The art of competing

Competition among companies and their products and services has not changed significantly in terms of the market dynamics (price, feature set, utility). What has changed is the pace at which feature parity among peers is converging. There used to be a real lasting advantage in developing specific features to differentiate from your competitors, but now those gaps are closed very rapidly. This morning I was reading Ulrich Homann latest blog post in which he explained this from a SaaS provider perspective and how many SaaS companies seem to be blind to their own competitive advantage (their moat). It seems weird but. it looks as if by focusing on your competitors product, you lose insight to what makes your product or service great.

Producing work or value?

I’ve been working as an “IT architect” (with apologies to Architects who bear this title as part of a regulated profession, something for another post, so excuse the digression) for a long time. In this field we’re working with various abstraction levels, fancy language that talks of “Business and IT alignment”, viewpoints, current and target states, solutions, systems, software, data, information and what not. All that work produced lots and lots of documentation, which was valuable in its own right in that it provided a track record and history of how an enterprise had grown its systems over time. It captured what was significant in terms of investment and what were meaningful differentiating factors that resonated with the enterprise. A reflection of the culture and mindset at which it operated in a larger society. The documents were of utmost importance, to demonstrate real thought had gone into consequential decision making to support boards and decision makers justify their coarse of action.

Defining “the mess”

One of my inspirators, Dr. Russel L. Ackoff, wrote something along the lines of: “If you want to improve a system, you first have to define the mess”. This reminded me of something really important, the use of language and aiming to be precise as possible significantly matters to be able to communicate “a mess” clearly and unambiguously. This allows critical thinking to emerge and helps to build a consistent, mostly objective (even rational?) view of the situation at hand. However, some of that in the realm of AI has seemingly been lost.

Finding synergy

Over the past 15-20 years in my day-to-day (working) life I’ve been thinking a lot about compute platforms. Starting with hands-on operational experience and learning to operate systems at scale. Also with creating systems architecture and design, which requires a lot of forward thinking and planning. In that work, we usually look at platform aspects in relative isolation. This helps to limit discussion but also can trip you up by overlooking or under-emphasizing significance of some aspects. By virtue of doing this work long enough, over time a bigger picture on the subject matter has emerged/materialized that has really helped me make better decisions. I’d thought I’d take the opportunity to organize my brain a bit on this topic by writing it all(?) down in this post and hopefully share some useful insights.

The Outer loop

With the advent of Copilots and Agentic coding, a lot of the industries focus has been on capturing and optimizing the pure Development effort performed by developers. This is highly successful and is innovating at a stunning rate. What has been left out is how the outer loop need to change.

Why the outer loop matters

The outer loop has been invented (for lack of a better word) to achieve the following: