@keeper_dota2: #ВэтотДень #dota2 #dota #дота2 #дота

Хранитель Дота 2
Хранитель Дота 2
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Region: US
Friday 09 October 2026 08:19:41 GMT
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i0qoriginal
Orotimaru :
сбежал от ама дк и шейкера
2026-10-09 10:08:19
8
keeper_dota2
Хранитель Дота 2 :
кому не трудно, оцените ролики в закрепе 🥺 буду благодарен за лайк и подписку, и приходите на стримы 😇 кто хочет пообщаться или вместе поиграть, пишите в вк или тг, ссылки в профиле
2026-10-09 08:27:23
0
d00mka152
d00mka152 :
Наконец-то знающий человек собрал октарин, а никто не сказал "ыыыы что за слот"
2026-10-09 14:57:02
0
bratstylaabama1
брат стулки :
интересный слот слева от линки
2026-10-09 09:39:10
1
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How to automate bookkeeping with AI: the whole system for a bookkeeping firm How to automate bookkeeping with AI for a real bookkeeping firm, step by step. Tess runs Copperline Bookkeeping: 55 landlord and house-flipper clients, 4 bookkeepers, 312 transactions waiting. She wants 100 clients without hiring 4 more people. Her team clicks through every bank transaction in QuickBooks Online. QuickBooks rules handle the easy ones. When she pasted a month of charges into ChatGPT, it put a $1,186 Lowe's charge on a rental. It belonged to the house being renovated. Same receipt, three right answers: an upgrade on a renovation, a repair on a rental, a cost that waits on a flip. The missing piece was the stage of the house. The AI bookkeeping system, built as building blocks: 1. Memory (Supabase). Clients, houses with a stage (renovating, rented, flipping, buying or selling), each client's category list from QuickBooks, rules that only run once a person signs them, every approved decision with its reason, and your written procedures, searchable by meaning. 2. Engine (n8n, on a computer you control). A watcher, a thinker and a poster. Plaid pulls each bank account every morning and skips pending charges. QuickBooks' own bank download is switched off so nothing comes in twice. The poster is the only thing allowed to write into QuickBooks, with a unique request ID so nothing posts twice. 3. Brain (Claude, called last). First match wins: a client rule, an investor-type rule, a firm rule. Only then do the rulebook pages and 3 past decisions go to Claude, which fills the same form every time: category, house, how sure, why, question. Before anything leaves, a step in n8n swaps names for codes (Marcus becomes Client 14, Garnet Street becomes House B) and puts them back after. Claude runs under Anthropic's business API terms, with no training on your data. 4. Checks, then two lanes. Green: a signed rule, every check passed, a small amount, so it posts itself. Orange: new, big, unsure, or a buy, sell or refinance waits in QuickBooks under Needs Review for a person. 5. One dashboard, two views, built with Claude Code on Supabase. Clients answer questions with one tap, split a charge, set each house's stage, upload documents and read reports. Bookkeepers see what's waiting, who changed what, the rules, and a green
How to automate bookkeeping with AI: the whole system for a bookkeeping firm How to automate bookkeeping with AI for a real bookkeeping firm, step by step. Tess runs Copperline Bookkeeping: 55 landlord and house-flipper clients, 4 bookkeepers, 312 transactions waiting. She wants 100 clients without hiring 4 more people. Her team clicks through every bank transaction in QuickBooks Online. QuickBooks rules handle the easy ones. When she pasted a month of charges into ChatGPT, it put a $1,186 Lowe's charge on a rental. It belonged to the house being renovated. Same receipt, three right answers: an upgrade on a renovation, a repair on a rental, a cost that waits on a flip. The missing piece was the stage of the house. The AI bookkeeping system, built as building blocks: 1. Memory (Supabase). Clients, houses with a stage (renovating, rented, flipping, buying or selling), each client's category list from QuickBooks, rules that only run once a person signs them, every approved decision with its reason, and your written procedures, searchable by meaning. 2. Engine (n8n, on a computer you control). A watcher, a thinker and a poster. Plaid pulls each bank account every morning and skips pending charges. QuickBooks' own bank download is switched off so nothing comes in twice. The poster is the only thing allowed to write into QuickBooks, with a unique request ID so nothing posts twice. 3. Brain (Claude, called last). First match wins: a client rule, an investor-type rule, a firm rule. Only then do the rulebook pages and 3 past decisions go to Claude, which fills the same form every time: category, house, how sure, why, question. Before anything leaves, a step in n8n swaps names for codes (Marcus becomes Client 14, Garnet Street becomes House B) and puts them back after. Claude runs under Anthropic's business API terms, with no training on your data. 4. Checks, then two lanes. Green: a signed rule, every check passed, a small amount, so it posts itself. Orange: new, big, unsure, or a buy, sell or refinance waits in QuickBooks under Needs Review for a person. 5. One dashboard, two views, built with Claude Code on Supabase. Clients answer questions with one tap, split a charge, set each house's stage, upload documents and read reports. Bookkeepers see what's waiting, who changed what, the rules, and a green "engine ran" light. 6. Documents. Receipts go to a receipts inbox. Docling reads them on your own machine, the same name swap runs, Claude pulls store, date and amount, and the bank match allows 5 days either way. Loan statements get split into principal, interest and escrow. Closing statements become one big entry a bookkeeper checks. Property-manager payouts get grossed up into rent, fee and repairs. 7. It learns. Five matching approvals become a draft rule a person signs. The AI suggests, a person switches it on. 8. Month-end on the third workday: reminders, bank statement matching (the month stays open until every account is matched), then reports with your notes. The bookkeeper reviews and sends. You don't build it all at once. Memory first, then the daily engine on 3 clients next to how you do it now, then the dashboard, then documents, month-end and learning. The hard part isn't the AI. It's one dropdown that says what stage each house is in, and writing down what your team already knows. #aiautomation #aiemployee #aiagents #bookkeeping

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