The author has a new thing which is different - unfamiliar - and ostensibly better. To a customer, when is a claim for better credible, and when does better really better? How does better measure up as benefit?

The challenge for any product story is to a) illuminate the need - why is the status quo intolerable and b) communicate the benefit tangibly to your audience. That the audience thinks your new thing is worth the effort depends on them understanding the new thing, feeling the need, and feeling good about the effort needed to exploit your thing. You'd like to get to your customer saying "I want that".

I think the specific question for axonlore.com is communicating benefit - how does it impact whatever workflows it serves? The website is a "thing" story, vs a benefit story in my view. I like "enterprise intelligence" as a thing, but it's a tough product. It inevitably implies culture change, and in the decision making space, the key people think they are intelligent enough already -- they want to scale themselves. Someone mentioned "better RAG" - maybe the story is how agents can perform better and more cost effectively. I am not clear that "the market" knows that it needs that yet.

I don't think "familiarity" is the right framing. Application automation, or workflow automation, or whatever the enteprise framing is of agentic solution generation, is to me a question of variance and effort. Variance in the quality of a work product and the net effort to produce it. Variance is the complement to familiar.

- high variance / low effort: prototypes

- low variance / low effort: automating anything repetitive and complicated

- low variance / high effort: demonstrated need for precision and or reliability

- high variance / high effort: when there seems like potential huge upside, or existential risk.

From an IT perspective, enterprise status quo is towards low variance/high effort. The market "want" here now with "agentic" seems to the benefit of low variance/low effort solutions ... where, in enterprise, getting an adequate solution is no longer gated on negotiating with or relying on IT or dev. Ultimately, I think enterprises want low variance, low effort operations -- customers of enterprise customers pay for low variance. I think an Agentic-IT solution question will be how confidently can one iterate and converge to that from whatever is delivered in the first pass. What's the ultimate effort of getting something "right enough".

Homepage - https://goalapl.atlassian.net/wiki/spaces/GOAL/overview

Wikipedia - https://en.wikipedia.org/wiki/GOAL_agent_programming_languag...

Programming Guide - https://goalapl.dev/GOALProgrammingGuide.pdf

Game case study - https://multiagentcontest.org/publications/AppliedGOAL.pdf

"We consider composite media with a broad range of scales, whose effective properties are important in materials science, biophysics, and climate modeling. Examples include random resistor networks, polycrystalline media, porous bone, the brine microstructure of sea ice, ocean eddies, melt ponds on the surface of Arctic sea ice, and the polar ice packs themselves. The analytic continuation method provides Stieltjes integral representations for the bulk transport coefficients of such systems, involving spectral measures of self-adjoint random operators which depend only on the composite geometry. On finite bond lattices or discretizations of continuum systems, these random operators are represented by random matrices and the spectral measures are given explicitly in terms of their eigenvalues and eigenvectors. In this lecture we will discuss various implications and applications of these integral representations. We will also discuss computations of the spectral measures of the operators, as well as statistical measures of their eigenvalues. For example, the effective behavior of composite materials often exhibits large changes associated with transitions in the connectedness or percolation properties of a particular phase. We demonstrate that an onset of connectedness gives rise to striking transitional behavior in the short and long range correlations in the eigenvalues of the associated random matrix. This, in turn, gives rise to transitional behavior in the spectral measures, leading to observed critical behavior in the effective transport properties of the media."

[0] https://breakingdefense.com/tag/modular-open-systems-archite...

[1] https://www.dsp.dla.mil/Programs/MOSA/

[2] https://www.govinfo.gov/app/details/USCODE-2016-title10/USCO...

[3] https://blog.palantir.com/implementing-mosa-with-software-de...

What should I read to better understand this claim?

> LLMs are the equivalent of circles act using language.

Circled apes?