Top Tweets for #MoldableDevelopment
https://t.co/wgxb7yBogN #ElixirLang #MyElixirStatus #SmallTalk #GToolkit #MoldableDevelopment @feenkcom
Original post: https://t.co/D62jcYmkmJ
Blast from the past:Microtools with LLMs #Blog #Video #AI #MoldableDevelopment #Programming #Video #Video https://t.co/4TCZfjMuRF
https://t.co/4TCZfjMuRF
Blast from the past:Microtools with LLMs #Blog #Video #AI #MoldableDevelopment #Programming #Video #Video https://t.co/Ht5G54MKDo
https://t.co/Ht5G54MKDo
Blast from the past:Microtools with LLMs #Blog #Video #AI #MoldableDevelopment #Programming #Video #Video https://t.co/SkH9GwSeH2
https://t.co/SkH9GwSeH2
Blast from the past:Microtools with LLMs #Blog #Video #AI #MoldableDevelopment #Programming #Video #Video https://t.co/rseUdI2ddr
https://t.co/rseUdI2ddr
Blast from the past:Microtools with LLMs #Blog #Video #AI #MoldableDevelopment #Programming #Video #Video https://t.co/q4vUcmDyKP
https://t.co/q4vUcmDyKP
Blast from the past:Microtools with LLMs #Blog #Video #AI #MoldableDevelopment #Programming #Video #Video https://t.co/x2kEJ5yqfl
https://t.co/x2kEJ5yqfl
Is anyone working on "lovable for private repo/product" style of tool?
I either build myself one or use something out there that can help non-tech stakeholders to do #moldabledevelopment on an app.
DM me if you want to join the waitlist
Blast from the past:Microtools with LLMs #Blog #Video #AI #MoldableDevelopment #Programming #Video #Video https://t.co/GqoVRLJjNZ
https://t.co/GqoVRLJjNZ
Blast from the past:Microtools with LLMs #Blog #Video #AI #MoldableDevelopment #Programming #Video #Video https://t.co/qRTGhHrlT8
https://t.co/qRTGhHrlT8
Oscar Nierstrasz shared a series of case studies and illustrate a number of key patterns behind #MoldableDevelopment on the #YOW24 stage.
👀 Watch it here: https://t.co/EfB2AfkNRC
Do not rewrite legacy code
I cannot stress to you how much you do not want to rewrite legacy code
Only a 25 year old would think this was a good idea
GToolkit es nuestro ambiente de desarrollo preferido. Nos permite practicar #MoldableDevelopment para crear con relativamente poco esfuerzo herramientas específicas del dominio o, como en este caso, entornos dedicados completamente nuevos.
DynaClassroom was built on #GToolkit, the moldable development environment based on #PharoSmalltalk.
🚀 Its flexibility allows the creation of tailored environments like DynaClassroom, a collaborative educational space powered by tangible interfaces and augmented reality.
I often tend to talk about #MoldableDevelopment in too abstract terms. I did it in a call just now. It's not the most useful inclination. That's when I wish I had @swardley next to me to bring me down to earth and show concrete examples. Like he did in this chat when he had me show him how I construct a custom tool for exploring an API on the spot.
What do you think about this example?
I am talking quite a bit about making systems explainable through #MoldableDevelopment. This is a new way of programming and I am still searching for the effective compact narratives.
If you are interested to learn how it can apply your specific context (technology, domain, process), please ask questions either publicly or in a DM. I will answer them. I believe it will make the exercise more interesting for you and it will certainly be helpful for me as well. Win-win 😃.
So, what do you say? Care to comment?
#MoldableDevelopment is about programming through custom tools. Little tools, often in the shape of object views.
The key to making this practical is to decrease the cost of creating those custom views. While we already could create them in minutes, we've always been interested to get to costs measured in seconds.
Yes, yes, I know that #GenAI can be interesting in this context. But before we explore that path we should first try to exhaust possibilities that are much more approachable, explainable and ... less magic.
Like the approach described below. Once we accept that tools can be combined in a myriad of ways, we can get to all sorts of unexpected properties.
Let's look closer at the scenario from the video. We start with a file reference that points to an MP4 file. We see a view with the file path, but we'd rather also see a movie player. So, we write a script that produces an element that can play that movie in a web browser. Then we ask the object to give us a default view and Voilà!
This scenario is possible because we could combine the result of dynamic execution with the static extraction of a view and bring that magic in an interactive editor.
There is a tremendous potential for augmenting our human ability to relate to systems. And the key lies in the environment.
In our quest to make creating views more and more inexpensive, we now got to the point in which we can create custom views based on the object obtained from executing a snippet in the contextual playground from an inspector.
Sounds complicated? It's really not. Just take a look.
#MoldableDevelopment denotes a way of programming through custom tools. To make it practical, we need to make creating these tools be highly inexpensive. It's not enough for tools to be extensible, the ability to extend should be seamless. This is a research problem.
We first published our work on extending the debugger a decade ago and we implemented in #GToolkit. Indeed, we showed that we can improve debugging hard problems through custom debuggers. However, after a decade, we could observe that we only had a few dozen debuggers while we had thousands of inspector extensions. We asked ourselves: can we do better?
The problem was that extending the debugger was slightly too expensive. We could notice a need while debugging specific problems, but building the custom debugger required us to stop, code somewhere else and needing to know a bit too much about the underlying implementation. If we learnt anything over the past 15 years is that custom tools only get adopted in practice if the friction is small and the cost is mostly amortizable on the first use. And extending the debugger, while powerful, was slightly above this cost threshold.
So, we went back to the drawing board and started from the basics. What is a debugger? An inspector over the stack.
We already knew how to extend the inspector seamlessly. So, what if we can extend the debugger similarly? And indeed, we found out that we can! Extending the debugger can be as simple as promoting an exception's inspector extension. That's it.
Watch @onierstrasz explanation below for more details.
Moldable exceptions are all about extending the debugger by extending the exceptions' inspector.
How does that work?
Watch @onierstrasz's talk at Onward 2024:
https://t.co/jS4DjqPtzQ
We're excited to welcome Oscar Nierstrasz to the #YOW24 stage to share a series of case studies and illustrate a number of key patterns behind #MoldableDevelopment.
Get tickets here:
📍 MEL https://t.co/v50Wxpip9z
📍 BNE https://t.co/icKclDgEuY
📍 SYD https://t.co/WPgV0Uz8tB
If you are a technical person and want to convince your business manager to invest in better skills and tools for legacy modernization, start from the business perspective.
Say you looked into #MoldableDevelopment and are now convinced that you need to invest in it because it's your way out of what feels like a legacy hell. But how do you convince your business manager to invest in it?
One way is to start from a problem that business can quantify. Investing in the skills and technology needed to create custom tools is not on any business person radar today. Furthermore, often programming itself is still perceived as just a cost rather than an investment. In such situations, it can be difficult to argue for more investment. But they do have problems that they want to see addressed. There are at least two kinds of such visible problems:
1) long standing problems that do not seem to be ever addressed, or
2) pressing problems that are (about to be) triggering crises.
In the long standing category could be decreasing the cost of bug fixes after a release. It can be speeding up the customer support. It can be accelerating the adaptations to external systems. It can be limiting the risks associated with a long running migration. It can be improving the performance or scalability. You get the idea. In this category you can take a sample of the problem and show how that can be improved. Most of the time these problems are due to lack of visibility. Build dedicated tools for them to get a better perspective. It inevitably leads to new insights that you can then act on.
A recognized pressing problem can be another point to start from. I say "recognized" because there are always problems but most are typically not acknowledged on the business side. When in a crisis with no visible way out, people tend to be more inclined to try last resort actions and accept apparent magic. You can use this as an opportunity. Create tools that provide insights that are directly relevant for the crisis and build from that.
All in all, instead of selling the custom tools idea, you can show outcome. Start from a quantified problem and deliver a quantified result. Once you've done that you can show how you've done it and argue for more investment.
Btw: this path does not require scale. It can start with a single programmer.
#MoldableDevelopment is a way of programming through custom tools. We approach every development problem through a custom tool built specifically for that problem. This often leads to thousands of little tools per system...
"Thousands of tools? But is this not expensive?"
Well, no. Quite the opposite. They are cheaper to build than not to build. These tools do away with most need to manually read code, and reading code is the most expensive activity in software engineering today. Instead, these custom tools, built specifically for the questions we have, summarize the system and help us make decisions much faster and more systematically.
"So, these tools summarize the system. What AI are you using to build them?"
Ahh, well, summarization is not the same as AI. For example, a view over some data summarizes that data. Such a view is produced by a small program that can be created to capture what we are specifically interested in at that moment in time. Through such views we can make decisions much faster than we can by reading the data directly. And everything in a system is data, including source code, configurations, logs etc.
While AI can play a role in this equation, it is not essential. We can indeed rely on some AI to generate tools but that is mostly an optimization.
"But tools are expensive. How can it be practical to build thousands of them?"
Well, that's the thing. Tools do not have to be expensive. They can be as inexpensive as a few lines of code built in minutes.
"It's hard to believe this."
I know it is. That is why we built Glamorous Toolkit. Take a look.
"Ah, so this is whole Moldable Development thing is just an ad gimmick for your commercial tool?"
Not really. Glamorous Toolkit is free and open-source. We built it exactly so people can experience the idea of custom tools by themselves, in their own terms. Moldable Development is a practice. We used and validated it extensively. You can use #GToolkit to solve actual engineering problems with your systems. At the same time, and perhaps more important, Glamorous Toolkit is an extensive case study of Moldable Development showcasing literally thousands extensions that explain the inner workings of the environment.
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