> I dug through the chain-of-thought publication and did actually find (a few of) them. If people working on these LLMs are reading, it's very important to me that these are contained in the actual model output.
This is a very important point, especially when the output is from a non-deterministic random walk with some unknown probability distribution.
> Although there is an element of apparent sloppiness in many creative people, discipline is also required. (Note that time-sharing has been condemned by some as encouraging sloppiness, as opposed to batch processing [where sloppiness can be exceedingly costly in time and computing resources]. Perhaps time-sharing could actually encourage creativity, although there is the countering argument that computers intrinsically stifle creativity.) Similarly, diversity of experience also appears to be extremely important (e.g., [Sheppard]); the perspective afforded by familiarity with a variety of systems, subsystems, programming languages, and methodologies provides extremely valuable insights, especially where there is wide diversity (e.g., among TOPS-20, Multics, UNIX, and OS/370; SCRIBE, TEX, PUB and ROFF; Pascal-based languages and LISP; a formal methodology/specification language and conventional design).
I will think “Agentic Engineering” is the “time-sharing” of our time. Embrace it.
> There is an old adage (e.g., Zen) to the effect that we become what we perceive. In computer terms, our (human)
outputs become identified with our inputs. Computer technology is exceedingly habit forming, and our civilization seems to be becoming more computer-like, in the name of "progress". Many people tend to identify with their computers, while others become more computer-dependent, willingly or unwillingly. In addition, the so-called "factory experience" has an antihuman element to it. Although it could indeed help to reduce repetitiveness, it must also allow a suitable role for creativity. (In the spirit of this paper we note that unbridled attempts at creativity can often be detrimental, resulting in obfuscational terminology that masks an absence of novelty, or the reinvention of suboptimal or intermediate steps that have previously been discarded by others for subtle reasons not perceived by the "reinventor".) Thus, it is incumbent on system designers and system development managers to understand the negative effects of the use of computers, and to attempt to minimize those negative effects. In this way, it should be possible to increase incentives, challenges, and satisfaction, to reduce boredom, burnout, and laziness, and generally to increase the effectiveness of computer developers and users.
> Even more importantly, what happens to teamwork? If we are all a BBM now—or rather, if we all have personal armies of BBMs, permanently locked in a manic state, springloaded at all hours to generate things for us-and-only-us—how do we work together? How do cocoons communicate, interoperate? What does a team of ai solipsists look like? It sounds oxymoronic.
One example of teamwork is how the programmers and researchers worked together to build the UNIX SYSTEM (https://www.cs.dartmouth.edu/~doug/reader.pdf). It is not a product but an environment optimized for building tools and solving practical problems with tools written in C (while BBMs were busy with Lisp in Boston .;-)
C++ is a totally different story and you need an IDE for that.
If WASM succeeded in being the one universal ABI, it could be the perfect successor to the unix pipe for the AI age. Wasm modules for libraries, that double as terminal tools.. One could only imagine
I couldn’t help but notice the similarities between human aging and “filling up” the context window in Agentic AI: the “chain of thoughts” getting so heavy that nothing new can be created.
On the other hand, there was lot of disruptive work did survive, or we can call them “hallucinations”.
The reason I wrote that compact makefile is that I am at the beginning of a long journey to study the coding style of ngnk (https://news.ycombinator.com/user?id=ngnk).
I can see the potential of doing some implementation of APL/J/K at levels even lower than C, like how those guys did APL\360 using assembly language. It is going to be super fun in the era of everyone using LLM to pump out verbose Python/TS/Rust code with context windows bigger than the whole operating system.
Some people must be working on training some models exclusively on high quality OSS code base like curl and SQLite without the noise of low quality training data.
I would do that with 100% local models from scratch.
Especially when the solid core now ships with a web ui and API compatibility with OpenAI and Antropic. In my test of ai clients, Ollama was the only one I deleted.
This is a very important point, especially when the output is from a non-deterministic random walk with some unknown probability distribution.
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