Furkan Ermağ Blog

Etiket: AI Orchestration

  • Cross-Functional Super Agents Will Emerge in 2026 AI Landscape

    Cross-Functional “Super Agents” Will Emerge in 2026 AI Landscape

    “We’ve moved past the era of single-purpose agents,” says Chris Hay, Distinguished Engineer at IBM. In 2024, agents were small and specialized: email writer, research helper. But now, with reasoning capabilities, agents can plan, call tools, and complete complex tasks. In 2026, we’re seeing the rise of what I call ‘super agents’.”

    From Specialized to General-Purpose

    The evolution from single-purpose agents to super agents represents a fundamental shift in AI capabilities. Where previous AI agents could handle one specific task—like writing emails or summarizing documents—super agents can coordinate across multiple functions and tools.

    Hay predicts that “in 2026, I see agent control planes and multi-agent dashboards becoming real. You’ll kick off tasks from one place, and those agents will operate across environments—your browser, your editor, your inbox—without you having to manage a dozen separate tools.”

    Cross-Environment Operation

    One of the defining characteristics of super agents will be their ability to operate across different environments. This means:

    • Browser automation: Agents can navigate and interact with websites
    • Document editing: Direct manipulation of files in your editor
    • Communication: Reading and writing emails and messages
    • System integration: Connecting to APIs, databases, and internal tools
    • Workflow coordination: Managing multi-step processes across different applications

    Adaptive User Interfaces

    Forget static software in user experience and user interface. Hay predicts we’ll see interfaces and apps that can adapt to any scenario, making every user an AI composer. This means software that reshapes itself based on context, task, and user preferences.

    We’ve moved past the era of single-purpose agents. In 2026, I see agent control planes and multi-agent dashboards becoming real.

    — Chris Hay, Distinguished Engineer, IBM

    Every User Becomes an AI Composer

    The vision for 2026 is that everyone becomes an AI composer—someone who can orchestrate AI agents to accomplish complex tasks without needing to be a programmer or AI expert. This democratization of AI capabilities has profound implications:

    • Lower barrier to entry: More people can leverage AI power without technical skills
    • Increased productivity: Complex workflows that previously required teams can be managed by individuals
    • Empowerment: Non-technical users can build sophisticated automation
    • New workflows: Entirely new ways of working emerge when anyone can orchestrate AI

    The Control Plane Wars

    “Whoever owns that front door to super agent will shape the market,” Hay predicts. This means we’re likely to see competition for controlling the interface between humans and AI agents. The company that builds the most intuitive, powerful, and open platform for managing AI agents will have tremendous influence.

    Think of it like the operating system wars of the past—but for AI. The company that controls the AI OS for agents will have significant strategic advantage.

    Practical Impact

    For businesses and individuals, the rise of super agents means:

    • Centralized AI management: One place to coordinate all AI activities
    • Unified workflows: No more context switching between different AI tools
    • Scalable automation: Complex business processes can be automated end-to-end
    • Reduced technical debt: Less custom integration work needed as agents handle cross-platform tasks

    Looking Ahead

    The era of single-purpose AI agents is ending. In 2026, super agents that can work across environments, coordinate multiple tasks, and adapt to any scenario will emerge. This represents a significant step toward the long-promised vision of AI as a capable assistant that can genuinely help with complex, real-world work.

    The race to build the super agent platform is on. And the winners will shape how we all interact with AI for years to come.

  • Systems, Not Models, Will Define AI Leadership in 2026

    Systems, Not Models, Will Define AI Leadership in 2026

    In 2026, competition in AI will shift from building the best models to creating the best systems. According to Gabe Goodhart, Chief Architect of AI Open Innovation at IBM, “We’re going to hit a bit of a commodity point. It’s a buyer’s market. You can pick the model that fits your use case just right and be off to the races. The model itself is not going to be the main differentiator.”

    From Models to Orchestration

    What matters now is orchestration: combining models, tools, and workflows into cohesive systems. “If you go to ChatGPT, you are not talking to an AI model,” Goodhart explains. “You are talking to a software system that includes tools for searching the web, doing all sorts of different individual scripted programmatic tasks, and most likely an agentic loop.”

    This shift represents a fundamental change in how companies should approach AI. Rather than investing in building proprietary models, organizations should focus on integrating models into effective systems that solve real business problems.

    The model itself is not going to be the main differentiator. What matters is orchestration: combining models, tools, and workflows.

    — Gabe Goodhart, Chief Architect, AI Open Innovation, IBM

    Cooperative Model Routing

    In 2026, we’ll see more cooperative model routing systems. “You’ll have smaller models that can do lots of things and delegate to bigger models when needed,” Goodhart predicts. This approach offers several advantages:

    • Cost efficiency: Small models handle routine tasks, reserving expensive large models for complex queries
    • Speed: Faster responses for common use cases that don’t require full model capabilities
    • Flexibility: Easy to swap models in or out as better options become available
    • Reliability: If one model fails, the system can route to alternatives

    The Winner Takes the System Level

    “Whoever nails that system-level integration will shape the market,” Goodhart says. This means the companies that dominate AI won’t be those with the best individual models, but those with the most sophisticated systems for orchestrating and integrating multiple models, tools, and workflows.

    This has profound implications for AI strategy:

    • Platform thinking: Companies need to think like platform builders, not just model developers
    • Integration capabilities: The ability to connect AI systems with existing business infrastructure becomes critical
    • User experience: The interface between humans and AI systems becomes a key differentiator
    • Tooling: Building and maintaining the tools that AI agents use becomes more important than the models themselves

    Practical Implications

    For businesses, this shift means rethinking AI investment priorities:

    • Less focus on training: Training custom models becomes less important for most organizations
    • More focus on integration: Integrating existing models into business workflows becomes the priority
    • Tool development: Building the tools and connectors that make AI useful becomes crucial
    • System architecture: Designing robust AI systems that can route between models becomes a core competency

    The New Competitive Landscape

    In 2026, the companies that win will be those that build the best systems, not necessarily the best models. This democratizes AI in some ways—any company can access similar models—but raises the bar for system-level innovation.

    The era of model competition is giving way to the era of system competition. And the companies that understand this shift and invest accordingly will be the ones leading the next phase of AI evolution.