AI Contextual Layer: New Value in the IT Stack | Analysis

# The Context Layer as the Core of Value: How AI is Redefining IT Business Models

Analysts are noting a radical shift in value distribution within the technology stack. Traditional SaaS companies are losing market capitalization, while new players focused on the context layer are shaping the future of enterprise software. This process demands a rethink of system architectures and business strategies.

The Three-Layer Architecture in the Era of Generative AI

Evan Armstrong's research in Context is King shows how generative AI is transforming the software economy. The key thesis: value is shifting from familiar layers to a new domain—the context layer. This process began in 2023, when the market cap of SaaS giants dropped by $300 billion.

The modern technology stack now consists of three fundamentally different levels:

• Systems of record layer — databases and data storage
• Interface layer — user applications and frontend
• Context layer — business process logic and institutional knowledge

Meanwhile, the first two layers are gradually becoming commodities. AI code generation already accounts for 20% of total volume, and the cost of developing interfaces is plummeting. The critical issue for traditional SaaS companies: their margins have fallen from 85% to 50-65%, and projected market growth has halved—from 36% to 17%.

Why the Context Layer is Becoming a Strategic Asset

The context layer isn't just an intermediate link between data and interface. It's the system that defines:

• What actions AI agents should perform
• In what sequence
• Who has permission to perform operations
• How to evaluate process success

Unlike databases (which store raw data) and applications (which provide the interface), the context layer holds the semantic structure of the business. Example: algorithms that determine which actions lead to closing a deal and which result in order failures.

The key advantage of this layer is the compounding effect. Every AI agent run generates traces that improve subsequent iterations. The longer the system runs, the higher the switching barrier—as unique knowledge about the company's internal processes accumulates.

The Economic Model of the New Technological Paradigm

Armstrong highlights three factors that determine a company's value:

• Growth rates
• Margins
• Terminal business value

For traditional SaaS solutions, all three metrics show negative trends. Reasons:

• Lower barriers to entry: Building basic apps now requires minimal resources
• Budget reallocation: Companies are shifting spending from IT budgets to payroll
• Value shift: Customers get more functionality for less cost

Meanwhile, new AI-focused companies are showing steady growth. Their edge lies in focusing on the context layer, where:

• Coordination costs drop significantly
• Business operations become more transparent
• Previously manual approval processes get automated

Strategic Implications for the IT Industry

The market is undergoing two parallel processes:

For developers:

• The commodity nature of code devalues basic programming skills
• Demand is rising for experts in integrating business logic into AI systems
• The key skill becomes formalizing unstructured processes

For companies:

• Need to reorganize internal processes for AI agents
• Reallocate HR resources from IT departments to analytics units
• Increased investment in context management systems (Context Management Systems)

A particular concern is the forecast for job cuts. If changes in IT amount to 5-10%, managerial and coordination roles could see 20% or more. MBA managers bogged down in endless approvals are at risk.

Key Takeaways

• Value shift: Main profits are now generated in the context layer, not interfaces or databases
• Compounding effect: The longer the system is used, the higher the replacement cost due to accumulated knowledge
• Economic recalibration: Investments are moving from SaaS solutions to AI-focused startups
• New competencies: Need specialists who can formalize business logic for AI
• Strategic race: Control over the context layer becomes the key to competitiveness

Practical Steps for Adaptation

Companies need to:

• Audit internal processes with a focus on formalizing logic
• Build a system for collecting and analyzing workflow traces
• Develop an access rights management strategy for the context layer
• Integrate AI agents into processes with feedback loops
• Retrain IT staff for working with context systems

Special attention should go to securing the context layer. Since it holds critical business knowledge, any compromise could have catastrophic consequences. The architecture must include:

• Multi-factor authentication
• Detailed logging of all changes
• Anomaly detection systems for business logic
• Regular access rights audits

Technical implementation requires moving from monolithic apps to microservices architecture, with the context layer as a separate component. Example basic structure:

context_layer {
  business_rules: [
    { trigger: 'deal_created', actions: ['assign_manager', 'calculate_risk'] },
    { trigger: 'payment_failed', actions: ['notify_client', 'update_status'] }
  ],
  access_control: {
    roles: ['admin', 'manager', 'analyst'],
    permissions: {
      'deal_creation': ['admin', 'manager'],
      'risk_calculation': ['analyst']
    }
  },
  trace_storage: {
    retention_policy: '7y',
    encryption: 'AES-256'
  }
}

This approach allows independent development of the interface layer and systems of record, while keeping business logic stable. The key benefit: quick response to market changes without overhauling the entire system.

The Future of Enterprise Software

Forecasts point to accelerating trends. By 2028, expect:

• SaaS companies' market share to drop to 40%
• Private AI startups to capture 65% of total investments
• New standards for context management systems

The critical question: who owns the context layer—the company itself or the AI solution provider? The answer depends on the industry and knowledge centralization. In highly regulated sectors (finance, healthcare), companies will retain control, while other sectors will be dominated by independent platforms.

Main takeaway: context truly is king. Those who master managing this layer first will gain a strategic edge in the new software economy.

— Editorial Team