No-Code Agentist

WATCH ME BUILD AN AI BUSINESS FROM SCRATCH (EPISODE 1) I'm building an AI services business from scratch, on camera, with 4 rules: -100% cold outreach -No audience -No network -60 minutes a day max The scoreboard is how many days it takes a total stranger to pay me $500. Here's the entire model: 1) The niche is tree services in Charlotte. High ticket, no private equity, and after-hours emergencies where the first person to answer wins the job. 2) The offer: a built and hosted website, an AI-powered speed-to-quote form, and a Google Business Profile cleanup. $500 flat. 3) The website IS the lead magnet. We build it first, give it away free, and charge $500 to install and host it. 4) Five agents inside @hyperagentapp run everything. Prospector, Opener, Sitesmith, Fulfiller, and an Account Manager upsell. 5) The Prospector dispatched 8 subagents, scraped 494 businesses, and verified 98 real leads. Done in 30 minutes. 6) The competition is a joke. The first five "websites" on my list: a blank page, a 404, two dead links, and a redirect to a crypto gaming site. 7) First-touch texts: under 160 characters, no links, no emojis, no mention of AI. "Hey, do y'all still do tree removal in Charlotte? Found you on Google. Corey." 8) The agent wrote "y'all" on its own. Sounding like a neighbor, not a company, is the whole reply-rate game. 9) 60 minutes a day covers 25-50 outreach attempts. Outreach is the only work that actually makes money. 10) All 5 agents get given away free in episode 4, plus $1,000 in free Hyperagent credits at the link in the YouTube subscription. Enough to run my entire lead scrape 6 times over. Two things that I'm looking to accomplish here: 1) Strip away every advantage and prove the model still works. If it works with no audience and one hour a day, nobody has an excuse left. 2) Give away the finished deliverable, not a pitch. An owner looking at their own new website doesn't need convincing. Full breakdown below. https://t.co/KorFj09jeo (also available on the Build With AI podcast)

In June 2026 the industry stopped talking about prompting agents and started talking about designing the loops that prompt them. What loop engineering actually is, where it came from, where it pays, and where it is just an expensive while loop. https://t.co/EX7jzYzBRE

I've written an article on setting up a no-cost 24/7 agent to run basic tasks, research, automations etc. Have a look! https://t.co/V6RGKpN8aq

NO CODE AI AGENT AUTOMATION FOR EVERYONE For years, building autonomous AI agents required writing intricate python scripts, managing complex API keys, and wrestling with unstable developer frameworks. This steep technical barrier prevented non-technical creators, managers, and entrepreneurs from leveraging agentic workflows. BAIclaw officially dismantles these obstacles by introducing a visual, code-free environment for AI Agent execution. BAIclaw is designed from the ground up to make agent deployment simple, powerful, and ready out of the box. Featuring a minimalist graphical user interface, users can manage, connect, and run AI Agents without writing a single line of code. The one-click installation process eliminates tedious terminal configurations, allowing you to focus entirely on task outputs. Furthermore, BAIclaw is completely free, multi-platform, and local-first. This means your agent workflows run directly on your own device, maintaining absolute privacy while delivering high-speed execution across operating systems. Whether you want to automate administrative tasks or build sophisticated research agents, BAIclaw provides the cleanest visual toolkit available. Download it today at https://t.co/aKD4huHJgv and bring code-free AI agents to life. @BAI_AGI @justinsuntron #TRONEcoStar

An Anthropic engineer just explained the biggest mistake people make when building AI agents. They keep babysitting the model instead of designing a system that can supervise itself. His solution is to place the agent inside a graph where every step has a clear role, expected output and recovery path. The model no longer depends on a human to manually guide every action. In 25 minutes, he explains how Anthropic builds agents that work on multiple tasks in parallel. Different agents can handle separate parts of the workflow, then review each other’s results before moving forward. When one step fails, the entire process does not need to restart. The system identifies the problem, sends the task back for correction and continues from the point where the failure occurred. This gives the agent three essential capabilities: parallel execution, automatic verification and failure recovery. That structure is what separates a real agent system from a chatbot. A chatbot waits for another prompt when something goes wrong. A properly designed agent can find the error, correct it and continue working with minimal human supervision. The lesson is not to write longer prompts or constantly watch the model. It is to build an environment where mistakes are expected, checked and corrected automatically.

I built my dream AI CRM. It saves us hours and already helped us reactivate multiple stale deals. The entire CRM is ran by different agents running on schedule. Here's how it works: - Notion database as the CRM - SyncGTM MCP for enrichments and account signals to qualify and score - Claude Code and ChatGPT as agent orchestrators Combine all via MCP, you've got an army of agents working for your sales org. Here are all agents that run it:  1. Account research and meeting prep This agent runs every day at 8:00 am. It checks all demos booked for the day. Before adding a company, it checks whether the account already exists. For each new account, it: • Finds decision-makers, revenue, funding and the tools they use • Studies the company website • Identifies 3 to 5 possible customer profiles • Prepares discovery questions • Suggests 3 to 5 workflows I can share during the call • Scores the account using revenue, team size, funding and job openings • Qualifies or disqualifies the account 2. Post meeting summarizer This agent runs at 11:00 pm every weekday. We use https://t.co/XnYQWVklum MCP to fetch transcripts and summarize + score intent. It: • Matches each meeting with the right account • Reads the transcript • Summarises what was discussed • Updates the account in Notion • Scores their level of interest • Adds the next step 3. New signups qualifier and enrichment agent This agent runs once a day. It checks our Google Sheet for new signups from the last 24 hours. It then: • Checks the company’s revenue and sales team size • Adds only qualified accounts to Notion • Enriches and scores each account • Updates whether they are already a user • Assigns the next task 4. Follow-up AI SDR agent This agent runs every day at 8:00 am. It finds accounts marked “Follow up” where no action has been taken. It then: • Reads the meeting notes • Writes a five-step email and LinkedIn follow-up • Adds the contact to our Instantly campaign • Finds the existing Gmail thread • Checks whether they replied • Updates the follow-up status Vibe coding a CRM is the wrong approach. Tailoring and building agents to fit your workflows and playbooks seems to be the way. All you need is: - A good database to start with - Capable AI model connected to your tools - Multi agents that manage different parts of the system We're going to see many custom built solutions highly tailored to the team. Comment "AI CRM" if you want prompts of these agents.

What if you could run private #AI agents in minutes? With @llmware Model HQ on @Snapdragon X Elite, you can build no-code agent workflows that run on-device, in the cloud, or both. Watch how local small language models handle enterprise docs without cloud routing 👇 https://t.co/8zpRcVs7HR

BUZZ TESTED LIVE: THE AGENT ALREADY HAD MY WORDPRESS LOGIN This agent literally published a blog to WordPress with zero setup. Nobody gave it the login. It pulled it from Claude Code's existing config. We tested Jack Dorsey's Buzz from scratch. Here's what happened: → Installed the app. Picked Claude Code. No API key needed. → Tagged an agent: "Come up with content ideas." It scanned local files first. → Told it to write the blog. It used our custom SEO workflow. Untrained. → It even opened Firefox with computer use to verify the post went live. The whole thing took minutes. Every hour you spent training Claude Code carries straight in. Your workflows. Your formatting. Your credentials. All inherited. One catch: you must tag agents directly every time. And run out of Claude tokens? Switch to Codex mid-chat. Easier than Hermes. Easier than OpenClaw. Free. Want the SOP? DM me. 💬

"wowshot," AAA vibecoding, and "magnum opus," via Symphony doctrine https://t.co/oTpmiQx93V