Drop your preferred way of interacting with agents
A builder asks how people prefer to interact with AI agents: SMS, WhatsApp, chat, voice, or something else. The thread is a good snapshot of a real design question — the channel should match the reversibility of the task, with quick questions by voice and anything that spends or sends in writing where it can be reviewed.
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Is anyone actually using AI agents for a real reason?
A poster asks whether anyone uses AI agents for real work or if it is all hype, noting that most posts show multi-agent orchestrators and memory layers. The useful answers point to boring daily chores — triage, drafting, tracking what is due — with a human check before anything touches money or sends a message.
Read the source →How are you letting AI edit existing DOCX files without breaking the formatting?
A user asks where human review happens when an agent edits a DOCX: does the user see changes in an editor before saving, or download a new file to check. The practical answer is to never let the agent overwrite the original, ask for surgical edits only, and review tracked changes before anything ships.
Read the source →Are Hermes and OpenBot good for my workflow?
A newcomer doing code review, bug triage and feature work on GitHub asks whether Hermes or OpenBot would ease their workflow and how to configure them. The thread is a good entry point for anyone starting with coding agents: begin with one narrow job, keep a human as final approver, and pick the tool with the better GitHub integration.
Read the source →Muse email address use cases
A Muse user asks what a dedicated Muse email address is actually good for, beyond forwarding emails for it to act on. The key insight: mail sent to its own address keeps the sender context, while forwarded mail all arrives as if from the user. The main inbox stays connected for reading and drafting; the dedicated address is where automated mail lives.
Read the source →Don't reinstall Hermes because a plugin won't install. Update it.
Since November 9 the live Hermes plugin list has grown past the 2 MB the app accepts, so installs silently fall back to the old list the installed version shipped with — no error is shown. The fix shipped in v0.23.1: run hermes update, then install the plugin again. A useful reminder that a silent failure is worse than a loud one.
Read the source →Rezi: an AI resume builder at $239,000 MRR
Rezi is an AI resume builder for job seekers, earning $239,000 in monthly recurring revenue verified through TrustMRR payment data. It sits in the AI SaaS group, whose median is $19,800 MRR. The model is a narrow tool for one job people pay for monthly — but the resume niche is crowded with free competitors, and this figure is the top of its group, not a typical result.
Read the source →DM Champ: an AI sales agent platform at $55,300 MRR
DM Champ is an AI sales agent platform pitched as a way to start an AI agency in a week, earning $55,300 in monthly recurring revenue verified through TrustMRR. The pitch is selling a service, not software: the agent finds B2B buyers, writes outreach and books meetings. The caveat is that the first client and real delivery capacity matter far more than the tool itself.
Read the source →Reddit Agency: getting brands recommended by ChatGPT via Reddit at $38,000 MRR
Reddit Agency helps brands get recommended by ChatGPT and Google through Reddit — or the client does not pay — earning $38,000 in monthly recurring revenue verified through TrustMRR. It is a services business, where the median is $850 per customer per month. The risk is that results depend on opaque citation algorithms, and the line between genuine seeding and Reddit spam is thin.
Read the source →Muse models land on Google Cloud: Ember, Spark 1.3 and Wonder join Model Garden
Mark Zuckerberg announced that Muse Ember, Muse Spark 1.3 and Muse Wonder are now available on Google Cloud's Model Garden. It is the first time Muse models appear on a rival cloud, and the announcement also reveals Spark 1.3, a newer version than the Spark 1.1 launched days earlier. Ember is the low-cost model at $0.10 per million input tokens.
Read the source →New with AI things: where should a beginner start building a JARVIS?
A complete newcomer from Brazil asks how to start learning automation, APIs and AI agents while building a JARVIS-style assistant on a modest GTX 1650 PC. The thread is a good reminder that the best first step is one tiny working job, not a grand system. The discussion points beginners toward docs-first learning and one small build a week.
Read the source →Where to find real resources for building an AI operating system
A learner frustrated by YouTube videos that funnel viewers into paid Skool communities asks for trustworthy resources to build AI operating systems. The useful answer is to learn the agent loop first — model, tools, memory, orchestration — from free official docs, then build one small agent. The thread captures a common beginner trap: mistaking a sales funnel for a curriculum.
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