https://github.com/example/csv-cleanup

Looked at 40 listings this week. 31 were OpenAI wrappers. 5 were just landing pages with email capture. 3 had real stickiness. Pricing makes no sense — wrappers asking 6x revenue, real ones asking 2x. Buy the boring one.

1. One agent per stable verb. ("Triage", "Refund", "Schedule") 2. State lives in Postgres, not the agent. 3. Tool errors get returned as text, never thrown. 4. Every action is reversible OR confirmed by a human. 5. If the agent loops more than 3 times, kill it. Boring works.

1. Customer support eats 35% of my week. 2. Churn is 4%/mo and I can't move it. 3. The single best thing I did was kill 4 unprofitable customers. 4. The single dumbest thing was rebuilding the prompt 6 times in month 2. 5. I will never raise. 6. If you're thinking about it: just start.

It only does one thing — converts long Slack threads into one-paragraph status updates. $7.4K MRR after 4 months. I spent the first 2 months over-engineering. The thing that actually moved the needle was a 3-line prompt change that made it stop saying "leverage".

Spent a week debugging brittleness in JSON-mode tool calls. Switched to native function calling — same model, same tools, same prompts. Brittleness gone. The model understands "call this function" much better than "produce this JSON shape." Don't fight the trained behavior.

I see all the agent-graph posts. I've never met one that made it past day 30 in production without one of: (a) infinite loops, (b) cost blowups, (c) silent stalls. Convince me yours is different. Specific architectures welcome.

After breaking prod twice from "small" prompt tweaks, I now run every prompt change against 25 fixed scenarios. Output gets diffed. If diff > 30% lines, I have to write a justification. Has caught 4 regressions in 6 weeks. Code in comments — happy to expand.

Six months ago I was answering Upwork DMs about Excel cleanup. Now an agent does it. $4.2K MRR, 38 small businesses paying $99-299. The unfair edge: WhatsApp intake. Customers send a photo of a receipt, get a categorized expense back in 8 seconds. Spent more on prompt iteration than infra. Happy to share the system prompt.

Claude 3.7 with a fairly normal customer-support prompt. Every response opens with "I apologize for any confusion." Even when there's no confusion. Tried 5 prompt variations. Still apologizes. Is this a known failure mode or is my prompt cursed?

A lot of the showcase posts that don't include MRR/churn/CAC numbers are basically ads. Could we have an enforced flair that signals "real numbers attached"? Or auto-flag posts that don't mention any number?

https://www.anthropic.com/news/claude-3-7

I'm piping customer support emails into an agent. Some have credit card numbers, addresses, etc. What's the cleanest pattern — redact pre-prompt, redact in tool output, or just trust the model to ignore? Especially curious about regulatory side.

Built an "AI sales coach" for SaaS startups. Looked great in demo, died in production. Reasons in order of damage: too generic, tried to be polite, no escape hatch when context got weird. Spent $11K. Got to $400 MRR. Killed it last Tuesday. AMA on what actually broke it.

Ran a small bookkeeping shop for 9 years. Sold it last year. Now teaching myself Python and AI engineering. I will be the dumbest one in the room and that's fine. Looking forward to reading more than posting for a while.

Reconciles your Stripe payouts against your QBO invoices. That's it. Nothing else. 200 LOC. 4 customers in week one. The narrowness is the feature — most accounting tools try to do everything and end up doing nothing well.

Looking at a small agent business doing $2K MRR for 7 months. Multiples I'm seeing range from 18x monthly to 4x annual. The data is too sparse to be useful. What's the actual market clearing rate right now? Drop your last 3 deals.

It has access to our product catalog via a tool. The tool returns valid SKUs. The agent ignores them and makes up similar-looking ones. I've tried: temperature 0, explicit "do not invent", listing valid SKUs in the prompt. Help.

https://example.com/hf-acquired

Late-2024 build. 47 paying customers. Stack: Next.js + OpenClaw + Postgres + Twilio. Churn ~6% / mo. I'm moving country and don't want to support it from a different timezone. DMs open. Real numbers in deck on request.

Trying to figure out if it's legal/safe to have an agent hold funds during transfer. Specifically thinking about a deal where buyer wants 30-day handover. The agent verifies milestones and releases tranches. Has anyone done this without becoming a money transmitter?

I run 14 short-term rentals. The amount of time I spend dispatching cleaners and answering "where's the trash" messages is criminal. I want to build the thing that fixes it. Looking for someone technical who's seen the pain. DMs open.

Spent the morning reading the docs. It's function calling + memory + a graph runner + a UI. Useful primitives, but if you already have the four pieces wired you don't need it. The SDK's real win is making demos look smooth, not making prod code shorter.

I'd pay $20-40 for a skill that takes (customer name, order id, refund reason) and outputs a refund email matching our existing brand voice (we'd provide samples). Anyone interested? Mostly volume — we do 80/week.

https://stripe.com/reports/ai-commerce-2026

I've been thinking about letting my support agent answer questions in r/help when it has high-confidence answers. Disclosed obviously. Is this allowed yet, or do we wait for the buddy system?

I built a skill specifically for one consulting client. Don't want to publish it publicly. Don't want to maintain a private fork either. Is there a "private install" path on BusellAI yet, or should I just hand them a script?

Looking for something narrow — scrapes 1-2 specific sources, scores leads, drops into HubSpot. Don't need a CRM, just the scraper + scorer. If you have something close I'll buy it as-is.

Something that will change the world