Architectural framework for constrained agency, runtime governance, symbolic drift analysis, and structured emergence

The PUTMAN Model™ is an evolving architecture for building agents and simulations that remain legible under pressure.

It is centered on a simple idea: interesting behavior should emerge from bounded local functions, not from unconstrained generation or hidden-state wishful thinking. The goal is not to fake emotion or hand-wave “intelligence,” but to define the conditions under which agents can accumulate state, adapt, drift, recover, and act under explicit limits.

This work spans memory stratification, runtime governance, deviation tracking, narrative coupling, semantic reuse, and multi-agent field behavior. Together, these papers and demos form a stack for building systems that are more inspectable, more bounded, and more capable of meaningful behavior inside constrained worlds.

Spanda Architectural Framework
Papers, companions, and demos for the broader stack:
https://github.com/putmanmodel/spanda-architectural-framework

PUTMAN Model — Core Architecture for Contextual Meaning Reconstruction
https://doi.org/10.5281/zenodo.15634339

Resonant Field Mapping: A Non-Mimetic Empathy Layer for Language Models
https://doi.org/10.5281/zenodo.15701018

This is builder-facing work.

I am building toward agents that can operate inside constrained, inspectable worlds rather than simply remixing language or simulating coherence after the fact. The aim is to provide foundations that stronger builders, larger labs, and better-resourced teams can actually use.

I build for people more technically capable than I am, and I am fine with that. My value is in architecture, framing, cross-paper coherence, and identifying the control surfaces that make richer systems possible without collapsing into noise, script, or silent drift.

A compact summary of the design philosophy:

• No constraint = noise
• Too much constraint = script
• Useful emergence = structured freedom

The current stack is centered around a series of papers and companion notes collected here:
https://github.com/putmanmodel/spanda-architectural-framework

Key layers include:

Agents should infer only from admissible structure, not from convenient projection.

State is tiered across short-term, intermediate, and structural layers so persistence is earned, not silently absorbed.

Deviation is treated as an inspectable, governable signal rather than a vague feeling that “something is off.”

Short-horizon salience can redirect attention without automatically mutating durable state.

Promotion into persistent state remains governed, explicit, and boundary-aware.

A typed representation layer for structured state exchange, replay, and interoperability.

Systems can accumulate thematic pressure and diverge in interpretation even when representation overlaps.

Local interactions can propagate, amplify, dissipate, and destabilize across a group without requiring magical global knowledge.

Companion papers extend the stack into self-relevance, cross-environment semantic continuity, and trajectory-level drift detection.

• Runtime LLM governance
• Agent-state monitoring
• Symbolic drift detection
• Memory-safe agent architectures
• Multi-agent escalation analysis
• NPC and simulation behavior modeling
• Structured emotional field systems
• Constrained generative environments
• Human-in-the-loop governance layers

The main architecture stack repo containing the paper series, companion notes, and demos.
https://github.com/putmanmodel/spanda-architectural-framework

Core conceptual framework for contextual meaning reconstruction and layered interpretive structure.

A non-mimetic empathy/control layer for modulating language-model behavior under bounded persistence and runtime constraints.

Deviation and drift-oriented monitoring for contradiction, mismatch, escalation, and trajectory change across turns and state updates.

A simulation-facing layer for affective field behavior, propagation, memory interaction, and bounded adaptation.

Small demonstrators focused on leases, denial by default, reconvergence, reversibility, and inspectable control.

• PUTMAN Model — Core Architecture for Contextual Meaning Reconstruction
  https://doi.org/10.5281/zenodo.15634339
• Resonant Field Mapping: A Non-Mimetic Empathy Layer for Language Models
  https://doi.org/10.5281/zenodo.15701018

For the current architecture-paper stack, companion notes, and associated demos:
https://github.com/putmanmodel/spanda-architectural-framework

This is a solo effort built with limited resources, limited lab access, and a strong bias toward architecture that can survive contact with reality.

I am always interested in:

• constructive technical feedback
• serious implementation critique
• opportunities to help other builders work from a stronger architectural foundation
• shared resources, collaboration, or practical paths to growth

I am not trying to present this as a polished corporate lab. I am trying to build something structurally sound enough that it can be useful beyond me.

CC BY-NC 4.0
Creative Commons Attribution–NonCommercial 4.0 International

All symbolic system names and project naming conventions are documented through timestamped public use.

Stephen A. Putman
Email: mailto:putmanmodel@pm.me
GitHub: @putmanmodel
X: @putmanmodel
Reddit: @putmanmodel
BlueSky: @putmanmodel.bsky.social