Creating a Financial Foundation for Shared Infrastructure

Over a decade ago, I was one of the founding members of the Dallas Makerspace. My major contribution was designing the financial models that allowed the group to have a solid financial footing for renting it’s first dedicated space.

an antique drawing of three candelabras
Giovanni Battista Montano. Three Candelabra, 1534–1621. The Art Institute of Chicago.

The other founders were more involved in all the growing pains of starting an organization like that, and I moved to another city and didn’t lift those boulders. But (as far as I know) the original membership models kept the group bootstrapped long enough to attract more members and grow into the organization they are today.

A member of the ThePrepared Slack recently asked how I did this, and in retelling the tale, I realized that I’d never written down the methods I used. I think sharing them here might be helpful to other people looking to start either their own hackerspace, makerspace, or other opt-in, volunteer-driven group that seeks to have a single costly piece of shared infrastructure.

The Problem, Or What Not To Do

First let me lay out the problem. A volunteer organization starts with zero money. It can ask for donations and have some non-zero value of money, and then they can spend that money on projects. This model works fine if the projects are less frequent than how often you can ask people for money. If the organization wants to rent a space, they will now have a monthly operating cost that extends into infinity. There is no time when you’ll have raised enough money to pay for all the rent forever. You can only raise enough money for some number of months. You can think of each months rent as a “monthly project” you need to raise money for. If you organization has a regular meeting once a week, that means you will be either about to ask for money, asking for money, or telling people how much money you raised three out of the four weeks of the month. A primary task of the volunteers who have donated their time to keep the organization running will be to figure out how to collect enough money each month.

Suffice to say, unless your organization is a group of people who love to ask other folks for money, this will not be an activity that is long term sustainable by volunteers. They did not join the ranks of your group to run around asking folks for money.

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Comparing Engineering and Design

In an earlier post I wrote about the similarities between engineering and design. After discussing the concepts with a few engineers and designers, I thought it would be helpful to explore the differences between the two disciplines.

a crushed empty soda bottle on the ground
Photo by Roberto Sorin on Unsplash

Known solution versus unknown solution

In the introductory chapter of Designing Your Life, the authors point out the most salient different between engineering and design problems.

… [E]ngineering is a good approach to solving a problem when you can get a great deal of data and you’re sure there is one best solution.

Designing Your Life (Evans and Burnett, 2016)

They position design problems as not having a known single best solution.

[Creating the first laptop with a built-in mouse] was a design problem. There was no precedent to design toward, there was no fixed or predetermined outcome; there were plenty of ideas … but nothing was working.

Designing Your Life (Evans and Burnett, 2016)

In other words, engineering explores a problem space with a clear well-defined solution, while design explores a problem space without a well-defined solution.

Solvability

A professor introduced me to the idea of asking whether a problem is “solvable by design” or not. This is a question a designer should ask when identifying a problem to solve. I found it incredibly helpful to break out of an engineering mindset. I was in the early stages of a project, exploring a problem space and being a bit overwhelmed at all the different facets of a large and complicated situation. My process was to try and create a framework for understanding the entire problem space, and then using that framework to come up with “the solution”. The framework was helpful – it provided a way to organize my group’s thoughts and gave us a common language to talk about the different facets of the problem space. But it did not point to a “solution” – instead it made clear that the tree of problems we were looking at had a root problem that was simply not solvable by design. The best we could do is mitigate some of the effects of the problem and provide a tool designed to help the people affected cope.

I’m not sure that engineering has such concept as “not solvable by engineering”. Certainly there are problems that aren’t, but I don’t recall that being part of any engineering course or discussion I ever participated in. It is perhaps a blind spot in the way engineering is practiced. Or perhaps such problems are dismissed as “not solvable by engineering yet“.

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Building a small team

When starting a new venture, your team is often small due to timing, budget, or uncertainty. Growing a team from a small starting point takes careful thought about both the current needs and the future. When only a handful of people are on the team, each hire has a dramatic increase in the communication costs and cognitive load of relationships. There is a combinatorial jump as N goes from 2 through 6 that is unavoidable.

Photo by Wolfgang Hasselmann on Unsplash

On a small team, each member has to cover a wider spectrum of topics, even if the depth of understanding or time commitment of each topic is small. Someone needs to do all the little administrative tasks but they do not all sum to an amount of work that represents a full position. And that is often the case for many other topics. You do not need specialists yet.

But the software and technology industry is geared towards specialists. The cynic would say it is because it is easier to put people into a box with a label and disregard the other skills someone has. I think it is simply the nature of a tech industry culture dominated by huge players that are assembling large teams that are looking for very specific specialized roles. Those companies’ influence sets the tone of the discussion. When someone might get a job at a 10,000 person company or a 100 person company, which framing are they going to gravitate towards for themselves? It seems the gravitational pull of the big players wins out.

So building a small team is difficult. It is intrinsically difficult to do, and the hiring marketplace is slanted against giving you the information you need.

My advice, and the techniques I use follow.

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The Overlap of Engineering and UX Design

While simultaneously working in software engineering and completing my masters degree in HCDE, I started to notice a few overlaps in both the practice and conceptualization of engineering and design.

Both involve solving the problem of what to build. Both rely on a set of heuristics built by experience in the individual practitioners. Both are concerned with trade-offs.

two giraffes facing away from each other
Photo by Vincent van Zalinge on Unsplash

What to build

Solving the problem of what to build in either discipline is about understanding the gap the solution needs to fill.

In engineering, this is usually framed as requirements gathering. They are typically structural requirements of the embodiment (how many cycles in how much time, how much work done with how much resources), restrictions of performance envelope (an upper limit of acceleration, a lower limit in total capacity), or functional conditions (some response must occur whenever an event occurs).

In design, deciding what to build is based on satisfying the judgement of a person. This could be the design themselves (intuitive design), an end user (user-centered design), or a stakeholder (a mixture).

Heuristics

These appear to be poised opposite each other on a spectrum of hard and soft requirements. But that assumes solving the problem of what to build is simply mechanical. Problem solving is creative and involves synthesizing existing solutions in appropriate combinations as well as introducing novel solutions to the context. Both a designer and an engineer rely on a set of heuristics to build a solution, including the introduction of any sort of formal design process.

Trade offs

It is this aspect that ties engineering and design together. Both require space for ideas to be pieced together and evaluated. In any non-trivial situation, the addition or subtraction of an element affects the performance of the solution in a complex way.

A user experience design is not simply a set of steps to walk through. It must consider the holistic experience of many different types of people. It needs to take into account what is practical.

Similarly, an engineering solution is not simply the set of components involved. It isn’t even the much larger set of combinatorial ways that the components could be arranged. It must consider flexibility to meet future conditions and extensibility. A solution must address maintenance and the skills and abilities of the team who will maintain it.

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Timing concerns of delay line style memory

Circuit diagram of a delay line style memory system.
Delay line memory simulation. 32 bits are stored in four 1-byte addresses.

I was getting bent out of shape that I needed to somehow reconstruct the system clock out of the data stored inside a delay line. But fooling around with an old discrete delay line simulation in a circuit simulator by replacing the giant stack of flip flops with a proper length delay line shows that I don’t need to be too concerned

As long as

  1. The delay line stays a constant delay length in terms of time (dubious)
  2. The system clock stays a constant speed (actually very easy because amazingly stable crystal oscillators are trivial nowadays)

Delay lines varying in time is

  1. Highly probable with any sort of rotating media (magnetic drums, etc)
  2. Less likely for “solid state” delay lines such as acoustic torsion delay wire.
  3. Unknown for any other technology (tape loops?)

For rotating media or tape loops, it would probably be good to assume they require a second timing track. It’s somewhat of a “waste” of media density, but you should only need one per media – so one track on a drum or one track on the tape. You can have as many other tracks as you can cram on there.

For the more stable media, where the main drift is due to temperature, there could be some type of calibration mode where a signal is put into the delay line and then compared to the current clock speed. The clock speed could then be adjusted to match. This could even be automatic – perhaps something you would perform once on startup, and then once again when the machine is up to operating temperature. Of course any thing that is temperature dependent is probably best handled by installing a heater and keeping it at a steady 100degF (or whatever) no matter what.

Audio Digital Delay with DRAM and Arduino

Aka “ADDDA” or “AuDiDeDrAr” or “aww dee dee drawer” or “A3DA”

I’ve had this idea bouncing around in my head that you could use 1-bit wide DRAM as a delay line if you simply counted up through it’s addresses, reading and writing as you go. 1-bit wide DRAM like the M3764 have separate pins for Data In and Data Out which makes the read-and-write method easier.

The light bulb moment was coming across an old post on diystompboxes.com where one commenter provides a short snippet of code to do a Delta-Sigma analog to digital converter using the Arduino’s analog comparator pins. I had planned to do this purely in software by using the normal ADC pins and then calculating the Delta myself. But the built-in comparator makes this dead simple!

You can just see the OKI DRAM chip under all those wires.
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National Semiconductor 4510 Mathematician

I have a small collection of vintage calculators that I stumbled into collecting. I found one at a garage sale, and then one was given to me, then I found a neat one on eBay for a good price… Before I knew it, I was a calculator collector.

I actually use most of them despite having a great calculator app on my phone because I prefer their physical interfaces. I have one on each desk and one in my bag so I don’t have to go searching. I don’t have that many bags and desks though so there is also a small stash in a drawer.

The brown and tan color scheme is very 70s. I think they’d have used wood grain print adhesive vinyl if they could have.

My latest addition is a National Semiconductor 4510 Mathematician from the mid 70s. It has an 8 digit red LED display and runs on a 9 volt battery. There is a jack on the top edge for connecting a wall supply if you’ve got a lot of math to do.

It is in great condition and the seller even included a brand new battery. It is one of the lesser RPN calculators of the 70s and not expensive. Like most of my collection, is not valuable but it is uncommon.

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From the notebook: Tape Transports

Todays notebook sketch is some ideas for building a tape “transport” – the mechanical bits that move the tape around in the right way and at the right tension.

Three transport configurations and my current thinking on a capstan.

I have a weird fascination with magnetic storage media and tape in particular. It was a key technology in computing for decades and it has more or less completely disappeared.

All that time in home, commercial, and industrial use has left lots of bits and bobs to experiment with, although it is very very quickly disappearing.

Other than the playback and record heads and the media itself, the devices can be recreated from scratch. (And let me get back to you on making heads and media…)

Prototype Game of Life Synth Module

Conway’s Game of Life (CGoL)has always fascinated me. It is probably the most well known of all cellular automata and also probably the most intuitive. Yet even simple patterns can turn into complex sequences of shapes, patterns, and noise.

Years ago, when learning about the HTML5 WebAudio API, I came across a fun little demo called Blips of Life by Mike M. Fleming. Use your mouse to draw some dots and then click the triangle Play icon in the bottom left. Great, right? I’ll let you play around with that for a while. Leave it running while you read, perhaps?

This is in 1U Eurorack format.

When it came time to start prototyping new modules for my modular synth, I was inspired to recreate Mike’s work in hardware. I didn’t have exactly the parts to fully recreate his Blips of Life, but using the parts I had in hand I made a prototype.

My version has only an 8×8 grid and only has a major pentatonic scale. The small grid means that there are fewer possible patterns, although not so few it is monotonous. The major pentatonic scale is fine. The largest problem with the prototype is that I used CircuitPython to write it, which has no interrupt support. I love Adafruit – they’re a great company and they design terrific boards. But removing interrupts from their fork of MicroPython has cut several projects short.

The prototype works pretty well and exposed a new design challenge: how do you deal with “games” that end in loops? They’re a subset of steady state patterns in CGoL – a pattern can go “extinct”, “steady”, or loop in a finite sequence. The first case is easy to detect and deal with. If all the cells of the grid are off, repopulate the board. You can detect a steady state by comparing the next board with the previous. If they’re identical, repopulate.

But loops can be any arbitrary length, and can step through rather complex patterns. The only way I know to detect them is to have a list of boards known to be part of or lead to a loop. I’ve got some ideas how to do that either via live loop detection or with a precomputed list of boards. As yet, the performance limitations of CircuitPython really prevent tackling it. I’ll need to reimplement the code in C++ using Arduino. Hats off to Adafruit for supporting both Python and Arduino on their boards.

Book recommendation: Turing’s Cathedral by George Dyson

If you’re interested in the early history of computing, check out Turing’s Cathedral by George Dyson. It covers an interesting middle phase between the original electronic digital computers and the wide commercialization of computers in the late 50s.

The cover of the book recalls a punch card.

Specifically it examines the people and development around “the IAS machine” at the Institute for Advanced Study at Princeton. Big and not as big names make an appearance, and it is a detailed account of the forces at play: academia, industrial, military, and political.

The design of the “IAS machine” was the pattern for dozens of machines around the world. More than one country’s “first computer” was one built using the design developed by the people at IAS. I think of it as the first practical computer – the construction needed to solve a lot of problems that the original electronic computers didn’t need to address because they were just struggling to exist.

I’m not going to lie: there are a lot of “white men in ties” involved.

It’s been a while since I finished the book, but I do refer to it when I need details of how some design constraint was surmounted. It also includes enough biographical information that I use it to jog my memory of exactly who was who. The world of computing was still small enough that people who contributed to the IAR project show up in other places pretty often.

It’s widely available. It looks like Thriftbooks has it for under $5, so you could get it for free if you’ve got some reward points there.