Meta tags:
description=I used to spend 3 hours a day on repetitive tasks. Now an AI agent handles them while I sleep. This... Tagged with ai, automation, productivity, tutorial.;
keywords=ai, automation, productivity, tutorial, software, coding, development, engineering, inclusive, community;

Headings (most frequently used words):

the, how, automated, dev, running, what, from, don, alert, my, entire, workflow, with, ai, agents, 24, on, mac, mini, community, gets, architecture, key, design, principles, real, example, inbox, monitor, full, stack, all, free, or, open, source, started, without, going, crazy, lessons, this, in, production, next, top, comments, automate, everything, act, local, first, cloud, fallback, fail, silently, loudly, more, sam, hartley,

Text of the page (most frequently used words):
the (24), dev (14), this (12), you (10), and (9), that (9), automation (9), agent (8), every (7), day (7), share (6), with (6), one (6), telegram (6), for (6), email (6), your (5), are (5), workflow (5), #automated (5), what (5), alert (5), before (5), inbox (5), api (5), min (5), hours (5), mac (5), mini (5), community (4), free (4), week (4), here (4), python (4), local (4), comments (4), was (4), check (4), cron (4), everything (4), running (4), how (4), don (4), month (4), data (4), calendar (4), cost (4), fullscreen (4), mode (4), prompt (4), create (3), software (3), open (3), use (3), code (3), bot (3), stack (3), first (3), devops (3), sam (3), hartley (3), abuse (3), will (3), post (3), via (3), something (3), things (3), setup (3), hour (3), all (3), monitoring (3), market (3), total (3), cloud (3), reasoning (3), ollama (3), qwen (3), llm (3), notification (3), tasks (3), automate (3), account (2), log (2), their (2), 2026 (2), built (2), source (2), conduct (2), about (2), home (2), live (2), rule (2), work (2), more (2), from (2), mar (2), building (2), follow (2), hide (2), want (2), comment (2), still (2), report (2), preview (2), subscribe (2), set (2), like (2), own (2), have (2), parts (2), others (2), automating (2), can (2), powered (2), next (2), isn (2), thinking (2), doesn (2), checking (2), when (2), logs (2), build (2), once (2), working (2), add (2), feed (2), alerts (2), notifications (2), just (2), checker (2), job (2), paying (2), monthly (2), browser (2), inference (2), full (2), review (2), manually (2), time (2), saved (2), scam (2), detection (2), new (2), messages (2), monitor (2), not (2), them (2), weather (2), customer (2), instant (2), phone (2), model (2), handles (2), there (2), exit (2), enter (2), response (2), complex (2), only (2), tells (2), after (2), need (2), human (2), reminders (2), hourly (2), watch (2), face (2), now (2), entire (2), agents (2), copy (2), link (2), search (2), place, where, coders, stay, date, grow, careers, made, love, 2016, ruby, rails, powers, other, inclusive, communities, forem, terms, privacy, policy, mlh, shop, postgres, database, contact, showcase, organization, accounts, advertise, help, education, tracks, videos, challenges, space, discuss, keep, development, manage, career, paper, trading, went, guardrail, timeout, means, makes, approval, gates, actually, scheduled, ran, times, did, nothing, assertion, fixed, joined, developer, setups, bots, smartwatch, apps, further, actions, may, consider, blocking, person, reporting, confirm, child, well, sure, become, hidden, but, visible, permalink, dismiss, submit, templates, let, quickly, answer, faqs, store, snippets, template, trusted, user, personal, top, daily, tips, celebibot_en, business, service, too, custom, workflows, thing, tackled, drop, genuinely, curious, based, version, signals, rules, same, sounds, interesting, along, stopped, worrying, forgetting, value, speed, offloading, mental, overhead, scaling, works, yours, look, different, test, actual, replaces, mechanical, replace, minute, wastes, resources, fine, most, intervals, matter, fails, logging, lessons, production, lesson, trying, end, half, mess, trust, start, get, reliable, then, orchestrated, together, game, changer, added, suddenly, could, see, script, didn, weekend, honest, timeline, started, without, going, crazy, 150, costs, anthropic, safari, accessibility, apis, eventkit, macos, apple, mail, cli, bridge, access, jobs, scripts, orchestration, tool, component, 100, far, pattern, matching, analysis, responding, days, false, positives, rate, junk, moves, quietly, legitimate, sends, checks, against, known, spam, patterns, regex, scans, opens, real, example, failures, equal, treat, way, down, who, cares, fail, silently, loudly, perfectly, zero, simple, message, does, say, urgent, complete, claude, rare, else, qwen3, generate, private, query_is_simple, fallback, wrong, destroy, client, relationship, excellent, great, nuance, needs, attention, reply, customers, send, emails, make, purchases, act, tried, replies, clients, deleted, some, touch, decisions, judgment, creative, relationships, formatting, applies, hard, key, design, principles, additional, already, hits, hardware, always, orchestrator, scanner, fiverr, orders, fetcher, general, coder, 30b, network, gpu, layer, background, services, garmin, system, health, architecture, got, back, websites, leave, app, proactive, forget, constantly, seconds, per, automatic, triage, manual, task, gets, concept, right, office, picture, used, spend, repetitive, while, sleep, tutorial, productivity, posted, mastodon, facebook, linkedin, copied, clipboard, pick, gem, boost, save, jump, fire, raised, hands, exploding, head, unicorn, reaction, close, algolia, navigation, menu, skip, content,

Text of the page (random words):
how i automated my entire dev workflow with ai agents running 24 7 on a mac mini dev community skip to content navigation menu search powered by algolia search log in create account dev community close add reaction like unicorn exploding head raised hands fire jump to comments save boost pick as gem more copy link copy link copied to clipboard share to x share to linkedin share to facebook share to mastodon share post via report abuse sam hartley posted on mar 15 how i automated my entire dev workflow with ai agents running 24 7 on a mac mini ai productivity tutorial automation i used to spend 3 hours a day on repetitive tasks now an ai agent handles them while i sleep this isn t a concept post this setup is running right now on a mac mini in my home office here s the full picture what gets automated task before manual after ai agent email triage 30 min day automatic code review 45 min day 12 seconds per pr customer inbox check 20 min day hourly cron job calendar reminders forget constantly proactive alerts weather check open app manually agent tells me before i leave market data check 5 websites live on my watch face total time saved 2 5 hours day that s 75 hours a month i got back the architecture mac mini m4 always on ai agent orchestrator email checker hourly calendar scanner every 4 hours inbox monitor fiverr orders every hour market data fetcher every 15 min ollama local llm free inference qwen 3 5 9b general tasks qwen 3 coder 30b via network gpu notification layer telegram bot my phone background services garmin watch face data feed system health monitoring enter fullscreen mode exit fullscreen mode total hardware cost 0 additional mac mini was already there monthly api cost 25 only complex reasoning hits the cloud key design principles 1 don t automate everything the 80 20 rule applies hard automate checking monitoring formatting reminders don t automate decisions that need judgment creative work human relationships i tried automating replies to clients once deleted it after day one some things need a human touch 2 alert don t act my agent tells me when something needs attention it doesn t reply to customers send emails or make purchases one wrong automated email can destroy a client relationship ai is excellent at detection it s not great at nuance 3 local first cloud fallback if query_is_simple prompt free instant private response ollama generate model qwen3 5 9b prompt prompt else rare complex reasoning only response claude complete prompt enter fullscreen mode exit fullscreen mode 95 of automation tasks are simple is there a new message what does it say is it urgent a 9b model handles that perfectly at zero cost 4 fail silently alert loudly if the weather api is down no notification who cares if a paying customer messages instant alert to my phone not all failures are equal treat them that way real example the inbox monitor every hour the agent opens the browser inbox scans for new messages checks against known spam scam patterns regex ai if legitimate sends me a telegram notification with the preview if junk logs it and moves on quietly scam detection rate 100 so far pattern matching llm analysis false positives 0 i still review every alert manually before responding time saved 20 min day 30 days 10 hours month the full stack all free or open source component tool cost llm inference ollama qwen 3 5 0 orchestration cron jobs python scripts 0 notifications telegram bot api 0 email access apple mail cli bridge 0 calendar eventkit macos 0 browser automation safari accessibility apis 0 cloud reasoning 10 anthropic api 25 mo monthly total 25 before this setup i was paying 150 just in api costs how i started without going crazy i didn t build this in a weekend here s the honest timeline week 1 just the email checker one script one cron job week 2 added telegram notifications suddenly i could see it working week 3 calendar alerts this was a game changer month 2 inbox monitoring market data feed month 3 everything orchestrated together the lesson start with one automation get it reliable then add the next trying to build everything at once is how you end up with a half working mess you don t trust lessons from running this in production logging is everything when something fails at 3 am logs are all you have cron intervals matter checking email every minute wastes resources every hour is fine for most things ai doesn t replace thinking it replaces the mechanical parts of thinking test on your actual workflow before scaling my setup works for me yours will look different the value isn t speed it s offloading mental overhead i stopped worrying about forgetting to check things what s next i m building a telegram based version of this that others can use subscribe to signals set their own alert rules powered by the same local ai stack if that sounds interesting follow along have you automated parts of your workflow what was the first thing you tackled drop it in the comments i m genuinely curious what others are automating if you want to set something like this up for your own workflow or business i do this as a service too custom ai automation workflows daily automation tips t me celebibot_en top comments 0 subscribe personal trusted user create template templates let you quickly answer faqs or store snippets for re use submit preview dismiss code of conduct report abuse are you sure you want to hide this comment it will become hidden in your post but will still be visible via the comment s permalink hide child comments as well confirm for further actions you may consider blocking this person and or reporting abuse sam hartley follow developer building local ai setups telegram bots and smartwatch apps joined mar 7 2026 more from sam hartley my scheduled agent ran 40 times and did nothing here s the assertion that fixed it ai devops python automation timeout means no the one rule that makes ai agent approval gates actually work ai python automation devops my paper trading bot went live this week here s the guardrail stack i built first ai python devops automation dev community a space to discuss and keep up software development and manage your software career home dev challenges dev videos dev education tracks dev help advertise on dev organization accounts dev showcase about contact free postgres database dev shop mlh code of conduct privacy policy terms of use built on forem the open source software that powers dev and other inclusive communities made with love and ruby on rails dev community 2016 2026 we re a place where coders share stay up to date and grow their careers log in create account