August 11, 2025
SIGPfB: LLM Adoption Capability Maturity Models and Protocol Evolution
Participants: timber1997, _vgr, rafa_0x, sachbenny, anurajenp
The SIGPfB group engaged in an extended discussion about developing a comprehensive Capability Maturity Model (CMM++) specifically designed to describe how organizations mature in their adoption and integration of Large Language Models. Rather than treating LLM adoption as a generic management trend, participants analyzed how protocols and practices must evolve at different organizational maturity levels, using a framework that captures technical capability, political dimensions, and business unbundling/disruption dynamics.
Key to the discussion was the observation that successful organizations are not forcing LLMs into existing workflows but instead adapting their protocols to leverage what LLMs do well. Participants identified three categories of protocols: LLM-native (like reflexive learning to mediocrity), LLM-mutated (like memos replacing slides), and LLM-resistant (like legal oversight requirements). The group also explored how geopolitical and regulatory contexts shape adoption patterns, and how organizational politics around model selection and cultural fit create real constraints on AI deployment.
The group committed to developing a working CMM++ whitepaper with defined levels (0-6), each describing organizational state, key tensions, and emerging protocols. They noted that current companies primarily occupy levels 0-3 (the 'uncanny valley'), with levels 4-6 requiring speculative protocol fiction. Plans included publishing findings, engaging with companies at various maturity levels, and potentially presenting at the Berlin Sci-fi futures meetup.
- Organizations are adapting workflows to match LLM capabilities rather than forcing LLMs into existing processes—teams switching from PowerPoint to memos because LLMs excel at memo generation rather than slide design.
- A CMM++ framework should include political dimensions and (un)bundling dynamics beyond traditional capability maturity, with each level defining key tensions, emerging protocols, and organizational states.
- Levels 1-3 represent an 'uncanny valley' where organizations appear to be using AI but haven't fundamentally transformed, while levels 4-6 represent genuine discontinuous organizational performance shifts similar to continuous deployment adoption.
- Regulatory frameworks (state strength vs. law strength) will determine whether organizations face predatory pricing pressure, state control, or compliance-driven maturation in AI model selection and deployment.
- Political alignment among human participants within organizations matters more than AI alignment itself, as it determines which AI models are adopted and how organizational culture constrains AI tool selection.