Operational Interdependencies

An Agentic Service Group (ASG) relies on a lattice of tight integrations with existing enterprise functions. The ASG provides specialist agent capabilities, while partner departments provide the governance, infrastructure, and context required for those agents to function safely and effectively.

Cybersecurity & Risk

Dynamic Trust & Cognitive Defense

Traditional security relies on static permissions. Autonomous agents require a dynamic approach where trust is earned and verified in real-time based on behavior. This partnership moves beyond simple access control to establishing a "Zero Trust for AI" architecture that protects the enterprise from both malicious actors and unintended agent behavior.

ASG Provides

  • Cognitive Threat Modeling: Predictive analysis of how agents might be manipulated (prompt injection) or socially engineered, allowing for pre-emptive defense design.
  • Provable Safety Frameworks: Mathematical definitions of "safe operating bounds" for autonomous decision-making, rather than just retroactive logs.

Security Delivers

  • Dynamic Trust Architecture: Infrastructure that evaluates agent intent and context in real-time, granting access only for the specific micro-duration of a valid task.
  • Automated Governance Policy: "Security-as-Code" that instantly adapts guardrails based on the changing risk profile of the agent's environment.

Cloud & DevOps

Continuous Delivery of Agentic Workloads

The ASG acts as a factory producing a constant stream of new agent capabilities. This partnership ensures those capabilities reach production rapidly and reliably. The focus shifts from static hosting to high-velocity continuous delivery, ensuring that as soon as an agent is improved, it is deployed.

ASG Provides

  • Agent Pipeline: A continuous stream of versioned agent candidates ready for deployment.
  • Release Criteria: Specific pass/fail metrics (e.g., "95% accuracy on Golden Set") for promotion.

DevOps Delivers

  • Automated Delivery: CI/CD pipelines that take agent code from commit to production automatically.
  • Dynamic Infrastructure: On-demand provisioning of containerized environments for agent execution.

Platform Engineering

Delivering the Agent Framework & Mesh

Platform Engineering is responsible for the delivery, operation, and enhancement of the unified Agent Platform. This creates a separation of concerns: The ASG focuses on agent cognition, while Platform Engineering maintains the Agent Framework (developer experience) and the Agent Mesh (non-functional concerns like networking, sidecars, and observability).

ASG Provides

  • Framework Requirements (Dev): Defining the abstractions builders need (e.g., "We need a standard memory interface for vector DBs").
  • Mesh Policy Specs (Ops): Logic requirements for traffic shaping, circuit breaking, and inter-agent mTLS.

Platform Delivers

  • The Agent Framework: SDKs and scaffolding that standardize how agents are built, abstracting boilerplate infrastructure code.
  • The Agent Mesh: A sidecar architecture handling service discovery, observability, and resilience (retries/timeouts) transparently.

API & Integration Teams

Modernizing Infrastructure with MCP & Gateways

Agents cannot function effectively on legacy infrastructure. The priority is a radical refresh of the platform layer. Integration teams must deploy Model Context Protocol (MCP) servers and AI Gateways. This often requires rewriting or creating new "Agent-Native" APIs that reduce token usage and provide the semantic context LLMs need.

ASG Provides

  • Semantic Tool Definitions: High-level specs defining the intent and constraints of tools, not just raw JSON schemas.
  • Gateway Policies: Configuration rules for the AI Gateway to handle auth, logging, and rate-limiting centrally.

Integration Delivers

  • MCP Server Deployment: Standing up Model Context Protocol servers that standardise how agents discover and access data.
  • Modified "Agent-Native" APIs: Rewriting endpoints to be verbose where needed (context) and concise where necessary (token savings).

Data Engineering

The Corporate Intelligence Layer

The strategic goal is not just "cleaning data," but constructing the "Corporate Memory." Data Engineering must transition from managing storage to managing meaning. This partnership focuses on transforming isolated data silos into a connected Knowledge Graph that serves as the shared brain for all enterprise agents.

ASG Provides

  • Ontology of Intelligence: High-level mapping of how business concepts relate (e.g., "Customer" relates to "Contract"), guiding the structure of the Knowledge Graph.
  • Context Quality Standards: Strategic definitions of "AI Readiness," pushing data ownership and curation responsibilities back to the business domains.

Data Eng Delivers

  • The Semantic Layer: A governed interface that abstracts raw database schemas into meaningful business concepts that agents can reliably reason about.
  • Knowledge Graph Infrastructure: The active backbone of corporate memory, automatically linking unstructured documents to structured records to power deep reasoning.

Business Architecture

Value Stream Optimization

The ASG builds the "how", but Business Architecture determines the "where". This relationship focuses on identifying bottlenecks in value streams where human latency is high, and mapping agent capabilities to those specific friction points to maximize ROI.

ASG Provides

  • Feasibility Studies: Technical assessments of whether current models can actually handle the proposed tasks.
  • Performance Metrics: Speed/Accuracy data from agent prototypes.

Business Arch Delivers

  • Value Stream Maps: Detailed process flows highlighting "wait states" ripe for automation.
  • Process Re-engineering: Simplifying complex human workflows before attempting to automate them.

Enterprise Architecture

Architecting the Autonomous Enterprise

The rise of agents requires a fundamental rethinking of the enterprise topology. EA moves from governing applications to governing the "Agentic Ecosystem." This partnership ensures that the organization is designing for a future where human-agent teaming is the primary unit of work, preventing vendor lock-in and fragmentation.

ASG Provides

  • The Agentic Target State: A visionary blueprint of the future operating model, defining how autonomous agents will reshape core business capabilities over the next 3-5 years.
  • Ecosystem Interoperability: Strategic protocols ensuring agents from different ecosystem islands (Salesforce, Microsoft, Custom) can collaborate rather than compete.

Enterprise Arch Delivers

  • Cognitive Capability Mapping: Redefining the business capability map to distinguish between "Commodity AI" (buy) and "Differentiating AI" (build).
  • Sovereignty Strategy: Architecture principles ensuring the enterprise retains ownership of its intelligence and weights, preventing dependency on closed model gardens.

Human Resources

Workforce Transition & Organization Design

The deployment of autonomous agents is a workforce restructuring event. As agents take over routine cognitive tasks, human roles must be redefined to focus on oversight and strategy. Failure to partner with HR results in employee rejection of the technology.

ASG Provides

  • Task Substitution Analysis: Data showing specifically which parts of a job description are being automated.
  • New Capability Matrix: Definitions of new skills required (e.g., "Output Auditing").

HR Delivers

  • Reskilling Pathways: Formal training programs to move employees to "Reviewer" roles.
  • Org Redesign: Updated org charts recognizing "Hybrid Teams" of humans and agents.

IT Governance & Policy

Compliance, Ethics & Standardization

Agents operate in a grey area of existing IT policies. The ASG works with Governance to update frameworks for the AI era, ensuring agent outputs are legally defensible, ethical, and compliant with industry regulations.

ASG Provides

  • Transparency Reports: Documentation on model weights and decision logic.
  • Risk Registers: A live database of potential failure modes for every deployed agent.

Governance Delivers

  • Policy Frameworks: "Human-in-the-loop" requirements for high-stakes decisions.
  • Audit Protocols: Standardized testing to verify accuracy before production release.