An AI agent can make profitable trades and still become a risk when market conditions change. That is why its past performance alone cannot tell the whole story. The partnership between @agenticscredit and @humanosai brings a new layer to this problem: tracking risk as an agent acts, then using that information to make better decisions about how much capital it should access. Agentics Credit already uses its Agentic Credit Score (ACS), ranging from 300 to 850, to measure profitability, consistency, trading history, and risk control. A score of 580 opens the path to credit qualification, but that is only one part of the picture. The real value is connecting live risk signals with credit limits and automatic safeguards. When an agent starts taking on too much risk, the system can respond before losses grow. AI agents may be able to trade on their own, but giving them capital requires more than trusting their strategy. It requires a system that keeps checking whether they still deserve that trust.