No-Code Agentist

Nous Research quietly shipped a free desktop app for their self-improving agent. It runs on your own machine. It is called Hermes. The agent that remembers you and gets better the more you use it. -> Runs agents toward goals you set, unattended -> Saves the workflows it learns as reusable skills -> Plug in Codex, a local model, or Claude Code on Max -> Built-in voice, local speech-to-text, free text-to-speech -> Persistent memory across every session, no starting from zero Free and open source. MIT licensed. Mac, Windows, Linux. Link in the comments.

In October 2025, a builder with 30 years of experience posted a Reddit thread about AI agent personalities. By late December, the repo had 938 stars and 51 agents. Cute side project. Today it has 124,000+ stars, 20,000 forks, and 232 agents. It's called The Agency. And it stopped being a prompt library months ago. It's an org chart. 16 divisions. Engineering. Design. Marketing. Sales. Finance. Security. Product. Testing. Legal-adjacent support. Even a Game Dev division split by engine — Unity, Unreal, Godot, Roblox. Each agent isn't "act as a developer." Each one ships with an identity, critical rules, workflows, deliverables with code examples, and success metrics. The roster gets weirdly, wonderfully specific: → A Whimsy Injector who adds "celebration animations that reduce task completion anxiety" → A Reality Checker who refuses to certify anything without visual proof → An Evidence Collector who defaults to finding 3-5 issues in your code → An Anthropologist and a Historian — for world-building with actual scholarly rigor → A Korean Business Navigator. A Medical Billing Specialist. A Grant Writer. A CFO. The framing is the breakthrough: stop building one god-agent that does everything badly. Structure it like a company — specialists, clear responsibilities, handoffs between them. Deploy a squad: Frontend Dev + Backend Architect + Growth Hacker + Reality Checker, and ship an MVP with a quality gate at the end. And installing it went from "clone and copy files" to a native desktop app — macOS, Linux, Windows. Browse the roster, click, and it installs into Claude Code, Cursor, Codex, Gemini, and 10 other tools. Auto-updates included. The community translated the entire thing into 8 languages. The Japanese fork alone has 97 Japan-market original agents. MIT license. Use it commercially. Strip the branding. No attribution required. Nine months from Reddit thread to one of the fastest-growing repos on GitHub — because one person decided AI employees deserved job descriptions. Your dream team is a git clone away. Or now, just a download. (Link in the comments)

Release v0.13 - deployed🚀 What's New: • QUANTS 🧠 + Agent Vaults: 1-click vault creation with your agent. Anyone can now fund and invest in your quant agent strategy on @pacifica_fi + Go Live flow: deploy an agent to live auto-trading, fund its subaccount, pick pair/interval, toggle on and off + Visual strategy/trigger builder: build entry/exit rules + Show PnL for clone-funded positions directly in the investment row + Agent Positions tab: view all your agent positions in one tab on the trading screen + Set take-profit and stop-loss as simple percentages on any strategy + Triggers: easily modify and optimize agent signal triggers without needing to interface with natural language prompts or code mods + Explore: clone [1-click] proven quant strategies from top earning quants, traders and TradingView scripts https://t.co/4HAo76QYkU + Integrated perps exchange: @Lighter_xyz, with a guided 3-step setup (link wallet, deposit, enable trading) • VIBE 😎 + https://t.co/nwzDBMcBD1: mobile-first, creator driven quant agent funds. 1 tap deposit + Portfolio graph on your Vibe profile: equity and PnL over time (24H / 7D / 30D) + Vibe strategy cards now show depositor avatars so you can see who backed a strategy + Vibe referrals: custom referral code, shareable link with one-click copy, and a Referrals page tracking who you brought in + Earn referral credit when someone clones your agent + Redesigned Vibe top bar with logo, login button, and user avatar Fixes & Improvements 🧰 • Backtests now queue and run automatically when the system is busy instead of failing • Backtests run on Cloudflare Workflows with live progress and auto-recovery of stuck runs • AI strategy generation falls back to a paid model only as a last resort, so it keeps working when the default AI is degraded • Fewer exchange rate-limit errors during backtests (shared candle fetches plus retries) • Fixed order placement being blocked while the wallet was still loading • Fixed the login modal staying open after sign-in • Fixed the Reduce-Only checkbox flickering while positions load • Smoother onboarding, with a grace period so "link wallet" no longer flashes right after login • Prevent accidentally closing modals mid-action (for example during a deposit) • Polish on chat suggestion cards, empty states, and the loading overlay New Perp DEX Integrations 📈 + @Lighter_xyz [EVM] • manual trading - activated! • agent trading - activated! • guided 3-step setup (link wallet, deposit, enable trading) + @Ekidenfi [Canton] • manual trading - testnet! • on @CantonNetwork - soon🧠

"Anthropic just quietly changed the game for solo builders. Claude Sonnet 5 dropped June 30. Most people saw "new AI model." I saw a $4,200/month opportunity get 40% cheaper. Here's what actually happened — and why it matters for your income: Sonnet 5 now does what only Opus could do 3 months ago. It plans. It uses tools. It browses the web. It writes, fixes, and ships code — autonomously. End to end. Without stopping halfway. Zapier tested it: they handed it a two-part automation task — update Salesforce, send a launch email. It finished both. Alone. No human in the loop. That used to require a $25/month Opus model. Now it runs on Sonnet 5 at $2 per million tokens. Let me translate that into real numbers: Before Sonnet 5 — running an AI agent for a client automation workflow cost ~$80-120/month in API calls. After Sonnet 5 — same workflow, same output, costs ~$30-40/month . That's 40-60% cheaper to run the same business. The window is open until August 31. After that, price goes up 50%. Most people will read the headline and close the tab. The people building right now are locking in workflows at discount pricing before September hits. I use Claude daily to run my AI income system. This update just made that system cheaper, faster, and more autonomous. If you're not building with AI agents in July 2026, you're not just behind. You're paying full price while everyone else pays half. The clock is ticking."

People think building AI agents in n8n is hard. Reality: one prompt builds an entire agent for you. No need to learn complex workflows or spend hours on setup. Just give ChatGPT the following prompt. It handles the entire agent creation process in minutes. Here's exactly how to use it step by step: [bookmark 🔖 this post for later] The process: 1. Open ChatGPT 2. Paste in one mega prompt 3. Describe the agent’s purpose 4. GPT delivers: ↳ Workflow structure ↳ n8n nodes ↳ Trigger setup ↳ LLM integration ↳ Error handling ↳ Ready-to-use code 5. Implement the steps in n8n. And you’re done. Here's the mega prompt (copy it): - - - prompt starts below this line - - - <role> You are an experienced automation architect with advanced knowledge of building AI-powered agents in n8n. You have deep expertise in automation flows, activation triggers, third-party APIs, GPT connections, custom JavaScript logic, and error handling. </role> <task> Walk me through, step by step, how to create an AI-powered agent in n8n. The agent’s purpose is: {$AGENT_PURPOSE} </task> <requirements> 1. Begin by defining the agent's objectives and necessary inputs/outputs. 2. Create the overall architecture for the agent workflow. 3. Suggest the required n8n nodes to include (built-in, HTTP, function, OpenAI, etc.). 4. Explain how to configure each node and why it’s needed. 5. Provide instructions for any custom logic (JavaScript functions, expressions, etc). 6. Help me implement retry logic, error handling, and backup procedures. 7. Show how to store and access data between runs (e.g., with Memory, Databases, or Google Sheets). 8. When the agent requires external APIs or services, explain the connection and authentication process. </requirements> <output_style> Be exceptionally clear and practical, as if coaching a beginner automation developer. Use visual formats if possible (e.g., structured lists, flow-style layout), and always provide ready-to-implement node configurations or code examples. </output_style> <expandability> Conclude by recommending ways to increase the agent's capabilities, such as workflow chaining, webhook integration, or connections to vector databases, CRMs, or Slack. </expandability> - - - prompt ends above this line - - - I used this to create: ✓ A Reddit, Claude, Telegram content curator ✓ A prospect qualifier that evaluates and directs incoming leads ✓ An automated email assistant that analyzes messages + creates replies All driven by Claude + n8n. - No Zapier. - No LangChain. - No complex frameworks. Why this approach works: → GPT acts like a senior engineer, designing the agent end-to-end → n8n gives you complete flexibility (logic, memory, APIs, webhooks) → Claude or ChatGPT handles reasoning and decision-making It’s the simplest way to launch real AI agents today.

n8n in 2026: The Biggest AI Mistake Is Treating Automation Like an Agent Everyone wants AI agents. Very few actually need them. Most enterprise AI value still comes from deterministic workflows with AI embedded at the right decision points, not autonomous loops running the entire business. Deep Architect Lens Production AI automation is an orchestration problem before it's an intelligence problem. The winning pattern is simple: event-driven workflows, deterministic execution, AI only where judgment is required, and humans approving consequential actions. n8n fits this architecture exceptionally well. It orchestrates APIs, RAG, LLMs, MCP tools, and business systems while keeping workflows observable, versioned, and debuggable. When complexity evolves into long-lived reasoning, state machines, or autonomous planning, you've crossed the boundary from workflow automation into software engineering. That's where custom agent frameworks belong. CEO / CTO / Boardroom Lens The business doesn't care whether an agent wrote the email. It cares whether customer data stayed compliant, every action is auditable, costs remain predictable, and failures can be replayed and recovered. Governance, not autonomy, determines enterprise readiness. Market Shift From: AI replacing workflows. To: AI augmenting governed workflows with deterministic execution and bounded intelligence. What Actually Works in Production Self-hosted orchestration. Queue-based execution. Postgres-backed state. Encrypted credentials. Idempotent triggers. Version-controlled workflows. Scoped AI decisions. Human approval for business-critical actions. Where Most Teams Fail Agent-everything architectures. Silent workflow failures. No approval gates. Hardcoded secrets. Demo-driven automation. Building applications inside workflow tools long after they've outgrown them. Adopting Strategy Start with deterministic automation. Introduce AI only at high-value judgment points. Measure cost, latency, confidence, and outcomes before increasing autonomy. Let workflows graduate to code only when architectural complexity demands it. Final Insight AI doesn't replace architecture. It amplifies it. The teams that scale aren't building smarter agents. They're building smarter execution systems. #AIArchitecture #WorkflowAutomation #n8n #EnterpriseAI #LLMOps #PlatformEngineering #DistributedSystems #SystemDesign #AgenticAI #SoftwareArchitecture https://t.co/CYeIdTN14x

Voice agents just crossed from demo to product. xAI launched Voice Agent Builder on July 1. No code. Working agent in about 2 minutes. Knowledge base built in. Tools, guardrails, MCPs, observability. 80+ voices. Phone numbers and SIP support. Pricing is simple too: $0.05/min for audio. $0.01/min extra if you use their provisioned phone number. This is not a chatbot with a phone number. This is software that can answer, reason, use tools, transfer to a human, record the call, and leave a transcript. Every business with a phone line should be paying attention. Support. Scheduling. Intake. Follow up. Ministry workflows. The front desk is becoming an AI workflow. This is not a nice-to-have. It’s a new baseline.

xAI Launchs No-Code Grok Voice Agent Builder xAI has launched Voice Agent Builder in beta, a no-code platform that lets businesses create production-ready AI voice agents powered by Grok Voice in under two minutes. Users can describe how they want the agent to behave, attach documents, connect business tools, add guardrails, and deploy it with a browser-based interface without writing a single line of code. The platform also includes built-in telephony, observability, and one free phone number for every account. Voice Agent Builder uses a unified speech-to-speech architecture instead of the traditional stack of speech recognition, language models, and text-to-speech services. xAI says this delivers lower latency and more natural conversations while simplifying deployment. The service is priced at $0.05 per audio minute, targeting customer support, sales, and other conversational business workflows. The launch reflects a broader trend in enterprise AI: building and deploying custom voice agents is quickly becoming as simple as creating a website. As costs fall and setup times shrink, AI voice assistants are moving from experimental projects to mainstream business tools. #AI #xAI #Grok #VoiceAI #AIAgents #ArtificialIntelligence #Automation