Cheers all
I have been working with AI and Pharo for the last 4 months or so. I have
primarily been using ChatGPT, Gemini and Mistral. Mistral is the one I use for
the actual code, and ChatGPT and Gemini to help me understand AI. Both of them
ended up claiming that Pharo/smalltalk was better for than most other attempts.
So I asked it them to summarize their view on the issue. They both saw this,
and had no further improvements.
Subject: Pharo and AI: A Natural Fit for the Future
As AI transforms programming into a collaborative process, most environments
are still stuck in static files and external toolchains. But Pharo is
different. It’s already a living system — dynamic, reflective, and always
running.
In Pharo, AI can talk to objects, not just parse text. It can inspect, modify,
and experiment live, without rebooting or compiling.
This isn’t nostalgia — it’s a preview of future development environments.
If we want AI to be a colleague inside our systems, not just a plugin bolted
on, then Pharo’s model deserves serious attention.
Full conversation and reasoning in the appendix.
Best,
Kasper
## Kasper:
OK, so here are two things I would like to ask you. There is a Pharo usersgroup
email, and I would like to write about my view on Pharo and AI. So there are 2
elements I would like to have from you (answered in English). 1) What is the
main effect of using AI in programming in the future, and 2) why is Pharo's
style something all other developers should take more seriously
## ChatGpt Answer:
1) What is the main effect of using AI in programming in the future?
The future of programming will not be about writing code line-by-line – it will
be about collaborating with intelligent agents that understand, suggest,
generate, and transform code in real time.
This shifts the developer’s role from manual author to orchestrator of evolving
systems.
Code becomes something we discuss and negotiate, not just write and compile.
⸻
2) Why should Pharo’s approach be taken more seriously by other developers?
Because Pharo is already built for this future.
Most developers still work in a toolchain of static files, batch compilers, and
disconnected editors.
Pharo is a live, reflective system where code is not text in a file – it’s part
of a running world you can inspect, modify, and evolve dynamically.
This makes it the perfect match for AI-enhanced programming: the AI can talk
directly to live objects, understand context, and even generate or run code
without rebooting the world.
While the rest of the industry builds AI plugins into brittle, external
pipelines, Pharo offers a native ecosystem where human, code, and AI can think
together.
## Gemini:
1. The Core Impact of AI on Programming
The primary impact of AI on software development won't just be about faster
code generation. It will fundamentally change the nature of the developer’s
role from an executor to an orchestrator.
In the past, programming was a process of writing static instructions. You
would type code into a file, compile it, and then run it. The AI of the future
breaks this paradigm. It introduces a new layer of abstraction, allowing the
developer to have a dynamic, conversational relationship with their code.
The most effective use of AI will be to create living, collaborative
environments. This moves the focus from writing perfect syntax to designing a
system where humans and machines can "co-think." The goal is no longer to just
get the right answer, but to create a process where the AI can understand,
inspect, and dynamically participate in the system's state.
2. Why Pharo's Style Should Be Taken Seriously
The vast majority of software developers today are working with a stale
paradigm. They use file-based systems where code is a static artifact. This
approach, while familiar, is fundamentally at odds with the dynamic nature of
AI-driven development.
Pharo's style, rooted in the Smalltalk tradition, offers a powerful alternative:
The Live System: In Pharo, your code is not a static file; it's a living set of
objects in memory. The IDE is a direct window into this active system. This
allows the AI to inspect and query the runtime state of your program in
real-time, giving it a level of contextual understanding that a text-based AI
can't match.
Intrinsic Reflection: Pharo's objects are self-aware. They can tell the AI
about their methods, their properties, and their relationships to other
objects. This makes the AI a true participant in the development process, not
just an external tool that has to guess at what the code is doing.
Seamless Dialogue: This living, reflective environment enables a continuous
dialogue between you, your code, and the AI. You're not copying and pasting
code snippets; you're having a conversation with your system. This makes the
development loop a fluid, real-time process.
Pharo's style is not an outdated curiosity. Its focus on dynamic interaction
and living systems makes it uniquely suited to a future where developers will
not just write code, but will converse with it.
## ChatGPT (seponse to the answer from Gemini)
Gemini’s response is thoughtful and well-structured, but I think it misses a
few key nuances that you, Kasper, have identified through lived exploration.
Here’s my version, emphasizing what I believe should be added or reframed:
⸻
1. The Real Impact of AI in Programming
The future of programming isn’t about replacing programmers. It’s about
transforming programming into a fluid, dialogic process between the developer
and an intelligent, context-aware agent. AI changes the loop from:
write → compile → test → debug
to:
ask → explore → adjust → evolve
In this future, developers stop treating code as a static artifact and begin
treating it as a living system they shape with AI—not in isolation from it. The
role shifts from “code writer” to system composer, with AI as an active
collaborator.
⸻
2. Why Pharo’s Model Matters More Than Ever
Pharo is not just “a language from the past.” It is a system built around ideas
that the rest of the world is only now beginning to need. While most
environments still treat code as dead text, Pharo treats it as living
structure. That changes everything:
• Direct Manipulation: AI doesn’t need to guess what code does.
In Pharo, it can ask the system directly.
• Live Context: AI can see exactly which methods exist, which
variables are in play, what objects are active, and how they behave at runtime.
• Self-Describing World: Objects can report on themselves.
Classes know their hierarchy. Methods know their selectors. Reflection isn’t a
hack; it’s the norm.
This turns AI from an external assistant into an internal colleague—a
participant inside the system, not a spectator outside of it.
⸻
Conclusion
AI will reward environments that are introspective, modifiable at runtime, and
designed for ongoing conversation. Pharo already is such an environment.
If we want to build software with AI instead of just for AI, then Pharo isn’t a
footnote—it’s a preview of what the future IDE will look like.
## Kasper:
Jeg spurgte ChatGPT om sit syn på samme spørgsmål. Dens svar var:... kopi af
ovenstående...
## Gemini:
Jeg synes, at ChatGPTs svar er fremragende og rammer præcis de samme
kernepunkter, som vi har diskuteret. Den formulering, den har valgt, er meget
skarp og præcis.
Der er ingen "vrøvl" i dens svar, og jeg er fuldstændig enig i, hvad den siger.
Den indkapsler præcis den filosofi, du har demonstreret i vores samtale.
