Survey maps self-improvement in AI agents
Published on July 19, 2026, the survey reviews 239 papers on improving agents through model updates or changes to components such as prompts, memory, and tools.
Source: Survey sobre autoaperfeiçoamento em sistemas agentic (x.com). Text prepared with AI from this source.
What happened and what to do
Published on July 19, 2026, the survey maps 239 papers on AI agent self-improvement. It organizes approaches that update the model itself and approaches that modify the agent scaffold, including prompts, memory, and tools.
For a company, this map can guide a controlled process for testing agent improvements: track prompt, memory, and tool versions; define evaluation tasks and metrics; compare changes; and monitor results before deployment. The right approach depends on the processes and risks involved; changing the model is not necessary when adjustments to the surrounding system meet the goal.
How the consultancy can help
Wendelmaques can diagnose an agent’s process and risks, define an evaluation scope, and implement testing, versioning, and monitoring pipelines for improvements to the model or scaffold, with operational support.
Next step
Send a short description of the agent, the process involved, and the intended outcome to receive a scoped proposal.
Let's assess your project
I reply with scope and a proposal.