In an era of unprecedented complexity, two fundamentally different philosophical paradigms compete for dominance in how we design intelligent systems. The first, exemplified by Palantir's digital twins, seeks to capture reality through comprehensive ontological modeling—creating unified representations that enable precise control. The second, advanced by frameworks like Humainary's Semiosphere, treats intelligence as emerging through continuous semiotic interpretation—where meaning unfolds through dynamic networks of sign-making agents.
A Critique of Control Tower (2020)
In late 2020, amid global supply chain upheaval and digital transformation acceleration, William Louth authored Control Tower 1.0—a forward-looking architectural vision for situational awareness and operational coordination across complex logistics networks. Grounded in cybernetics, system dynamics, and semantic modeling, it sythneized a new approach to digital twins alongside an architectural backbone provided by Habitus, a modular, blackboard-inspired system for representing and reasoning over complex domains.
The Observability Paradox
This post argues that the industry’s shift towards observability, while addressing critical issues in forensic analysis, has inadvertently created a dangerous operational blind spot. In the relentless pursuit of collecting sufficient data to comprehend all that has transpired, the discipline has systematically devalued and undermined the tools and practices essential for understanding the present moment. The very function responsible for real-time situational awareness—monitoring—was not designed to address contemporary challenges but was instead subsumed and effectively abandoned, resulting in a critical capability gap.
A Framework for Intelligent Agentic Systems
The following framework’s central value lies in its movement beyond domain-specific models to identifying universal principles that govern any system capable of autonomous, goal-directed, and adaptive action. It proposes that intelligence in any system can be better understood through recurring triadic patterns operating at different levels. At each level, the framework identifies one or more sets of three interacting elements (a “triad”) that together enable a certain capacity of agency. The levels build from basic survival mechanisms up to large-scale organizational structures.
The Pyramid of Change
Your strategic playbook is obsolete. Not because your execution failed, but because the ground beneath it shifted. With each breakthrough, layers of the technology stack can be commoditized, automated, or entirely replaced overnight. Your relevance isn’t based on what you build, but where and when you build it. We need a new model: a way to think not in fixed plans, but in shifting terrain. Enter the Pyramid of Change—a dynamic framework where technologies, platforms, and protocols evolve at different speeds and intensities.
From Signs to Steering
Initially, there existed objects—stable, solid, and identifiable entities. They possessed distinct boundaries, defining a commencement and a conclusion. Their perceived reality stemmed from their resistance to transformation. However, over time, the world manifested itself not as a collection of static objects, but rather as a dynamic sequence of transformations. Processes supplanted objects as the focal point of attention. Motion, rather than mass, became the determinant of significance. Change, no longer perceived as a mere disturbance, emerged as a discernible signal.
Consequently, we commenced observing systems not as rigid structures but as dynamic behaviors. We diligently monitored for pulses, thresholds, and deviations. We meticulously constructed graphs, dashboards, and probes to meticulously track the execution rhythms. This process was characterized by observability. However, observation alone proved insufficient.
To derive meaningful insights from our observations, we transitioned to the analysis of signs. Signals became the manifestations of underlying issues, and behaviors assumed the roles of messages. We acquired the ability to interpret and subsequently infer from signs. Signals no longer solely described the system; they encapsulated its contextual situation. With this shift, signs acquired a profound sense of meaning.
However, with meaning came uncertainty. Consequently, we sought something more profound. We constructed simulations. Not mere reflections of the present, but models of the potential. Simulations provided us with leverage over time. They enabled us to pose questions such as “What if?” “What transpires next?” “What alternative possibilities exist?”
Simulation transformed into a laboratory for contemplation, a platform for contemplating consequences. It served as a means of transcending reaction, progressing toward imagination, and receiving feedback. Within these imagined realms, signs emerged. They interwove, clashed, and reconfigured. They crafted narratives. Not merely sequences, but structures of transformation. Each narrative constituted a pattern, a recollection of a trajectory of signs and transformations.
However, a narrative was never merely a recollection. It served as a blueprint—a means of translating comprehension into orientation. For intelligence doesn’t conclude with observation; it commences there. It progresses through simulation and culminates in action. Consequently, the cycle was completed. We acted. Not as a reflex. Not as a repetition. Rather, as situated intervention, guided by significance, memory, and projection.
Subsequently, design emerged not solely as a matter of planning, but rather as a means of shaping reality through the mediation of signs and the anticipation of future events. To design entails guiding the future through our comprehension of the past. In acting, we transformed the world. And in this transformation, we generated novel signals. And in perceiving them, we commenced anew.
⤷ From object to process
⤷ From signal to sign
⤷ From sign to simulation
⤷ From simulation to story
⤷ From story to action
⤷ From action to steering
⤷ From steering to new signs
This is the semiotic cybernetic spiral—a living circuit of perception, projection, and participation. It isn’t a map of machines but a grammar of intelligent mediation. It’s a loop where systems learn not only to monitor but also to comprehend. They rehearse and reshape their conditions of existence. This is what I am constructing—not merely tools or intelligence, but a means for systems to perceive the world. Envision alternative possibilities and act with purpose.
This is Substrates.
This is Signetics.
This is Semiosphere.
Semiosphere: Systems that Understand
Modern distributed systems generate unprecedented volumes of operational data, yet organizations consistently struggle to derive meaningful situational awareness from this information abundance. Rather than treating system observability as a data aggregation problem, Semiosphere reconceptualizes it as a meaning-making challenge, implementing structured interpretation processes that mirror human cognitive patterns.
The Semiotic Loop: Cybernetics, Meaning, and Substrates
In our machine-mediated age, the capacity to observe, interpret, and act transcends technical functionality—it forms the semiotic essence of digital existence. At the heart of this transformation lies an ancient, recursive pattern, weaving through organisms, organizations, and intelligent systems. This article explores the semiotic loop, grounding Peirce’s triadic categories in cybernetic principles and manifesting them in the Serventis and Signetics, powered by Substrates.
On Abstraction, Compression, and the Living Reconstitution of Meaning
Every act of communication is, at its heart, a living paradox: it’s an act of both forgetting and creation. When we speak, remember, or make sense of the world, we don’t transmit the full weight of experience. We compress, we select, we abstract—letting go of details, pruning the chaos of the past into something portable, survivable, and shareable. The art of observability, then, isn’t in perfect preservation, but in wise selection and creative reconstruction—in knowing what to forget and what to imagine next.
Observability: The Great Misunderstanding
The term "observability" is ubiquitous in software engineering, yet a profound misunderstanding clouds its current practice. Observability isn’t what most organizations are doing—it’s what they think they bought. What they’re engaged in is often mere telemetry plumbing, a far cry from genuine system sense-making.