My friend is doing analysis at an investment research institution and complains every day about too many tools: ChatGPT is responsible for Q&A, Perplexity checks information, Notion keeps records, and finally requires manual integration. He said, "I don't need ten AI, I just need one AI that can do the job This reminds me of @ SentientAGI's GRID+Spaces. It encapsulates multi-agent collaboration into a unified network, Generate complex tasks such as research, planning, and reporting with just one click. The siege lion believes that this is the true "AI engineering"—— It's not about having one more model, it's about multiple models working together. 1/ Recently, I saw the latest updates posted by @ SentientAGI: The GRID module has been upgraded again, and the Spaces feature has been officially launched. The transition from laboratory models to the application of open AGI networks is a critical turning point. Siege Lion believes that this upgrade is not just a "functional update", but a paradigm shift for the entire open-source AI ecosystem. 2/ Let me briefly explain its actions: After the upgrade of GRID, it can unify the scheduling of multiple agents, models, and data sources; Spaces is the user interface that can transform complex tasks into structured results, such as research reports, market analysis, and itinerary planning; The open network is moving from "whitelist testing" to "real user scenarios", which is a signal from concept verification to ecological implementation. 3/ Many people ask: What problem is Sentient really solving? The siege lion summed up in one sentence: Open source models are "usable but not profitable", and Sentient wants it to be both open-source and sustainable. In the past, once models trained by open-source developers were uploaded, they were modified, nested, and commercialized, while the original creators did not receive any revenue. Sentient utilizes OML fingerprint mechanism and encrypted audit protocol to give the model true "digital property". 4/ The siege lion believes that Sentient's three-layer logic is particularly noteworthy: ① OML protocol layer: Establish model ownership, validate calls, and allocate benefits. ② GRID intelligent network layer: aggregates multiple agents and data sources to form ecological collaboration. ③ Spaces user layer: allows ordinary users to use and combine AGI without needing to understand technology. The cleverness of this structure lies in its retention of "openness" while introducing "sustainable incentives". 5/ The siege lion is more concerned with its "engineering philosophy": While others are working on large models and closed source APIs, Sentient is working on the "protocol layer" and "trust mechanism". The future of AI is not just about who has more parameters, but also about who can make model collaboration traceable, profitable, and governed. This is the truly open ecosystem that can run smoothly in the long run. 6/ Of course, the siege lion also needs to pour some cold water: The stability of OML fingerprints under multiple rounds of retraining still needs to be verified; The implementation cost of TEE framework is high, and it is not suitable for all developers in the short term; The community governance system has just begun and has not yet fully prevented the problem of "whale control". But this precisely indicates that it is still on a path of "prototype first, standard later". 7/ Siege Lion believes that Sentient's strategy is more comprehensive than most "decentralized AI projects". It is not a computing market, nor a single model platform, but the underlying economic structure of open AI: Model → network → users → revenue distribution → governance, this is a closed loop. 8/ Summary in one sentence: If OpenAI is the 'enterprise version AGI', then Sentient wants to do the 'human version AGI'. In this era dominated by a few giants, Sentient's attempt seems to be opening up another path to the future. The siege lion is uncertain whether it will ultimately succeed, but what is certain is that it represents a direction worth taking seriously.