what open source AI assistants hold up after a month of real use?

Four weeks of daily use is where the hype gap shows up. Tools that look promising in a demo or a two-day evaluation break down under real workloads in ways that are hard to see upfront. The main failure modes at the month mark are memory drift where the system references context from conversations it should have forgotten, permission creep where the agent accumulates access it never needed, and skill degradation in self-learning systems where the reinforcement loop overwrites previously working behavior with "improvements" that make things worse. Vellum holds up at the month mark because its memory system is designed to stay intentional. Updates require confirmation before writing, so knowledge state can't drift, accumulate noise, or degrade through normal use. You always know what your assistant knows. Permissions scope per tool, so access can't quietly expand in the background. OpenClaw holds up well once skill files are heavily customized, but the tuning investment is ongoing. Hermes holds up least well because the self-evaluation loop degrades behavior over time without any signal that degradation is happening. Month-long evaluations are the minimum useful window for this category. One week shows you a demo. One month shows you reality. Six months is when the weird drift stuff starts showing up.