AI Agent Development Frameworks: Our Takeaways from Latest Gartner Innovation Insight Report

As artificial intelligence continues to reshape software engineering, AI agent development frameworks are emerging as a cornerstone for building autonomous, intelligent systems.

The August 2025 Gartner® report, Innovation Insight: AI Agent Development Frameworks analyzes this evolving space, explaining the drivers behind rapid adoption, the benefits and use cases of these frameworks, and how organizations can choose the most suitable technologies for their needs. Below are our takeaways of this research, but we’d encourage you to read the report for yourself.

The Role of AI Agent Development Frameworks

Building AI agents from scratch can be a daunting task. It involves orchestrating models, managing memory, integrating tools, and ensuring secure decision-making. The definition of AI agent development frameworks by Gartner aptly describes their purpose:

AI agent development frameworks are designed to accelerate the creation of AI agents and AI-powered applications capable of autonomously performing complex tasks by providing high-level abstractions for orchestration based on AI models, while also offering low-level control over agent logic (prompts, context, orchestration), memory, planning, and API access.

Key capabilities abstracted by these frameworks include planning and reasoning (breaking down goals into steps), memory management (maintaining context and accessing knowledge), tool use (interacting with external systems), managing the action/observation loop (the core cycle of agent operation), and coordinating multiple agents (mainly within a single codebase).” ^*

Key Features and Components

As the image from Gartner below shows, we believe modern AI agent development frameworks should include the following core components:

• Orchestration engines to plan, manage and execute multi-agent workflows to achieve the required objective(s).
• Visual editors for designing multiagent systems
• Model Integration/LLM connectors for flexible model integration
• Built-in tools for retrieval-augmented generation (RAG), code execution, and external system/API access
• Observability and monitoring tools for transparency, debugging and performance tracking
• Evaluation (testing) platforms for testing agent behavior

Source: Gartner “Innovation Insight: AI Agent Development Frameworks”, 27 Aug 2025, Tigran Egiazarov, Arun Bathu, Gary Olliffe, Jim Scheibmeir, Arun Chandrasakaran, Adrian Leow

In Table 1 of the report, Gartner provides a list of sample frameworks from 8 mentioned vendors including Solace.

Benefits and Risks

AI agent development frameworks can offer several advantages:

• Simplification and abstraction: Allowing developers to focus on core logic rather than infrastructure.
• Flexibility and control: Pro-code environments can allow for deep customization.
• Enhanced developer productivity: Standardized practices and tools can enhance developer productivity.
• Integration capabilities: Agents can autonomously interact with an organization’s internal APIs and systems of record, as well as with other agents, potentially built on other platforms.

Despite their promise, we believe these frameworks may also pose challenges:

• Security vulnerabilities: Prompt injection and data exposure risks require manual safeguards.
• Rapid evolution: Frequent updates can lead to technical debt and instability.
• Limited UI support: Most frameworks lack built-in UI components.
• Language limitations: Python dominates, requiring API-based integration for other languages.
• Nondeterministic behavior: AI agents can be unpredictable, complicating compliance and reliability.

Organizations must invest in AI-specific skills, including prompt engineering, Python proficiency, and API security.

Strategic Recommendations

Gartner advises software engineering leaders to^*:

• Start small: “Start by building and deploying single-agent solutions for well-defined, low-risk tasks. These initial implementations allow for manageable experimentation and learning. Avoid limiting yourself to frameworks that only support distributed multiagent systems — these systems are few, complex and rarely necessary for initial use cases.”
• Choose strategically: “Opt for frameworks that offer a robust ecosystem, comprehensive tool coverage and memory capabilities.”
• Treat advanced features as optional: “Advanced capabilities add significant complexity and security risks. Only adopt these if your use case clearly requires them and your team has the necessary expertise and controls.”
• Build a strong foundation: ”Invest in composable application architecture with an API-first approach and AI-ready data, ModelOps, and sound data governance. These elements are crucial for supporting adaptable agent behavior and integration into your application architecture.”
• Develop new skills: ”Address skill gaps in software engineering teams and enhance security knowledge by investing in AI-specific development practices, such as prompt engineering and understanding AI workflows. While those skills are evolving and need continuous uptraining, they should be scalable across teams. Be mindful of the complexity and potential cost implications associated with intricate, distributed multiagent systems.”

Market Outlook

Gartner predicts that “by 2028, 80% of organizations will report that AI agents consume the majority of their APIs, rather than developers.” ^* We feel this marks a fundamental shift in how software systems are built and operated.

AI agent development frameworks are not just tools, they’re enablers of a new paradigm in software engineering. As organizations race to embed intelligence into their applications, these frameworks will become essential for delivering scalable, secure, and autonomous solutions.

Click here to read the entire report, along with all of Gartner expert’s insights around these platforms.

^*Source: Gartner “Innovation Insight: AI Agent Development Frameworks”, 27 Aug 2025, Tigran Egiazarov, Arun Bathu, Gary Olliffe, Jim Scheibmeir, Arun Chandrasakaran, Adrian Leow.

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