How to Migrate Between AI Agent Frameworks
Framework migrations fail for two reasons: teams underestimate the scope of what needs to change, and teams try to migrate everything at once instead of incrementally. The scope issue is common because agent systems have more surface area than they appear. Beyond the agent logic itself, there are tool integrations, prompt templates, state schemas, error handling patterns, monitoring dashboards, deployment configurations, and operational runbooks that all reference the current framework. Missing any of these during planning means discovering them during execution, which delays the migration and introduces risk.
Step 1: Audit Your Current System
Before writing any migration code, document every component of your existing agent system. This audit serves as both a migration checklist and a specification for the target implementation.
Document every agent with its system prompt, model configuration, tool list, and any framework-specific settings. Document every tool with its name, description, parameter schema, and implementation. Document every state schema showing what data flows between agent steps. Document every integration point where the agent system connects to external services, databases, or APIs. Document every prompt template with its variables and the contexts where it is used.
Also document operational components: monitoring dashboards and alerts, deployment scripts and configurations, logging formats and destinations, error handling and recovery patterns, and any custom middleware or extensions built on top of the framework. These operational components are easy to overlook during planning and expensive to rebuild under time pressure during execution.
The audit typically reveals that the system is larger than expected. A "simple" agent system with three agents and ten tools often has 50+ distinct components when you count prompts, schemas, configurations, and operational infrastructure. Knowing the true scope before starting prevents the mid-migration discovery of unplanned work that derails timelines.
Step 2: Build an Abstraction Layer
Before migrating framework-specific code, create abstraction interfaces that separate your business logic from the framework. This layer serves two purposes: it makes the migration incremental (you can swap framework implementations behind stable interfaces without changing business logic), and it protects you from future migrations (if you need to change frameworks again, only the abstraction layer implementation changes).
The key interfaces to abstract are tool definitions (a common format for defining tools that can be translated to any framework's tool format), agent execution (a common interface for running an agent with inputs and receiving outputs), state management (a common interface for reading and writing agent state, independent of how the framework persists state), and observability (a common logging and tracing interface that maps to framework-specific tracing systems).
Implement these interfaces for your current framework first. This step is a refactoring of your existing code, not a migration, so you can validate that the abstraction layer works without changing any behavior. Run your existing test suite against the abstracted code to verify that everything still works. Only after the abstraction layer is validated should you begin implementing it for the target framework.
Step 3: Implement in the New Framework
With the abstraction layer in place, implement each interface using the target framework's APIs. Start with the simplest agent and work toward the most complex. This progression lets you learn the target framework's patterns on easy problems before tackling difficult ones.
Migrate tools first because they are the most portable component of any agent system. Tool logic (the actual code that executes when a tool is called) is framework-independent. Only the tool registration format changes between frameworks. If your abstraction layer defines tools in a common format, migrating tools means writing a translator from your common format to the target framework's tool registration API.
Migrate agents next, starting with single-agent workflows and progressing to multi-agent systems. Each agent migration involves translating the system prompt (usually unchanged), configuring the model and parameters (framework-specific settings), registering tools (using the already-migrated tool definitions), and implementing state management (using the abstraction layer). Test each migrated agent against the same inputs that your production agents handle, comparing outputs to verify behavioral equivalence.
Migrate workflows last because they depend on agents and tools being functional. Workflow migration involves translating the execution flow (sequential steps, conditional branches, parallel paths) from the source framework's representation to the target framework's representation. This is typically the most framework-specific part of the migration and requires the most rewriting.
Step 4: Run Both Frameworks in Parallel
Deploy the new implementation alongside the old one and route a percentage of production traffic to the new system. Start at 5-10% and increase gradually as you gain confidence. Compare outputs, latency, error rates, and costs between the two systems.
Parallel running catches problems that testing alone cannot find. Production traffic includes edge cases, unusual inputs, and failure modes that test suites do not cover. Running both systems on the same traffic lets you identify these problems with a small blast radius (5-10% of requests) rather than discovering them after a full cutover.
Define specific criteria for increasing traffic to the new system: error rate must be equal to or lower than the old system, latency must be within 20% of the old system, output quality must match the old system as measured by a defined quality metric, and no new types of errors that the old system does not produce. If any criterion is not met, investigate and fix before increasing traffic.
Step 5: Cut Over and Decommission
Once the new system has handled 100% of traffic for at least one week without degradation, begin decommissioning the old system. Keep the old implementation available but inactive for two to four weeks as a rollback option. After the rollback period expires without issues, remove the old framework code, dependencies, and configuration.
Update all operational artifacts: monitoring dashboards, alerting rules, deployment scripts, runbooks, and documentation. These artifacts reference framework-specific concepts and need to reflect the new framework. Leaving old references in operational documentation causes confusion during incidents when operators follow outdated procedures.
Migrate incrementally through an abstraction layer, validate with parallel running before full cutover, and budget two to three times your initial estimate for the total effort. Framework migrations are always larger than they appear because agent systems have more surface area than the agent code alone.
When Not to Migrate
Not every framework limitation justifies a migration. If the limitation is a missing feature that you can build on top of the current framework, building the feature is almost always cheaper than migrating. If the limitation is performance, verify that the bottleneck is the framework and not the model provider or your infrastructure before committing to a migration. If the limitation is a missing integration, check whether a third-party library or Composio can add the integration without changing frameworks.
Migrate when the current framework's architecture fundamentally does not support your workload (a single-agent framework when you need multi-agent coordination), when the framework is abandoned with no maintenance activity, or when organizational requirements mandate a specific vendor or compliance certification that the current framework cannot provide. These are structural reasons that cannot be solved by adding features or integrations.