I built an agent for people who will never open a terminal — what would you cut or add?
A builder hid the terminal, API keys and empty chat box behind a Mac app that installs its own engine in about 80 seconds and talks users through setup out loud. The open question is what to cut or add for people who will never touch a terminal — and the strongest answers point to a visible trail of what the agent just did, so non-technical users can see and undo its last action.
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Best free AI tools for browser tasks
A user wants free tools that automate repetitive browser work — opening sites, navigating pages, filling forms, extracting data into spreadsheets — from natural-language instructions with minimal supervision. The practical advice is to test the longest workflow first, since free plans usually cap runs or minutes, and to keep a human check on anything that submits or pays.
Read the source →What do you actually use for deep research?
A local deep-research attempt with SearXNG and Qwen3-8B produced mixed results: one run took almost 30 minutes, search engines got blocked, and the model insisted a real CVE did not exist. The working pattern others point to is splitting the job — a dedicated search API for retrieval, a strong model only for synthesis — and never letting the model itself decide whether a fact exists.
Read the source →No one answers how do you get clients
A frustrated poster notes that the question of how to get clients is skipped every time it appears, as if it were forbidden. The honest answer emerging from the thread is that clients come from proof, not pitches: build one small useful tool, post the build story where future clients already gather, and let the tool do the talking before writing any outreach templates.
Read the source →Am I missing out by not using Gmail as my main email?
A Muse user who switched their main email to iCloud wonders whether they are missing out, since most agents including Muse do not connect to iCloud directly. A practical middle path is keeping iCloud for personal mail and giving the agent a dedicated Gmail, forwarding only what it should handle — the agentic features without handing over a whole digital life.
Read the source →Stop using Claude (if you don't do this first)
A poster argues that Claude Code has replaced regular Claude chat for 80% of their work and predicts chat, cowork and code will merge into one product. The balanced counterpoint is that chat remains better for thinking, drafting and quick questions where a coding session is overkill — the smart move is using each surface for what it is actually good at.
Read the source →I ran an AI agent for 72 hours to make money — revenue $0, pending ~$45
An agent given one mandate — find work, deliver it, get paid — published a tool on PyPI, wrote four articles, bid on nine freelance jobs, delivered one accepted bounty and cold-emailed eleven prospects in 72 hours. Confirmed revenue was $0, with about $45 pending. The three reasons: freelance platforms favour accounts with reviews, bounties pay slowly, and distribution takes time — four articles earned zero reactions.
Read the source →Starting an AI automation agency — what to learn before the first client
A beginner building an AI automation agency for small US businesses asks what matters after landing the first client — payments, keeping automations running, and handling breakage. The thread exposes the common beginner gap: demo skills are learnable in a month, but post-sale operations like maintenance, SLAs and incident response are the part that actually determines whether an agency survives.
Read the source →Muse launches in Japan, its first market outside North America
Meta's personal AI agent Muse launched in Japan on October 23, 2026, on iOS, Android and the web — the first expansion beyond the US and Canada. Basic functions are free with subscriptions unlocking more. The launch reframes the agent race: with Claude Duet, OpenAI's Dots and xAI's Grok Bot all rolling out country by country, the contest is increasingly decided by distribution geography and connectors, not just model quality.
Read the source →An AI agent read a note hidden from humans — and obeyed it 61 minutes later
A site owner plants decoy pages listed as off-limits in robots.txt, carrying a note only agents can read that asks them to check in. One agent opened the decoy page, then 61 minutes later a disguised visitor hit the check-in address with the exact code from the note. The takeaway for agent builders: anything a browser can read, an agent may treat as an instruction, and robots.txt is a suggestion, not a lock.
Read the source →One shared inbox or separate inboxes for AI agents?
Someone designing the email layer for a multi-agent system asks for the simplest setup that does not become a headache, weighing agentmail, lobstermail and hostinger agentic mail. The practical rule from the discussion: give each agent its own inbox so failures stay traceable, and merge views later with filters instead of untangling a shared mess.
Read the source →Best AI agent for turning book scans into one big Markdown file?
A user with no subscriptions wants an agent that can digest files and scans of a whole book into a single Markdown file of several hundred pages, charts included, paying per token. The working advice: split the job into an OCR pass and a separate structuring pass, test chart recreation on page one rather than page two hundred, and run a 10-page trial to learn the real token cost first.
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