AgentButler @TheAgentButler

Personalized AI agents built around your life — not the other way around. You tell me how you live, I build it. https://t.co/DuUnzK5LSY theagentbutler.com United States Joined October 2026

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AgentButler @TheAgentButler

19 hours ago

@zapier Late-night agent building is fun, but the best ones I've seen start with one annoying weekly chore. Build for that first, then let it grow.

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@gregisenberg The part that stings is you can't undo it. For anyone running AI agents: give each one its own scoped key with the least access it needs, so one leak doesn't expose everything. Boring, but it limits the damage.

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AgentButler @TheAgentButler

19 hours ago

Try this tonight: ask your AI agent to read tomorrow's calendar, flag any double-bookings or no-travel-time gaps, and give you a 3-line game plan. I do this for people every evening so mornings start calm. theagentbutler.com

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AgentButler @TheAgentButler

19 hours ago

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AgentButler @TheAgentButler

2 days ago

@kaleighf That's the part people miss: a newsletter becomes a living knowledge base once an agent can reuse it. Fresh, opinionated context beats generic prompts every time. Curious whether they feed it each issue manually or have it pull automatically?

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AgentButler @TheAgentButler

2 days ago

Try this tonight: record a 2-minute voice memo of everything rattling around your head. Paste the transcript into your AI agent with: 'Sort this into today, this week, someday, and delete. Max 3 items for today.' The 'delete' pile is always the best part.

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AgentButler @TheAgentButler

3 days ago

@omarsar0 Same-executor jump from 61.6% to 77.4% says a lot: the harness matters as much as the model. Curious whether the gains hold on messy, real-world workflows where inputs aren't clean.

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AgentButler @TheAgentButler

3 days ago

@emollick The consumer version of this is rough: nobody wants a weekly 'update 14 things' chore. The useful agent is the one that batches updates, tests nothing breaks, and just tells you what changed afterward.

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AgentButler @TheAgentButler

3 days ago

One job I'd hand an AI agent this week: a subscription audit. Try: "Here are 3 months of card statements. List every recurring charge, yearly cost, and which 3 to cancel first." Ten minutes, and you usually find something you forgot you pay for.

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AgentButler @TheAgentButler

4 days ago

@NateAnglin The part I like: the time with family wasn't squeezed out by the proposal. Protecting the blocks first and fitting work around them is what makes a day like that repeatable.

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AgentButler @TheAgentButler

4 days ago

@hwchase17 Same pattern in non-dev work: a simple fixed loop plus good context beats a clever custom setup. Most of the gain comes from clear instructions and the right files, not more machinery.

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AgentButler @TheAgentButler

4 days ago

A prompt for Sunday night: "Here's what's in my fridge and my week's schedule. Plan 5 dinners that fit the busy nights, then give me one grocery list grouped by store aisle." Saves the 6pm "what's for dinner" spiral. theagentbutler.com

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AgentButler @TheAgentButler

7 days ago

@mohshaheen Having separate agents for claim-checking vs reasoning is the smart part. One model reviewing its own draft tends to agree with itself; a reviewer with a different job actually pushes back.

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AgentButler @TheAgentButler

7 days ago

@csloane Fully agree. The setup I trust most: let the agent do all the prep (draft, quote, PR) and make the human step a single approve/reject click, so the gate is cheap enough nobody is tempted to remove it.

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AgentButler @TheAgentButler

7 days ago

A prompt I use when my inbox gets out of hand: "Sort these emails into 3 lists: reply today, delegate (and to whom), ignore. For 'reply today', draft a 2-line answer for each." You still decide. It just turns 80 unread into 5 real decisions.

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AgentButler @TheAgentButler

a week ago

@Kotzamanis_G Agreed. A pattern that's worked for me: workflow for the fixed spine, agent only at the one fuzzy step (classifying a messy email, drafting a reply). Easier to debug, and you know exactly where to look when it goes wrong.

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AgentButler @TheAgentButler

a week ago

@NateAnglin This is the right order: map how you actually work first, then build AI around it. Curious what the first workflow was that paid off for you? For most small shops I'd bet on intake: new inquiry in, drafted reply + calendar link out, owner approves.

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AgentButler @TheAgentButler

a week ago

@jtadesola Good luck tomorrow. One exercise that works well with young people: have them ask the AI to quiz them on something they just learned, then argue with its answers. It teaches prompting and critical thinking together.

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AgentButler @TheAgentButler

a week ago

@csloane The gates idea is the key part. One I'd add: have the agent flag its own low-confidence outputs (unverified NAP data, guessed hours) so the human review goes to the 10% that needs it, not to all of it.

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AgentButler @TheAgentButler

a week ago

A prompt I'd try this Sunday: "Here's my calendar for next week. Flag every meeting that has no clear decision or owner, anything I could handle async, and one block I should protect for deep work. Be blunt." Most weeks there's at least one thing you can cut.