aizensou

The 'Super Self-Improving Multi-Agent Framework' for your Hermes or OpenClaw agent. The article below outlines how Hermes can watch over your Openclaw agent, so this example uses Hermes as the main agent. This idea is interchangeable based on preference. How it works: Agent 1 (Hermes) - The main agent: who operates your workflows, and who you have in the top hierarchy of agents. For simplicity, it also runs the workflows using its persistent memory and self-improving skills. Agent 2 (Hermes) - Main's Supervisor agent: who monitors the entire system, reading operations and failure logs, searches for bugs, solutions, then brings them to... Agent 3 (OpenClaw) - External Supervisor agent: who also monitors the Hermes system, and searches for issues and solutions. Multiple times per day, Agent 2 audits the system, finds errors, stale jobs, etc, proposes a fix, then tags Agent 3. Agent 3 audits the system, reads Agent 2's summary, and verifies the problem and solution. Together, they go back and forth in a dedicated channel until they find a coded solution to the problem. If it's a low-risk fix, it auto-fixes it. If it's high-risk, it's raised to Agent 1 for approval via the owner (me). The first goal is never to have to worry that the system is operating correctly. The second goal is to have two separate agents focused on recommending improvements to the system. Ideally, there are no bugs to fix, and you can have them focus on making meaningful improvements to your workflows over time. This is the basic workflow for monitoring, but you can extrapolate this framework to many more use cases. What's [redacted]? I'm cooking up something to continue working toward my goal of building more sentience in my agents. I will share more soon. Let me know in the comments if this works for you. I'll create a fleshed-out article if you are interested.

We firmly believe there are ongoing US-Iran "peace deal" talks right now: Why? Because we have seen this EXACT sequence of events MULTIPLE times in previous deals negotiated by President Trump. In fact, the May 2025 China trade deal followed the exact same timeline. On April 24th, 2025, just 15 days after the "90-day tariff pause," which also came as the 10Y Note Yield soared above 4.45%, President Trump made similar claims about China, and China responded like Iran just did. Trump said China was interested in a "trade deal" with the US, and China responded stating that "there are absolutely no negotiations between the US and China." Just 3 weeks later, on May 12th, 2025, the US and China announced their first trade deal, reducing tariffs to a 30% baseline. We believe a similar situation is happening right now with Iran, behind closed doors. As Iran's war strategy has become to play the “long game” and pressure the US/Israel through capital and energy markets, Iran does not want to lose leverage and allow markets to normalize until a definitive deal has been solidified. This is the same exact form of leverage that China had in April 2025 negotiations, which they initially denied, as the 10Y Note Yield broke above 4.50% and US equity markets collapsed. We believe Trump is following the same playbook now. That said, volatility will persist until there is a clear agreement in place, and broader market normalization after this historic shock will take months. Pattern-based trading has become incredibly profitable over the last 12 months, and we continue to update our models as a result. Bookmark this post. Keep following the patterns.

The Iranian Foreign Ministry, now confirming Iranian media reports, that there have been no talks with Trump.

Just spent $500 in compute vibe coding my own Civilisation RPG but with unbounded natural language diplomacy.. meet Uncivilised. ask me anything.

Very good framework to prepare for what's coming in the market.

$BTC macro-cycles: 2015–2017 bull: 12 Jan ’15 -> 11 Dec ’17 (1064 days) 2017–2018 bear: 11 Dec ’17 -> 10 Dec ’18 (364 days) 2018–2021 bull: 10 Dec ’18 -> 8 Nov ’21 (1064 days) 2021–2022 bear: 8 Nov ’21 -> 7 Nov ’22 (364 days) 2022–2025 bull: 7 Nov ’22 -> 6 Oct ’25 (1064 days)