No-Code Agentist

@sriramk @garrytan You should check out https://t.co/jGcfVuVVyj to find full agent workflows you can install in OpenClaw and Hermes. Lmk what you think.

FREE AI Agents Course Build & Automate ANYTHING https://t.co/y2HIurA7LR

An open-source project called AaaS (Agent as a Service) has been released for regular users and small businesses to present their services via an AI agent. What you can do with it: - Use your domain knowledge to build the service with no code. Use the chat in the dashboard/CLI to build the service including database and service rules (SkILL) within the workspace. - Manage transactions with an adaptive dashboard. - The agent runs within its workspace on your local machine; no hosting service is required. - Deploy it to major platforms like WhatsApp, Telegram, Discord, and Slack. - Embed it in your website in a chat-widget using one-line HTML. - Free webhook relay service included for website embedding and WhatsApp. Sample Use Cases - Date Matchmaker AaaS deployed on social platforms. - Used iPhone buyer and seller agent. - Agent to accept beauty salon appointments. - Delivery service agent for a grocery shop. Repo: https://t.co/ty819KTxPd AaaS website: https://t.co/ShzhfakT2P Feel free to support the project. AaaS is for regular users and small businesses to incorporate an agent into their business WhatsApp, Telegram, or website to run their business.

A prompt is a one-shot thing. Input goes in, output comes out. An agent has a goal, uses tools, loops until the job is done, and hands off structured output to the next step. Most people hear "AI agent" and think it's a fancier prompt. It's not. Here's the difference and how we build them: A prompt: you paste a competitor transcript, ask for analysis, get a response. You manually copy the output and move to the next step. An agent: you give it a list of 10 competitor brands. It searches Meta Ad Library, finds their longest-running video ads, extracts transcripts, analyzes each one through a research framework, writes individual analysis files, consolidates patterns across all 10, and outputs a structured research brief. You review the final output. The 4 building blocks of every agent: Tools — what it can do. File read/write, API calls, web search, code execution. The tool list defines the ceiling. Memory — what it remembers across steps. Short-term is the context window. Long-term is JSON files it writes and reads across sessions. Loop + Exit Condition — perceive, think, act, check, repeat. Runs until a specific exit condition is met, not until it runs out of things to say. Handoff — how it passes structured output to the next agent or to you. Clean handoffs use typed JSON files. We use Claude Code to build these. The research agent reads a brand list, processes each competitor through the full analysis framework, and writes a research_brief.json that the script agent picks up automatically. The human gate is built into every agent. The research agent produces a brief — you review it. The script agent generates hooks — you pick the winner. Autonomous doesn't mean unsupervised. This is the infrastructure that lets a 2-person team produce content at the velocity of a 15-person creative department.

Switching AI tools used to reset everything. New agent. No memory. Start again. OpenClaw 4.11 fixes that. Now you can import your entire ChatGPT conversation history into Dreaming memory. That means: → persistent preferences → remembered workflows → stored decisions → project continuity → long-term agent intelligence Your agent finally grows with you. Save this video, you’ll understand why this update matters. Full Guide available inside the AI Profit Boardroom. DM for the link. 💬

𝗚𝗼𝗼𝗴𝗹𝗲 𝗷𝘂𝘀𝘁 𝗹𝗮𝘂𝗻𝗰𝗵𝗲𝗱 𝗮 𝗚𝗲𝗺𝗶𝗻𝗶 𝗔𝗴𝗲𝗻𝘁 𝘁𝗵𝗮𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝘀 𝗺𝘂𝗹𝘁𝗶-𝘀𝘁𝗲𝗽 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 𝗮𝗰𝗿𝗼𝘀𝘀 𝗚𝗺𝗮𝗶𝗹, 𝗖𝗮𝗹𝗲𝗻𝗱𝗮𝗿, 𝗗𝗿𝗶𝘃𝗲, 𝗮𝗻𝗱 𝗠𝗮𝗽𝘀 𝘄𝗶𝘁𝗵 𝘇𝗲𝗿𝗼 𝘀𝗲𝘁𝘂𝗽. Here's a real workflow you can try the moment you get access: → Scan my inbox from the past 72 hours → Summarize emails that need action → Draft responses for the straightforward ones → Flag anything complex for my review → Add follow-up tasks with deadlines to Google Tasks That used to take an hour every Monday morning. The agent handles the first pass in minutes. Here's the honest comparison with OpenClaw: Gemini Agent: Zero setup. Works immediately inside Google. US only. $249/month. OpenClaw: Free to use. Works across Gmail, Outlook, Slack, Discord, and more. Requires technical setup and active security management. Currently Gemini Agent is only available to Google AI Ultra subscribers in the US in English only. If you're already in the Google ecosystem and want the lowest friction entry point it's worth exploring. If you want flexibility across multiple platforms OpenClaw is the more powerful option. The skill that matters regardless of which tool you use: Learn how to break a workflow into steps and delegate execution to an agent. That skill carries forward no matter what wins. Save this post. Want the full breakdown? DM me. 💬