too many times and walked away with too many headaches and too much heartburn. I want to know what we are doing, i.e., the function. I really don’t want to see the names and cute little logos of products.

Consider, as one example, Excel from Microsoft. It is a fine product. It is such a fine product that it can function in many ways. Excel can be a database of people with name, phone number, email address, home address, and so on. Excel can be the repository in a data call where there are 50 questions and places for 50 different organizations to place their 50 answers all in one thing. Excel can be a project organizer where each sheet contains information on each phase of the project and each participant. And, guess what, Excel can function for the finance folks to keep track of money (wow, I think it was created to do that last one).

The same can be said for each of the products that Person beaming with confidence said at the beginning.

Please, tell me what we are doing. Then tell me what product we are using for each function we perform. Please try harder to communicate how we engineered a system to do something useful for people.

We can do better. Let’s do better.

by Dwayne Phillips

Some AI tools increase productivity in some areas. Okay, I’m done with this task. Now what? That choice can be vexing.

I used an AI tool (won’t mention which one). I completed a two-day task in an hour. Now what? Hey boss, tell me what to do now.

One answer: go to step two, step three, etc. and let’s finish the whole thing before lunch today. Then we’ll move on to another thing.

Another answer: Wow. Only an hour. Let’s do this over again with a slight variation. If it only takes an hour, we can run this a dozen times with a dozen slight deviations to fill the two days we allocated to this task.

Both answers, I am sure there are more answers, are pretty good. Which one do we use? More than anything, this resolves with temperament. Huh? What about dollars and cents? Nope. Temperament or personality. Does the manager like to ponder one more possibility? Does the manager like to move on? Are we in analysis paralysis or going full speed regardless of the hole in the ground in front of us?

Alas, new tools bring these questions. This is not a new situation. These answers are not new. It is unfortunate, that these questions are new to the people now using today’s new tools. Proceed with caution and have some sympathy for the other person.

by Dwayne Phillips

Every now and then we need a new scapegoat, i.e., something that receives the blame for all the faults and mistakes of society. We have one.

Ah, the datacenter. It is big, noisy, ugly, and raises my electric and water bills. I hate it. It is the cause of all ills in my life. It is the new scapegoat.

Never mind that I use it every time I write a blog post, do a Google search, save a computer file, shop for stuff, and … wait a minute. I do these things all the time everyday. There must be something wrong as a scapegoat is supposed to be bad, not useful.

And then there are all those jobs for everyone from a cement truck driver to an AI engineer. How can a scapegoat provide jobs for all those people? And those jobs allow people to house, clothe, and feed families. Are scapegoats supposed to do those things?

Let’s ignore all the uses and benefits of the datacenter. It is the scapegoat. Let’s only discuss its faults so we can blame everything on the datacenter. It causes inflation. It causes people to buy stuff we don’t need. It causes… give me a few minutes to make a list. Scapegoats have to earn their title, and I am sure this scapegoat will earn its title.

Well, maybe or maybe not. It relieves stress to point to something that receives blame for all the ills of the world. And those tall, noisy buildings are easy to see and so much easier to be the object of my pointer finger.

by Dwayne Phillips

The middle manager has been replaced by the entry-level employee. What?

Ah, the bane of 20th century civilization—the middleman. The middleman was the person in the middle who did nothing but pass a product along from the producer to the consumer. The middleman did nothing of value, but took a good 10% or more cut and passed that to poor me, i.e., the consumer.

Closer to home and daily life was the middle manager. This person did nothing but pass instructions from the big boss down to me. What? The big boss could have sent a memo directly to me or something. Why was the middle manager there? Even the big boss knew the middle manager was a waste of money and should be eliminated.

Along came computing hardware and software. Aha! That would replace the middle manager. The word processor, email, desktop publishing, network, inter-network of computers—one of these things would replace the middle manager.

Along came AI, which is merely yet another thing in the above list of things that were supposed to replace the middle manager. Today’s incarnation of AI, there have been many incarnations since the 1950s, is here and doing fundamental tasks in business and commerce.

But wait. Today’s AI is replacing the entry-level employee. That is who would do the fundamental tasks in business and commerce.

But wait. The middle manager is still here. AI saved the middle manager. Instead, AI clobbered the entry-level employee.

Someone made a mistake.