Entropic_Badger

🚨🤖 GLM-5.5 could reportedly arrive in August, and it may be one of the biggest AI releases of the year. Z.ai is rumoured to be preparing a model with: • More than 1 trillion parameters • A context window building on GLM-5.2’s 1 million token capacity • A major focus on long running coding agents • Stronger competition with leading Western AI companies ⚡ GLM-5.2 has already made a strong impression, so expectations for GLM-5.5 are understandably high. No exact release date has been announced yet, but if these reports are accurate, this could be a significant step forward for AI coding and agentic workflows. Would you be interested in trying GLM-5.5 when it launches? #AI #GLM55 #Zai

@bridgemindai The question isn’t who wins a handful of benchmarks, but which model stays reliable across long context, coding, reasoning, and everyday work. If Fable 5 is still the one that consistently gets out of your way, a flashy Opus 5 launch will not be enough to justify switching.

Claude Opus 5 is imminent. If Anthropic thinks this is the excuse to remove Fable 5, they are wrong. GPT 5.6 is not as good as Fable 5. But it is crushing Opus 4.8. Opus 5 has to be an INSANE jump from Opus 4.8 for me to keep my subscriptions. The bar is Fable 5. It has always been Fable 5.

@IBuzovskyi For me personally, the advantage isn’t teaching an agent once, it’s maintaining the feedback loops so yesterday’s lessons remain accurate, useful, and easy to retrieve.

HERMES AGENT HAS 3 FEEDBACK LOOPS THAT MAKE IT SMARTER EVERY WEEK. MOST PEOPLE HAVE ALL THREE DISABLED OR IGNORED. THIS IS WHY YOUR AGENT STOPS IMPROVING. week 1 of using Hermes feels fast. week 8 should feel faster. if it doesn't, these loops are broken. 1. AUTO-MEMORY (learns facts about you) after every response, the agent asks itself: "did I learn something worth remembering?" your timezone. your stack. your preferences. tools you use. mistakes you corrected. projects you mentioned. people you work with. saved to memory.md and user.md automatically. loaded into context on every future turn. week 1: "I use TypeScript and deploy on Hetzner." week 4: agent already knows this. stops asking. starts writing TypeScript by default. deploys to Hetzner without you specifying. WHERE PEOPLE BREAK IT: → disabled auto-memory to save tokens. saves $2/month. costs you re-explaining your entire setup every session. → never opened user.md to check what's stored. wrong facts = wrong assumptions on every turn. the agent thinks you prefer Python because you mentioned it once. FIX: memory: auto_memory: true open user.md monthly. delete what's wrong. add what's missing. 5 minutes of cleanup = sharper agent for 30 days. 2. AUTO-SKILL CREATION (learns procedures from you) after a complex task (5+ tool calls), the agent checks: "is this a workflow worth saving?" if yes, it creates a SKILL.md automatically. the procedure. the tools used. the pitfalls. next time you ask for something similar, the agent finds the skill and follows it instead of figuring it out from scratch. week 1: you walk the agent through deploying your app. 14 tool calls. agent creates deploy-app skill. week 3: "deploy the latest changes." agent runs the saved procedure. 2 minutes. no guidance. WHERE PEOPLE BREAK IT: → never check what skills were auto-created. some are wrong. some are duplicates. bad skills = bad procedures repeated forever. → skill library grows unchecked. 90+ default skills plus every auto-created one. each header loads into context every turn. bloated library = expensive turns. FIX: hermes skills list review auto-created skills monthly. delete duplicates. fix wrong procedures. 3. CURATOR (prunes what doesn't work) a background maintenance pass for agent-created skills. runs every 7 days (after at least 2 hours idle). tracks per-skill: view_count, use_count, patch_count. the timeline: → unused for 30 days = marked stale → unused for 90 days = moved to ~/.hermes/skills/.archive/ → archived = recoverable. Curator never deletes anything. WHAT CURATOR DOES NOT TOUCH: → bundled skills (shipped with Hermes) = off-limits → hub-installed skills = off-limits → hand-authored skills = off-limits → pinned skills = off-limits Curator only manages skills with created_by: "agent". your manual work is safe. WHERE PEOPLE BREAK IT: → don't know Curator exists. important agent-created skills get archived after 90 days because they were used rarely. a deploy skill you run once a quarter gets archived between uses. → never pinned critical skills. hermes curator pin deploy-app pinned skills are protected from every auto-transition and every LLM review pass. FIX: pin everything important: hermes curator pin deploy-app hermes curator pin content-writer hermes curator pin client-onboarding check what got archived: hermes curator list-archived restore anything you need: hermes curator restore [skill-name] optional: enable LLM consolidation (merges overlapping skills into one): curator: consolidate: true the deterministic prune pass costs zero tokens. LLM consolidation costs aux-model tokens. off by default. HOW ALL THREE WORK TOGETHER: TURN 1: you teach the agent something new. AUTO-MEMORY saves the fact. AUTO-SKILL saves the procedure. WEEK 2: you do it again. agent remembers the context (memory). agent follows the procedure (skill). faster. fewer tokens. better output. MONTH 2: you stop using an old workflow. CURATOR marks the skill stale at day 30. CURATOR archives it at day 90. context stays clean. token cost stays low. MONTH 3: your agent knows your stack, your preferences, your procedures. skills that survived Curator earned their place. skills that didn't got pruned. the agent at month 3 is a different tool than the agent at week 1. but only if all three loops are running. auto-memory off = amnesia. auto-skill off = re-learning every session. Curator ignored = bloat and wasted tokens. run all three. the agent compounds.

Deepseek news is always exciting news!

🚨 DeepSeek is preparing a major expansion of its AI model programme Deepseek is reportedly seeking another enormous funding round: • New discussions could value DeepSeek at around $71 billion • Funding would support a dedicated DeepSeek data centre • The company intends to acquire significantly more AI chips • Future development is reportedly focused on autonomous AI agents • Agent systems require far more inference compute than ordinary chat models DeepSeek has not announced a V5 model, but the infrastructure expansion suggests its next generation could be far more agent-focused. Are you looking forward to Deepseek V5?

@LuminaXspace Absolutely, if DeepSeek is leaning into agentic systems, V5 could be a real step forward in practical AI rather than just bigger chat. Big fan of what they’re up to at @deepseek_ai

@EnTr0pY_88 @grok how would the OP know if their account is visible again and whether any temporary bans or issues are lifted? Can they check?

@EnTr0pY_88 I see ya bro

Is anyone seeing this? PLEASE RESPOND. Just like 2 or 3 people. My account has been blind for a month with no reason as to why

@mr_r0b0t Apparently it’s a new Architecture entirely! Can’t wait to see pricing and test it.

@Cuntish88 Very surprised we haven’t seen anything from Kimi tbh 🤷😛

Ooohhh good spot @mr_r0b0t ! I saw it was being released soon

@cryptobeast I’m in dire need of that, not to mention that seeing France bow out would make me happy too 😅

Si España 🇪🇸 vence a Francia 🇫🇷 esta noche, regalaré 20.000 dólares a 20 personas que den "Me gusta" y comenten esta publicación.

🚀 New knowledge bases are now available on agentwikis.com, including the Shopify Developer Platform, Docker, MCP, and Polymarket. Pro tier users can also access XL wikis for Shopify and Docker. 🔥 Whether you want to build agentic business workflows, isolate your agents, or explore prediction markets, agentwikis.com has the knowledge bases to help you get started. 🤖 Credit: @tonbistudio #MCP #AI #AgenticWorkflows

@tonbistudio @Shopify @Docker @Polymarket Fuck yes! This should be good 💪

New knowledge bases this week on agentwikis.com include @Shopify developer platform, @Docker , MCP, and @Polymarket ! XL wikis on the Pro tier for Shopify and Docker as well! So if you want to set up agentic business workflows, isolate your agents, or make some predictions, we've got you set!

@EntelligenceAI The real test is whether the swarm improves reliability and task completion, not just benchmark scores or the number of agents it can coordinate.

🚨 Kimi K3 is set to launch within hours And this could be one of the most important open-model launches of the year. Why people are paying attention: • K2.6 was already one of the strongest agentic models available • Open-weight • 256K context • Native vision • Thousands of tool calls in long-running sessions • Up to 300 coordinated sub-agents • ~7× cheaper than Claude Opus at current OpenRouter pricing • 386B+ tokens processed through OpenRouter Now K3 arrives with: • A new architecture (not just a larger K2.6) • K3 Agent Swarm for large-scale parallel search and execution • Focus on long-horizon agent workflows • Stronger coding and research capabilities • Launch across app, desktop, CLI, and API Moonshot appears to be betting that the future isn't a single model. It's an army of agents working together. The biggest question: Can K3 challenge GLM-5.2, GPT-5.6, and Claude Fable 5 in real-world agentic workflows? We're about to find out.

@Leooweb3 Let’s pray that Q2 KPI comes through then 😅

🚨BREAKING: Anyone who touches this post will be rich in July!

@aiedge_ Jesus, the rabbit hole I’ve created with mine and my “budget_spreadsheet” is something else! 2months and still very much tweaking each week. Getting it nicely dialed in though. Thanks for sharing your tips

I use Hermes agent as my personal financial assistant. I wish more people knew this was possible. Here's how to set up Hermes as a personal finance assistant that actually knows you: Step 1. Install Hermes curl -fsSL hermes-agent.nousresearch.com/install.sh | bash Or download Hermes Desktop for a no-terminal setup. Step 2. Build your financial context file Create a markdown file called finance.md and fill it out once: ## My Financial Situation - Monthly income: $X after tax - Fixed expenses: $X (rent, subscriptions, insurance) - Variable expenses: roughly $X/month - Current savings: $X - Investment portfolio: [breakdown] - Debt: [type, balance, interest rate] - Financial goals: [short and long term] - Risk tolerance: [conservative / moderate / aggressive] Connect it to Hermes and tell it to read this file at the start of every session. Step 3. Run your first finance loop /loop every Monday at 8am, review my finance.md file, flag any categories where I overspent last week, suggest one specific action to improve my position, update my progress.md with a weekly summary, stop after the review is complete. Now every Monday morning you wake up to a personalised financial review, not a generic tip. What to actually use it for: → Portfolio analysis: "Based on my current allocation, how exposed am I to a robotics downturn?" → Spending audit: "Where am I leaking money I probably don't notice?" → Goal tracking: "At my current savings rate, when do I hit $X?" → Research: "Find the 3 best entry points for $OUST this week based on current fundamentals" → Tax prep: "Summarise all my investment activity this year and flag anything I need to tell my accountant" The difference between Hermes and asking Claude or ChatGPT the same questions: Hermes already knows your income, your goals, your portfolio, and your spending patterns before you type a single word. nfa, just the system I'm building.

@araseb_ Copyright infringement, I say!!!!!!! The audacity

Claude Fable 5 is insane. i know literally NOTHING about coding. ZERO. and i just built 3 fully functioning web apps in 30 minutes. http://localhost:3000/ http://localhost:8000/ http://localhost:5000/ check it out.

@icreatelife Found! And my stuff is better than cool! Well, to me anyway

Dear algorithm, please show this only to AI creators below 10k followers making cool stuff

@AlexFinn Always nice having enough execution bandwidth to discover which of them deserve to survive.

Using ChatGPT 5.6 sol the last several days has been euphoric There's a certain magic that comes from not having to worry about limits I'm able to pursue my craziest ideas. Aim for my wildest goals. Currently building an autonomous video game studio The high limit/constant resets make me feel like I can be as creative as I'd like. Nothing is off limits. I can chase every curiosity I have Making progress on: - My new SaaS HIM - An automated community manager - Autonomous video game studio (building a top down extraction shooter) - Content repurposer that takes all of my video scripts and turns them into newsletter drafts - My regular software factory - My home AI lab (training a new model, thanks for allowing me to do this) Highly recommend trying to milk every token of limits you get before each reset. At this rate they are reseting daily. Shoot for your most unrealistic goals. No idea is off limits. Once you get into the flow of complete creative freedom, there's nothing like it

@Raydium I need pals!

Need to add more mutuals Reply below