No-Code Agentist
A daily digest of practical AI agent workflows for non-developers. We isolate actionable no-code guides from viral hype. Scored against human-defined standards.
Daily Summary
20 curated | 31 evaluatedThe no-code agent ecosystem continued to evolve as practitioners shared , , and documented evidence that agents improve through without retraining, while security researchers flagged in desktop agents and educators released .
Grok Bot Use Cases NEW TODAY - Refresh after Xapi filed 5 more posts: 89 unique (last_empty after 6 GraphQL pages: 20+20+20+20+9+0). Official 0 / Testers 89. Xapi 5/5 landed (SymoneBeez, GlowbomOSS, RetroValix, Av1dlive, TheNotARubicon). 76 new vs urls-latest first dump; 13 of the prior 19 still on the timeline (6 first-dump posts not in this scrape — content kept). No elonmusk / bot / grok author posts. Quoted SpaceXAI engineers and PMs still Testers (author is the poster). Glowbom OSS from inside Grok Bot is Testers, not Official. Hype (trading PnL, $83.5k, $7.7k, $24k/mo, “make money”) labeled, not treated as fact. Not a medical or trading how-to. Review 2090096266533335474 stays separate. - Testers (SymoneBeez, Sep 2): Email bot for 5 inboxes + Slack bot + Chief of Staff stood up in ~20–30 min. Works across devices. Testers comparison to Hermes/OpenClaw is Tester framing, not Official product. Filed: First hour / Chief of Staff; Team of bots; Inbox and calendar. - Testers (GlowbomOSS, Sep 2): “Built in Glowbom OSS using Muse Spark 1.3 via OpenCode from inside Grok Bot.” Testers OSS from inside Grok Bot — not Official bot / grok / elonmusk and not a Glowbom Official SKU. Fills Grok Build site (was empty). Filed: Grok Build site; Overnight coding and build / print loop. - Testers (RetroValix, Sep 2): B2B growth-agency “AI office” — 5 named seats on one persistent cloud computer: Growth Strategy Analyst, Sales Outbound, Paid Media, Sales Analyst, Agency Account Manager. Skills/Routines; parallel; handoff loop Strategy → Outbound/Paid Media → Sales Analyst → Strategy. “50% more clients” / net-profit line is Testers anecdote, not a SKU. Filed: Team of bots; One-person company. - Testers (Av1dlive, Aug 29): Grok Bot template sharing live — early-access Chief of Staff bot to copy. Testers template, not Official Marketplace SKU. Filed: First hour / Chief of Staff; Bot Templates. - Testers (TheNotARubicon, Aug 27): Chief of Staff routes large requests/jobs to local Grok Build CLI to conserve Bot tokens; Grok Build sends results back to Grok bot. Testers setup, not Official SKU. Filed: First hour / Chief of Staff; Grok Build site; Overnight coding and build / print loop. WHAT IT IS - This note is use-case practice from the Grok Bot Use Cases folder only: how Testers actually staff a Chief of Staff, brief a bot, run a small team, wire inbox/calendar/Slack, hunt subscriptions, run a one-person desk, research, code overnight, copy templates, shop with Link, and keep a human on money. It is not Review as its own title. It is not Grok Bot How To Use. It is not a Grok Bot product dump (folder Grok Bot stays separate). - Official vs Testers: Official = elonmusk / bot / grok as AUTHOR of the post. Everyone else is Testers — including posters quoting Elon or SpaceXAI engineers/PMs, and including GlowbomOSS. This dump has Official 0 / Testers 89. - Do not retitle. Do not mix Review (id 2090096266533335474) or Grok Bot How To Use into this as those titles. Do not invent features, prices, or plan SKUs. Glowbom OSS / Skills Dojo / Plugin Marketplace / web-app bots are Testers claims, not Official SKUs. Hype (trading PnL, $100k-class claims, millionaire, “almost unfairly easy”) is labeled, not treated as fact. Not medical or trading how-tos. HOW TO USE - Sequence from dump (Testers): (1) treat the Bot as a teammate with a job, not a chat window; (2) name one Chief of Staff first — it routes, it does not do all the work; (3) write Description vs Task and set approval gates before the first send; (4) run by hand three times, then skill, then routine; (5) start with two Bots, cap the roster, reuse before spawning; (6) connect mail, calendar, and Slack and report actuals; (7) put handoffs in /workspace, not chat paste; (8) stay silent unless stuck; (9) overnight: Cursor or local Grok Build CLI for watched/heavy work, Grok Bot team for the rest; (10) copy a proven template instead of rebuilding; (11) Email+Slack+CoS can stand up in 20–30 min (Testers); (12) label money/PnL stories as Testers hype. [] Write a job, not a prompt — what it owns, which accounts, what hours, who it hands finished work to (unicodef1wn, kloss_xyz) [] Separate Description (never changes) from Task (this run). Mixing them is why bots feel inconsistent [] Name one Chief of Staff as the only human entry point. It routes, delegates, watches handoffs, escalates — it does not do every job (adiix_official, ScottyBeamIO, SymoneBeez) [] Set approval gates before the first task: money, publishing, deletion, signatures, irreversible external actions. You still hit send (unicodef1wn, adiix_official, s4yonnara) [] Do not automate on day one. Run it by hand, save a skill, then a routine (unicodef1wn) [] Start with two Bots only. Cap team size. Reuse a bot you already set up before adding a new one (beamnxw, kloss_xyz) [] Connect mail, calendar, and Slack. Have Chief report what you actually spent time on, not what you planned (kloss_xyz, s4yonnara, SymoneBeez) [] Put research, drafts, evidence, decisions, and handoffs in /workspace so the next Bot continues where the last stopped (adiix_official) [] If a tool blocks automation, do the task once while it watches; save the correction as a permanent rule (kloss_xyz) [] Tell bots to stay silent unless they are stuck or they need you to decide (kloss_xyz) [] Overnight: keep watched coding in Cursor; route token-heavy jobs to local Grok Build CLI; hand everything else to a Grok Bot team; ping when the fix lands (0xCarnagee, joehansen, TheNotARubicon) [] Copy a proven template / marketplace bot instead of rebuilding the desk (RoundtableSpace, shmidtqq, Av1dlive) [] Treat trading PnL, “make money,” and $60k / $1k→$3.9k / $83.5k claims as Testers hype. Not a trading or medical how-to - Watch Official elonmusk / bot / grok for any later restatement. Treat SpaceXAI-engineer quotes as Testers until those handles author the post. First hour / Chief of Staff - Testers (SymoneBeez, Sep 2): Email bot (5 inboxes) + Slack bot + Chief of Staff in ~20–30 min. Across devices. Testers vs Hermes/OpenClaw is Tester framing. - Testers (Av1dlive, Aug 29): copy a shared Chief of Staff template instead of writing one from scratch. Testers template sharing, not Official SKU. - Testers (TheNotARubicon, Aug 27): Chief routes large jobs to local Grok Build CLI to save Bot tokens; results come back to the Bot. Testers. - Testers (ericosiu, Sep 2): CoS is the management layer — routes, collects updates, one clean handoff. Does not execute every task. Human reviews send/publish/live-page changes until a workflow earns a specific exception. - Testers (clairevo, Sep 2): How I AI timestamps — Chief of Staff bot first in the 7-bot roster. - Testers (0xRunix, Sep 2): Lauren Tan relay — CoS talks to you; managers talk to CoS; workers talk to managers. You never touch a worker. Testers relay. - Testers (phosphenq, Sep 2): CoS chat running for months; never watch a context meter. Testers relay of SpaceXAI PMs. - Testers (unicodef1wn, Sep 2): skip “General Helper.” Narrow roles (Talent Scout, Bug Reproduction). Description vs Task. Approval gates first. Hand-run → skill → routine. Blueprint: Job, Description, Scope, Approval Gates, Task, Checkpoint, Skill, Routine. - Testers (adiix_official, Sep 2): create the Chief first. It does not do the work. It routes → delegates → watches handoffs → collects outputs → escalates. One persistent cloud computer, multiple Bot screens, shared files, browser sessions, credentials, /workspace underneath. - Testers (kloss_xyz, Sep 2): write a job description (owns / accounts / hours / handoff). Write what each bot is not allowed to touch. Cap team size; ask before adding bots. Point it at the best person you work with and let it read their real work. (First-dump post; not in this timeline — content kept.) - Testers (0xCodez, Aug 18): link-only in first dump. Xapi: automate life 10 steps. Closest section; do not invent the 10 steps from Notes. (First-dump post; not in this timeline — content kept.) - Testers (joehansen, Sep 2): filed closer under Overnight coding (never-sleep ticket watch). First-hour reminder in dump: the Bot keeps the shift after you close the laptop. [] Create one Chief of Staff as the only entry point before any specialist [] Paste a job description into Description; keep this-run instructions in Task [] Set the never-alone list (send, publish, spend, delete, sign) before the first task [] Do not start with 20+ agents. Two Bots, then add [] Email + Slack + CoS can stand up in the first half hour if that is the desk (SymoneBeez) [] Point Chief at heavy jobs so it can route them to local Grok Build CLI instead of burning Bot tokens (TheNotARubicon) How to brief a bot - Testers (Dmytroo_eth, Sep 2): Asteri 10-step operating contract — one narrow job, approved sources, fixed output, exact stop-for-decision. First task by hand on the same cloud computer. Bot never decides both what is true and whether it is allowed to act. - Testers (neil_xbt, Sep 2): don’t design the team from scratch. One agent interviews you (speak answers), then proposes specialized roles. - Testers (ericosiu, Sep 2): one job each; measure business outcomes not AI activity; every bot needs a target, a safety limit, a quality bar, and an eval. - Testers (unicodef1wn, Sep 2): a bot needs a job, not a prompt. Vague tasks drift, forget context, or ask for approval on things that do not matter. Full structure: Job, Description, Scope, Approval Gates, Task, Checkpoint, then Skill and Routine. - Testers (kloss_xyz, Sep 2): when you correct it, save that correction as a permanent rule. Track everything already told; every report only contains what you have not seen yet; if nothing is new, one line. One bot owns conclusions from the data or three bots will argue the numbers. - Testers (adiix_official, Sep 2): every serious workflow gets three gates — source gate → evidence gate → action gate. Bots keep working until something actually needs human approval. - Testers (qyromat0, Sep 2, closest fit from research post): no guessing. If it is not in the data, it does not go on the board. Chief refuses anything a single photo suggests. [] Brief outcome, sources, constraints, deliverable, and the stop-for-review point before you send [] Save every correction as a standing rule [] Require source + evidence before action [] One bot owns the conclusion from the numbers [] A bot should never decide both what is true and whether it may act (Dmytroo_eth) Team of bots - Testers (RetroValix, Sep 2): 5 named AI employees, one permanent job each, same persistent cloud computer, Skills/Routines, parallel, handoff loop. B2B agency desk. Testers scale anecdote. - Testers (SymoneBeez, Sep 2): Email + Slack + CoS as the starter three. - Testers (0xRunix, Sep 2): 20+ / 1 CoS / 3 managers / 16 workers. Not a flat list. Testers relay of Lauren Tan. - Testers (clairevo, Sep 2): 7 named bots (Chief, TradBot, LGTM, Lockdown, Holly, Penny, ShopZilla/Sylvie). - Testers (ericosiu, Sep 2): separate bots for SEO, short-form, outreach, recruiting, sponsorships, pre-call research, code. Park bots that no longer deserve attention. - Testers (ScottyBeamIO, Sep 2): seven named agents around one Chief — Researcher, Writer, Visualiser, Analyst, Scheduler, Publisher. They share memory. Record yourself doing a repetitive task once. - Testers (0xCodez, Sep 2): 20+ agents with Chief of Staff + PM + workers (Lauren Tan relay). Loop and graph, not one agent. Testers scale; dump also says too many Bots can slow the system (adiix_official). (First-dump post; not in this timeline — content kept.) - Testers (0xrux, Sep 2): three bots, three jobs — Pop content, Crackle research, Bubbles inbox. One job each, own computer for browse. - Testers (s4yonnara, Sep 2): Claire Vo — one job, one name, one scope. Own account per bot. Approval gate before anything irreversible. (First-dump post; not in this timeline — content kept.) - Testers (antpalkin, Sep 2): swarm that hires and fires its own staff; one veto agent. Org chart is the advantage. Hype ($1k→$3.9k, $300/mo) labeled, not a trading how-to. (First-dump post; not in this timeline — content kept.) - Testers (0xChonsy, Sep 1): link-only. Xapi: how many agents. Closest section; do not invent a headcount rule beyond kloss/adiix (cap, reuse, too many slows). - Testers (tibor_tee, Sep 2): workshop on agent teams to research, prioritize, and ship products. - Testers (0xchromium, Sep 2): add a second and a third, tell one who’s in charge, they sort order. Record once → routine. [] One Chief; specialists with one job each [] Shared /workspace bus — no copy-paste of context between tools [] Reuse before spawn; cap the roster; ask the human first [] Merge / deploy / send / spend stay behind a human gate [] Record yourself once to teach a repetitive task [] Five named seats with one permanent job each, same persistent cloud (RetroValix) Inbox and calendar - Testers (SymoneBeez, Sep 2): Email bot for 5 inboxes + Slack bot under Chief, stood up in 20–30 min. - Testers (rileybrown, Sep 2): bot gets its own email; webhook trigger runs a routine on inbound mail; forward mail / add to chains. Testers. You still hit send. - Testers (clairevo, Sep 2): TradBot = family agent (schedule). Same walkthrough as s4yonnara. - Testers (s4yonnara, Sep 2): Chief sweeps six inboxes, six Slacks, and every calendar hourly, and only pings when it truly matters. Trad Bot prints the day’s schedule on paper so kids read it at breakfast, not on a screen. (First-dump post; not in this timeline — content kept.) - Testers (0xrux, Sep 2): Bubbles triages email, drafts in language she had actually written, and ranks what to skip (blasts) vs what has a real brief. You still hit send. - Testers (kloss_xyz, Sep 2): have it read email and calendar every hour and report what you actually spent time on. It is rarely what you planned. [] Connect mail and calendar under the Chief first [] Add Slack if that is where the desk lives (SymoneBeez) [] Triage what needs a reply; draft in your voice; you hit send [] Report actuals hourly; ping only when it truly matters [] Do not auto-send. Do not auto-post [] Webhook-on-mail is Testers practice — still a human on irreversible (rileybrown) Subscription audit - Testers (clairevo / s4yonnara): Penny Pincher digs through receipts for subscriptions to cancel and bills worth renegotiating. Same walkthrough: approval gate before anything irreversible. - Testers (shmidtqq, Sep 2): catalog includes bots that cancel parasitic subscriptions — copy a proven bot; still a human on binding cancel/pay. [] Read-only first: list subscriptions from receipts / mail [] Hard stop: no accept, no confirm charges, no binding cancel without you saying run it [] Human still signs in and hits the irreversible button One-person company - Testers (RetroValix, Sep 2): B2B agency AI office — 5 employees, parallel, persistent cloud, recurring Skills/Routines. “50% more clients” is Testers anecdote, not Official earnings. - Testers (ericosiu, Sep 2): agency-shaped desk; share templates with teammates; everyone manages a small group of specialists; park bots that do not earn attention. - Testers (wandermist, Sep 2): research / leads / email / content / ops passing work. Testers; not a headcount guarantee. - Testers (beamnxw, Sep 2): 6-bot newsletter company that keeps working after you close the laptop. You pick the topic and polish the draft; Bots do the rest. Steal this roster only as Testers practice: research compiler → draft writer → ESP sender on your best times → marketing → sponsor outbound → chief of staff on top. Start with two Bots. Research finds three options. You pick one. Writer drafts. You edit. Then add send, marketing, and sponsors. “Make money” is Testers hype, not Official earnings. - Testers (s4yonnara, Sep 2): Claire Vo runs business and family on named Grok Bots. Hire like people. Own computer that keeps working after the laptop closes. - Testers (ScottyBeamIO, Sep 2): people point it at sales outreach, research, SEO, bookkeeping, customer replies, personal admin, publishing. Question is what you point it at, not whether you can build an API stack. - Testers (Mikadzyki_NFT, Sep 2): “agent factory” — company in, digital worker out. Testers; not a SKU. [] Write what the company does in one paragraph and what it must never do alone [] Chief of Staff first; two Bots; you still pick the topic and polish the draft [] Add send / marketing / sponsors only after the research→write loop is clean [] You still hit send, publish, and spend Daily brief / research - Testers (SPCX100T, Sep 2): weekday pre-market sourced brief; quiet sections say “nothing new”; every item has a source link. Testers scanner, not Official; not financial advice. - Testers (hanakoxbt, Sep 1): overnight filings/read loop; ping only for irreversible. Testers anecdote; $4.98 labeled. - Testers (liam_fallen, Sep 2): link-only BI system card. Closest section; do not invent a BI dashboard how-to. (First-dump post; not in this timeline — content kept.) - Testers (ScottyBeamIO, Sep 2): Researcher finds what is moving, checks the claim, drops duplicates, hands a brief with links. Analyst reads what actually performed (hook shape, format, time slot) and tells Writer/Scheduler what to change. - Testers (0xrux, Sep 2): Crackle browses on its own computer, generates ideas from that day’s actual news — without touching her browser. - Testers (qyromat0, Sep 2): six agents index 31,400 photos, rebuild days from geotags/receipts/timestamps, write only what can be sourced. Chief refuses unsourced pages. Not medical. Not a memory-clinic how-to. - Testers (kloss_xyz, Sep 2): every report only contains what you have not seen yet; if nothing is new, one line. - Testers (morpphhhaw, Sep 2): research, not a trading desk — agents surfaced a public builder instead of inventing a Polymarket strategy. ~$60k / rent story is Testers hype, not advice. [] Demand sources and links on every brief; no guessing [] New-only reports; one line if nothing changed [] Analyst loop: what actually performed, then change the next draft [] Do not treat folder trading stories as a how-to Grok Build site - Testers (GlowbomOSS, Sep 2): Glowbom OSS site built with Muse Spark 1.3 via OpenCode from inside Grok Bot. Testers OSS — not Official bot / grok / elonmusk. Do not invent Glowbom as Official. - Testers (TheNotARubicon, Aug 27): CoS sends large jobs to local Grok Build CLI; Grok Build returns results to the Bot. Testers token-conservation setup. - Testers (ericosiu, Sep 2): FirstMate — Grok Bot for GitHub & development (chapter in the business video). Testers. - Testers (0xrux, Sep 1): Website Maker bot with its own browser, defined role. Testers. [] Build the site from inside Grok Bot if that is the desk (GlowbomOSS Testers OSS, not Official) [] Route large coding jobs to local Grok Build CLI; results come back to the Bot (TheNotARubicon) [] Human still reviews merge / deploy / production Overnight coding and build / print loop - Testers (TheNotARubicon, Aug 27): CoS automatically sends large requests to local Grok Build CLI, then results return to Grok bot. Testers. - Testers (GlowbomOSS, Sep 2): OpenCode from inside Grok Bot produced a live OSS site. Testers. - Testers (clairevo, Sep 2): LGTM the PR closer in the 7-bot roster. - Testers (0xCarnagee, Sep 1): Grok 4.6 in Cursor for the work you are watching; hand everything else to a GrokBot team. Parallel agents from Desktop, Slack, GitHub or Linear. Testers relay of Dawson Lind, not Official bot. - Testers (s4yonnara, Sep 2): PR closer clears pull requests daily and fires Cursor cloud agents to rebase; killed a backlog of 50 in that walkthrough. Tester anecdote, not a guarantee. - Testers (joehansen, Sep 2): watch a ticket all night, find the break, ping when the fix lands. Never-sleep shift, not a body. - Testers (tibor_tee, Sep 2): Product workshop — agent teams to research, prioritize, and ship products (closest to this build/ship loop; not a Grok Build TUI post). - Testers (kloss_xyz, Sep 2): do not send a screenshot and ask it to rebuild. Give the real file and a live preview; say “slower” or “too much.” Designing twenty of something: build the first one exactly right, then point the bot at that one. - Testers (hanakoxbt, Sep 1): overnight loop; woke three times only for things it could not undo. Testers anecdote. [] Watched coding stays in Cursor; unattended work goes to a Grok Bot team [] Heavy / token-expensive jobs can go to local Grok Build CLI via Chief (TheNotARubicon) [] Ping only when the fix lands or a decision is needed [] Real file + live preview; do not eyeball a set of twenty from a screenshot [] Human still reviews merge / deploy / production Bot Templates - Testers (Av1dlive, Aug 29): template sharing live — copy a Chief of Staff bot. Testers early access, not Official Marketplace SKU. - Testers (ericosiu, Sep 2): Skills Dojo public skills + bot-template section (AEO/SEO, Trial Reels, Talent). Testers library, not Official. - Testers (mrfundman, Sep 2): SpaceX-engineer writing/CRM/calling bots and Ryze marketing bots — copy and test. Testers. - Testers (RoundtableSpace, Sep 2): Marketplace — browse specialized bots by category, see how each works, add them with routines and workflows already built in. “App store for AI teammates” is Testers phrasing. Not an Official SKU in this dump (no bot author post here). - Testers (shmidtqq, Sep 2): 178 battle-tested setups from 1,628 public posts, categorized (sales, code, finance, content, daily life), ranked by real usage, auto-refresh every 6 hours. Copy a proven bot and run it. Zero code / zero signup / zero cost are Testers claims, not Official pricing. - Testers (nima_owji, Sep 2): Plugin Marketplace / web-app bots are Testers claims, not Official SKUs. [] Browse a category / copy a proven setup instead of rebuilding the desk [] Keep the same approval gates on an imported bot: send, spend, delete, publish stay with you [] Do not treat a copied finance/trading template as a trading how-to [] Shared CoS template is Testers (Av1dlive), not Official Shopping with Link - Testers (rileybrown, Sep 2): bot gets a Stripe Link credit card; test buy from Amazon via email. Testers. You still hit buy. Not Official pricing/SKU. - Testers (clairevo, Sep 2): ShopZilla and Sylvie Style — personal shopping in the 7-bot roster. Testers. [] Human still hits buy / confirm / pay [] Do not treat a Tester Amazon-buy demo as an Official Link SKU CFO / Bank Connect - Testers (rileybrown, Sep 2): Stripe Link card on the bot. Closest money-connect post. Testers. Human still approves spend. - Testers (s4yonnara, Sep 2): closest fit — Holly Helpdesk handles refunds through a Stripe approval button (human still approves). Penny Pincher is receipts/subscriptions (see Subscription audit). No Grok Finance / bank-connect post in this scrape. - Testers (antpalkin, Sep 2): swarm with one veto agent between the brain and money. Filed under Team of bots. $1k→$3.9k / $300 a month is Testers hype, not a CFO how-to and not financial advice. - Testers (morpphhhaw, Sep 2): Polymarket research anecdote filed under Daily brief. Not financial advice. Not a bank-connect how-to. - Testers (BIGMayrr / Lummox_eth / polydao): one agent proposes, several must agree, human gate before anything real leaves. Testers trading-floor architecture — hype labeled, not a CFO how-to. [] Human approves every pay, refund, move, or confirm-charges action [] Do not treat folder PnL stories as a how-to. Not financial advice ACCESS - No Official elonmusk / bot / grok author post in this scrape. All 89 Testers. Watch Official if they later restate product, templates, Marketplace, web-app bots, or Link. - Testers workshop: Grok Bot for Product (tibor_tee / roshan_s) Wed Sep 2. Testers meetup: mattyp coffee shop Fri Sep 4 (credits claim not Official). - Testers Marketplace / Skills Dojo / template copy / Glowbom OSS / Plugin Marketplace / web-app bots are preview in this dump, not Official SKUs here. - Defer Review → Review note (id 2090096266533335474). Defer Grok Bot product dump → Grok Bot. Defer Grok Build TUI → Grok Build. Do not retitle this Grok Bot How To Use. - Not medical. Not trading. Hype labeled. KEY LINKS - Testers Email+Slack+CoS 20–30 min (SymoneBeez): https://t.co/mwSTVtrcRD - Testers Glowbom OSS from inside Grok Bot (GlowbomOSS): https://t.co/OeWjuDLPU2 - Testers B2B agency AI office (RetroValix): https://t.co/W0N9pKnrhp - Testers shared CoS bot template (Av1dlive): https://t.co/UxgkYxyY8M - Testers CoS routes to local Grok Build CLI (TheNotARubicon): https://t.co/F1O0OluEPi
I turned Codex into a self-learning agent and now vastly prefer it to OpenClaw, Hermes, Grok Bot and others. Every task improves the client files, memory, templates, skills and workflows and I can inspect or move all of it. Here's how. https://t.co/zAlcT8hB9J
It was never handed a list of addresses. Eight collisions dropped, three vaults survived, two of them documented nowhere. The full method is written up — discovery, the rules, and the evidence standard. Nothing in it rests on trusting us. https://t.co/rcVSVyfdGl
I moved almost my entire Content Engine into @AmpCode. Not just writing. Research, editing, images, visualizations, and even video. Most of my content now starts in the simplest possible way: I open Amp and write a rough thought. Sometimes I do not even type. I just use voice dictation and dump the idea as it exists in my head. Then my harness takes over. Inside the project, I have built a set of skills, instructions, references, and templates that define how I want different parts of the content process to work. So a raw idea can move through something like: Idea → Research → Writing → Editing → Visuals → Publishing assets. But the interesting part is that this is no longer a text-only workflow. The harness is multimodal. For thumbnails and illustrations, I have skills that contain my visual templates and rules. Amp can use its Painter tool, powered by GPT Image 2, to generate or edit the actual image. For some ideas, I want motion instead of a static graphic. I have another workflow using Hyperframes to turn concepts into short visual videos. The agent can work with the files, generate the required assets, assemble the visualization, and iterate on the result. So I can literally start with: “Here is the idea I want to explain.” And the same environment can help me research it, write it, create the image, or turn it into a video. This is where Orbs make the workflow much more interesting. I do not need one agent to do everything sequentially. I can keep writing while another Orb researches a topic. Another can work on the thumbnail. Another can build the Hyperframes visualization. They are separate remote environments, so these tasks do not have to block my main workflow. That changes how I think about coding agents. I started using them because they could write code. Now I increasingly see them as programmable work environments. The real leverage is not just the model. It is the harness around the model. Once your instructions, skills, tools, references, and workflows are encoded into the project, the agent stops being a blank chatbot every time you open it. It already knows how your system works. In my case, that system happens to be a Content Engine. I can sit at my computer or open Amp from my phone, speak an idea into it, and hand different parts of the work to different agents. My job becomes less about operating individual tools. And more about steering the system. That is probably the most interesting thing about Amp for me right now. I am not using a coding agent just to code. I am using it as the runtime for my own content harness.
BREAKING: A team at Tsinghua open-sourced a tool that turns any topic into a full interactive classroom, AI teacher and all, from one sentence. It's called OpenMAIC. Here's what "learning from AI" usually means today. You ask a chatbot, it dumps a wall of text, and you read it alone. Or you watch a talking-head video you can't interrupt. It's one-way, flat, and forgettable, and the polished AI-tutor apps that fix it are paid and closed. This builds you the actual classroom instead. Here's what it actually does: → Describe what you want to learn, or drop in a PDF, PowerPoint, doc, spreadsheet, image, audio, or video, and a two-stage pipeline turns it into a playable lesson → An AI teacher delivers the lecture out loud, with voice narration, spotlight effects, and laser-pointer animations, like a real instructor at a whiteboard, not a paragraph you skim → Interactive quizzes — single, multiple choice, short answer — graded in real time with feedback, so you're tested, not just talked at → Hands-on HTML experiments built into the lesson: physics simulators, flowcharts, things you poke instead of read about → A LangGraph multi-agent core runs several AI agents that take turns and even hold discussions, plus project-based mode where you pick a role and work through milestones with them → Wire it into OpenClaw and generate a full classroom straight from Feishu, Slack, Discord, Telegram, or WhatsApp, no terminal required → Run it hosted with an access code, or self-host the whole thing Two honest flags: it's early (v0.3.0), and the team points to a richer, further-optimized "MAIC-UI" build, so this open version is the solid base, not the maxed-out product. The people who actually retain what they study from AI didn't find a better chatbot. They stopped reading walls of text and walked into a classroom that talks back. MIT licensed. 28.3k stars. 4.8k forks. 100% Open Source. (Link in the comments)
We built a fake company to test whether an agent gets better at its job without anyone retraining the model. Policy compliance went from 20% to 64%. The benchmark is public. This is what we learnt building it. https://t.co/4xIdaM1XRg
To assist those giving OpenClaw 2.0 another chance (like me). :) https://t.co/Gw85D3Atlt
Most analytics MCP tools stop at running SQL queries on your data. Meelu Analytics MCP goes beyond that. Meelu Analytics can actually run data science workflows: • Feature extraction • Classification • Clustering • Predictions • Statistical analysis • ML algorithms • Automatically choosing the right algorithm based on your question Think of it as a full-fledged data scientist for your CSV files — and it’s completely open source. 🚀 Just upload your CSVs, ask a question, and let the agent figure out what analysis or ML algorithm is needed. No SQL. No manually selecting algorithms. No writing ML code. 🔗 https://t.co/Pj6Fbr7DKT
Claude Hacks: 21 Ways to Stop Hitting the Limit I’ve been digging into the latest Claude optimization guide, and these tips are game-changers. If you use Claude daily, you need to see this. 👇 1/ Preparation is everything Don't upload raw PDFs, screenshots, or PPTX files. Copy the text → Google Doc → Download as .md → Turn it into a Skill. Stop making Claude read your trash formatting. 2/ Plan before you build Never open Cowork and say "Build a financial model." Open Chat first. Plan the structure. Then say: "Build this exact file." Big difference. 3/ Force Claude to ask questions Prompt hack: "I need [task] for [goal]. I expect [goal] achieved once we hit [specific targets]. Ask me questions before you start." Fewer hallucinations. Better output. 4/ Stop redoing everything When Section 3 is wrong, say: "Only redo Section 3. Keep everything else. No commentary. Just the output." No more re-writing the entire document. 5/ Batch your tasks Instead of: 1. Summarize 2. List points 3. Suggest a headline Send one prompt: "Summarize, list points, suggest a headline." Saves tokens AND time. 6/ Reuse the same prompt structure Turn your prompts into Claude Skills. Swap only the variable part. I use the same 30-word prompt for 80% of my sessions. 7/ Edit, don't follow up In Chat, click Edit on your original message instead of sending a new one. Fixes it. Regenerates. Replaces the entire exchange. (Works in Chat only, not Cowork.) 8/ Pick the right model Grammar check? Reformat? Use Sonnet or Haiku. Save Fable and high effort for real work. 9/ Ditch the .md files Cowork reads your folder before every task. Instead of dumping files, turn them into Skills. 10/ Restart, don't follow up When Cowork gets it wrong, don’t say "No, I meant..." Click "Restart the conversation from here" on an earlier message. 11/ Summarize every 15–20 messages Ask Claude to summarize everything important. Copy it. Open a new session. Paste it as your first message. Limit Hacks (10–21) ✓ Only include what's needed Don't dump your whole folder. Select only the files Claude needs for that specific task. No files? Select 0 folders. ✓ New topic = New chat LinkedIn post → Proposal → Recipe in the same chat? Stop. New topic, new chat. ✓ Turn off what you don't need Web search, connectors, Explore mode → all add tokens. Default: everything off. Turn on per task. ✓ Use Projects for recurring files Stop uploading the same PDF to five different chats. Upload the file once in Projects. ✓ Schedule recurring tasks Use the /schedule plugin. Set it once. It runs on its own. ✓ Stop using Claude for what it can't do Need images? → ChatGPT Need real-time search? → Grok Use the right tool. ✓ Speak your prompts Use https://t.co/46ev8hXu7j to speak your prompts. Richer context. Fewer follow-ups. Fewer reloads. ✓ Spread across the day Claude uses a rolling 5-hour window. Split your usage → Morning / Afternoon. By the time you come back, earlier usage has rolled off. ✓ Prompt Claude Code tightly "Build a bar chart from this CSV. Save as chart.png." Specific prompts = specific results. ✓ Set Up Preferences Settings → General → Personal Preferences Set your style. Turn off Memory. 👉 Save this thread. You’ll thank yourself next time you’re staring at the "usage limit" screen. Which hack surprised you the most? Let me know below 👇
I know this is a late take but @bot truly feels like the next stage of AI. Biggest leaps so far: 1. GPT release 2. Deepseek/china models 3. Cursor/Claude code via terminal 4. Cursor ai agents 5. Grok Bot About 1-2 years ago until recently it took 5 different providers I had to manually set up to create a full set of useful tools. To understand the extent of it, this were the moving parts of just one project: -Database -Data pipeline -Data cleaning -Computations -Cron/24h live provider -Wrapper/MCP for delivery -Website hosting -Deployment Cloud (with security, password...) -User management Despite AI being good at coding allowing for all the moving parts to talk, Grokbot gets rid of the backend work almost fully. It understands the bottlenecks, the logins, api keys... It solved the issue of being able to replicate what a human would be able to do... A full computer, able to do anything just like a user would, remembering logins, workflows and able to learn. This allowed me to build nets of communication between tools like never before. The best part is the hierarchical ability it has as well on top to create on top of tools. Get the database to communicate with X for news, transform it, post it into Discord. Create a few different ones, one focused on retrieving valuation data, another quant, another news... Another Grokbot from there can look at all reports, create a master doc, upload it to my Karpathy wiki, post it on X. From that report for the week I can then ask yet another how we could improve our workforce(the bots themselves), to get closer to a prime broker level report. I can use this report itself to run automated backtests for the most promising ideas the pod had that week, I can implement real improvement steps, sharpen my data and feedback loop. No more 10 different steps and making sure nothing breaks. Grokbot handles it all, like an actual assistant you would send off to do a task. The AI adjacent providers and overall what backend means itself is shifting back further into the background, making room for swarms of AI agents to take over. In the end Compute, Storage, Energy, AI gets commingled into one overall assistant cost... A very sticky product as you start to use it. 3 agents become 20 agents before you know it. You end up with a real organization, with managers and all. I'll leave you with these two things: 1. We are at yet another breakthrough, where difficult coding disappeared first. This breakthrough is making backend disappear for consumers. Perhaps the next major one is management. 2. We are at the start of this shift, which will need to include payment rails, more speed and overall will need sharpening, but we are moving fast. In the end the result will be networks of AI agents, hundreds to thousands per person over time, transacting, managing the bots and the work product target and working towards the goal you set through the best workers you set up. 3. Those of us with the most data, gathered over the past months and years(even including our own twitter archive, substack, review, prep, charts, execution data and more), will have an amazing and easy time extracting great intel, creating helpful tools and overall use the tech. In a world with no backend, your only real alpha source is the data you feed it and the workflows you build upon it, the automations and multiple layers of alpha generation you get from it. (Personally, my business life is meticulously saved, from what I say, do, prep, review, tools, website, news and much more to make sure that AI has the biggest surface possible to create links, build upon it, understands me and more.)
I built a fully autonomous GTM AI on Fable 5.1, and I'm giving away the setup. It hunts buying signals, finds the decision makers, verifies their emails, and loads the campaign into your sequencer. Funding is only one of those signals (which is what we show in the video below). It reads hiring, tech-stack changes, job posts and ad activity the same way, so you can point it at whatever tells you a company is in motion. Fable 5.1 is a game changer because highly complex agentic workflows are cheaper to run. Considering a single prospecting tool can run dozens of tool calls back to back, cost is a big part of the entire equation. In the video below, you can see the full workflow for one buying signal (funding rounds): 1. It routes to PredictLeads for the signals and keeps 7 real rounds out of 25 raw events. 2. It switches to AI Ark for the people and matches 5 of the 7 companies. 3. It waterfalls the email providers cheapest first, lands on Findymail, and comes back with 5 of 5 found and 4 verified. You never pick a provider. The agent picks on fit, cost and accuracy, and prints what every call spent. That run cost 91 credits. Every account on https://t.co/YKizWZe59i starts with 300 free credits and no card, so you can point this at your own ICP probably three times before you pay us anything. What you get: 1. The Claude Code skill running in this video, one command to install. 2. A key to the ColdIQ's unified GTM API: 40+ data providers, 700+ endpoints, one bill instead of 40. 3. The three prompts, so you can swap in your own filters. Reply "SIGNALS" and I'll send it your way :)
They Never Take Lunch. They Never Say “I’ll Call You Back.” How Much Money AI Agents Are Really Making — and Saving — for Business https://t.co/DbvvnRSF5q
I read the RuntimeWire investigation on Kimi Work this morning, and it raises a question every entrepreneur building with AI should sit with. Moonshot's desktop agent has a hidden system-prompt override. Click "Version" in Settings five times, and you can replace the agent's entire instruction set. RuntimeWire tested it. With the override active, a simple math question triggered a local file read outside the workspace — no approval dialog, no consent gate. The same question with default settings produced nothing. Here's what actually matters: 1. Manual approval does not mean what you think it means. Moonshot's docs say "nothing happens without your consent" under Manual approval. But the underlying Kimi Code kernel auto-allows reads, greps, and glob searches. Writes and shell commands get blocked. File access does not. That distinction may be defensible for a coding agent inside a repo you deliberately opened. It is not defensible for a "system-level digital employee" organizing your folders, browsing your files, and handling client documents. 2. Hidden settings create hidden liability. The prompt override isn't in the release notes. It isn't labeled as experimental. It sits behind a five-click easter egg in a consumer-facing desktop product. That isn't transparency — it is opacity dressed up as power-user convenience. When you're handling financial models, client contracts, or personal records, opacity is a bug, not a feature. 3. The canary test proved local exposure, not exfiltration. RuntimeWire used synthetic data. The file was read. It was not transmitted — zero requests hit their localhost listener. So this is not a remote data breach. It is a local permission bypass that could expose sensitive material to the model's context window without your knowledge. That distinction matters for your threat model. The real question isn't whether Moonshot will patch this. They probably will. The question is whether you're treating your AI agents like tools or like employees with unvetted access to your entire operation. I close sensitive files before I open any agent. Not because I distrust the tool, but because I verify the access before I grant the trust. Every business has data it would not hand to a new hire without a background check and an NDA. Yet we are dropping desktop agents onto machines with auto-approved read access to everything — then calling it "Manual approval" because the write button asks nicely. That is not a security posture. That is hope. If you are using Kimi Work, or any local AI agent, audit what it can read before you worry about what it can write. Ask yourself whether "system-level digital employee" is a marketing phrase or an accurate description of the access you have just granted. The gap between those two definitions is where your risk lives.
Higgsfield brings Claude Fable 5.1 into 3D design Anthropic just rolled out Claude Fable 5.1, its new flagship model for coding and agentic work, and Higgsfield has already plugged it into a very specific use case: turning a written brief into a fully rendered 3D space. 🧩 According to Higgsfield, pairing Fable 5.1 with its own MCP infrastructure creates what the company calls the world's most advanced model for 3D spatial design and architectural modeling. The model reads a complex design brief and writes the underlying Three.js structure directly from that description, handling geometry, proportions, and navigation logic without anyone touching code by hand. 🏗️ Once the structure exists, Higgsfield MCP takes over the visual layer: photorealistic materials, lighting, and spatial models built on top of the code Fable 5.1 just generated. It's a two-step pipeline, one model plans the space, the other gives it texture, depth, and light. ⚙️ Higgsfield says the whole workflow is already live directly inside Claude through the Higgsfield MCP connector, and inside Higgsfield Supercomputer, so nobody has to jump between a separate modeling tool and a separate rendering engine mid project. 🌐 It's worth remembering that Fable 5.1 wasn't built for architecture. It's the same model Anthropic introduced just days ago as its most advanced system yet for coding and knowledge work in general, one that's reportedly better at long, complex programming tasks while also being more cost efficient to run. Seeing it redirected this fast toward a vertical use case like 3D spatial design shows how quickly the ecosystem around Claude is specializing through tools like MCP. For architects, game studios, and creative teams, this means moving from a written idea to a walkable digital space without opening traditional modeling software, a shift that's mostly about prototyping speed rather than replacing human design judgment. 💭 What strikes me here isn't really the announcement itself, it's how fast a model built for general coding and reasoning gets redirected toward something as specific as architectural modeling, and to me that's a sign the real value is shifting from the labs building base models to the companies that know how to wrap a usable vertical workflow around them almost overnight. For anyone working in design I think the real question is no longer whether to use these tools but how quickly you can integrate them without losing creative control over the final result, because a clearly written brief is still where all of this actually starts. 📱 Want AI updates on WhatsApp? DM me "AI" and I'll send you access. 🔔 Follow me for the last AI updates! #AInews #Higgsfield #ClaudeAI #3DDesign #GenerativeAI