Grokbot or Muse? How to choose an AI agent platform on price-to-performance
A newcomer asks which multi-agent platform to commit to — Grokbot, Muse or another — with price-to-performance as the deciding factor. The practical answer emerging from the thread is to split jobs across tools rather than pay for three platforms at once, and to start on a free tier until a specific job keeps failing. Muse stands out as the strongest all-rounder for deep work, while cheaper platforms cover routine jobs.
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Absolute beginner learns vibe coding with free AI tools and a plan file
A student with no paid plans asks how to actually learn vibe coding. His current method — having ChatGPT write a master plan file, then handing it to a free agent — is already sound. The advice that fits: keep each prompt to one small feature, get the app running before asking for the next piece, and learn fastest by shipping tiny finished projects, ideally at hackathons.
Read the source →Which LLM gives the best results for AI agents and is cheap too?
After trying frontier models from OpenAI, Anthropic, Google and DeepSeek, a builder asks which LLM is both good and cheap for agents. The cost-saving pattern is routing by job: a fast cheap model for routine calls and a strong model only where reasoning matters. Most of the bill comes from long context, not the model tier, so short prompts and caching matter more than brand.
Read the source →Muse Windows web app opens links in the wrong Chrome profile — the fix
A Muse user on PC installed it as a Chrome web app and found every external link opening in the wrong Chrome profile. The cause is simple: a web app inherits the profile it was installed from. The fix is to uninstall it and reinstall from the intended profile, or launch Chrome with the --profile-directory flag pointed at muse.ai.
Read the source →Why Meta AI cannot check Reddit for answers the way ChatGPT can
A Meta AI app user asked for Reddit-only sources and got no Reddit links at all, while ChatGPT handled the same request. The gap is search coverage: Meta AI answers from its own index instead of opening Reddit threads. The workaround is to ask Muse, whose web search opens pages, or to paste the thread link directly and ask for a summary of that page.
Read the source →What do you re-explain to your AI every week? Start with what done means
An AI Agents group member asks what everyone keeps re-explaining to their AI each week. The most repeated item is the definition of done — agents drift on success criteria faster than on anything else. A short done-checklist in the instructions outlasts paragraphs of explanation, and restating which tools the agent may not touch is the other weekly repeat.
Read the source →Training bots: voice narration captures the reasoning, screen recording only captures clicks
A bot owner trains by taking over the bot screen, voice-chatting through each step, and letting the bot turn the session into skills and SOPs. The open question is the new Teach a Task feature, which records the screen but not audio, so the reasoning behind each step is lost. Voice narration plus a transcript pasted into instructions remains the stronger method for anything needing judgment.
Read the source →From walkthrough to bid in 20 minutes: voice capture in the field, AI structures it later
A contractor walks a job site talking into his phone while Gemini captures measurements, damage and the owners words, then hands the transcript to Claude to build a scope by trade plus the questions he forgot to ask. One AI for the field, one for the office — the write-up that used to eat the evening now takes about twenty minutes. The key move is asking the AI what it still needs, not just what it heard.
Read the source →Workflows io: AI-native agency grew from /bin/bash to .3M ARR in about a year
Workflows io, an AI-native go-to-market agency co-founded by Fivos Aresti in July 2025, reports reaching .3 million in annual recurring revenue with a team of 21 and no outside funding. The team deliberately held revenue flat for six months to build its foundation. The figure is self-reported through an interview, not payment-verified, but the model — selling AI workflows to businesses on setup fees plus retainers — is the agency path many solo builders are copying.
Read the source →Replayed: AI-assisted YouTube editing service at 6,945 in 30 days
Replayed sells on-demand YouTube video editing matched to each channels style, with AI assisting the matching and workflow while humans still do the editing. Its public profile reports 6,945 in revenue over the last 30 days and ,467 in monthly recurring revenue as of 9 November 2026. The gap between the two numbers is the caution: most revenue is one-off orders, not subscriptions.
Read the source →No-code consultant sells chatbot setups to small businesses: ,000+ in two months
A marketing consultant who cannot code built a chatbot for a skincare client drowning in repeat questions, charging 00 to refine and install it. Within a month there were three more clients at 50 to 00 each, plus a 0 monthly maintenance fee — six paying clients and over ,000 in revenue by month two. The figures are self-reported from a podcast episode, but the model needs almost no capital: chatbots answering repeat questions are the easiest AI service to sell to small businesses.
Read the source →Best multi-agent setup? Reviewing construction drawings with an agent team and an independent checker
A real estate developer wants a team of AI agents to review commercial construction drawings for errors, omissions and coordination issues between trades, with a second model independently checking the findings. The thread is a good example of multi-agent design in a high-stakes domain: split by trade, one lead agent, an independent checker, and a human sign-off on anything touching cost or safety.
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