Self-improvement in agents: making adaptation controllable
A survey published on July 16, 2026 examines modern agentic systems as foundation models integrated with prompts, memory, and tools. Its system-level view helps identify where updates happen and how to make them controllable.
Source: Uma survey sobre autoaperfeiçoamento em sistemas agentic modernos (arxiv.org). Text prepared with AI from this source.
What happened and what to do
The survey, published on July 16, 2026, defines modern agents as foundation models connected to operational scaffolds such as prompts, memory, and tools. It frames self-improvement as adaptation that turns experience into accumulated capability gains. Its system-level perspective helps locate where updates may occur and consider how to control them.
A company could apply this approach by mapping its agents’ components, recording changes to prompts, memory, and tools, and monitoring their effects on tasks and quality criteria. Those records can support reviews, tests, and limits that make adaptation observable and governed, without assuming every process needs additional AI.
How the consultancy can help
Wendelmaques can diagnose how your agents use prompts, memory, and tools, identify adaptation risks and opportunities, and propose a scoped implementation of monitoring, testing, and controls. The engagement can include operating the solution, with scope defined for your environment.
Next step
Send a brief description of your agent or adaptation process to receive a scoped proposal for diagnosis and implementation.
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I reply with scope and a proposal.