It took me a long time to finally deploy my @ openclaw Agent, give it commands, write code automatically, and experience bug fixing. It was really enjoyable, but after the excitement, I believe everyone should be anxious again when they look at the token consumption bill in the background. Because the shift from pure AI dialogue to localized super privilege agent paradigm will inevitably be accompanied by an exponential increase in computing power consumption. Don't expect your agent to actively save you money, especially before you have fully "mastered" it. What should we do? I have seen many friends share a set of solutions provided by @ dgrid_ai, and I would like to share some opinions: 1) Agents are actually very picky eaters, especially coding agents like Opencalw. In order for them to perform at their best, they have to meet some of their preferences, such as writing code with Claude Sonnet 4.5 and then using GPT-5 for logical reasoning. They may also use Gemini's Nano Banana to generate graphs, which means we need to provide them with a bunch of accounts and API keys at the same time. The first pain point that DGrid AI hits is the 'Unified Access Layer'. It can be understood as OpenRouter for Web3, which connects over 200 mainstream models in the backend. When developers deploy Openclaw, they only need to configure a DGrid API Key to switch models freely like using a "universal socket". It should be noted that this is not simply API forwarding, DGrid introduces Smart Router (Intelligent Scheduling) and PoQ (Proof of Quality) algorithms. When the agent initiates a request, the decentralized routing network automatically matches the optimal model and verifies the response quality. This is equivalent to adding an "intelligent scheduling valve" between the Agent and the large model, which ensures execution quality and simplifies the development configuration process. 2) The reason why DGrid thinks this business is promising is because after calculating the cost, especially since you are a heavily domesticated agent user, using a purely traditional SaaS subscription model is actually very uneconomical. Assuming that you want to maintain subscriptions to flagship services such as OpenAI Pro, Grok Heavy, Gemini Ultra, Claude Max, etc. at the same time, the explicit cost per year may reach tens of thousands of dollars. DGrid has developed a Premium Pass gameplay, which costs approximately $1580 in the first year, but is equivalent to a monthly model token consumption limit of $300, which is worth $3600 per year. For users who need to configure the aforementioned models at the same time, this not only meets their needs, but also amounts to a 30% discount. This account is very Make Sense for deployers like Openclaw who are "big spenders on tokens". above The reason why DGrid is said to be a web3 version of OpenRouter is that it must have a lot of web3 gameplay and activities, such as the "earn while using" model for paid users, and activities such as unpaid users participating in AI Arena to earn points. I won't go into detail here. Interested friends with needs can go and learn more. However, the prerequisite is to ensure that you are a heavy user of Openclaw first. If you just want to deploy an experience for fun, don't spend money on it yet. (For novice users, use domestic models like Zhipu to transition first, which is very cheap.) When you are sure that your "digital employees" can do a lot of work for you, it is not too late to increase investment.