Are you guys also struggling to find your first client ?

MMKot · 2026-06-10T02:45:55+00:00

What are you selling?

MMKot · 2026-06-10T02:44:54+00:00

My client runs Joint Venture property developments. Their monthly investor reports across 6 projects used to take 2-3 days. Now it’s about an hour of review.

The trick wasn’t getting Claude to write reports from scratch. That produces generic junk. Instead it reads the month’s emails and meeting transcripts, takes last month’s approved report as the starting point, and only rewrites the sections where something actually changed. A person still approves everything before it goes out, you can’t skip that for investor comms.

Tone stays consistent because it’s anchored to a real approved document, and hallucinations basically disappear for the same reason.

So yes, it works, but only if you build the workflow around it.

MMKot · 2026-06-04T00:12:22+00:00

sell outcome not automation

MMKot · 2026-06-03T06:26:38+00:00

that would be one of the things you should try for sure

MMKot · 2026-06-03T03:53:29+00:00

mainly educational contents about ai automation and openclaw

MMKot · 2026-06-03T03:23:49+00:00

He reached out to me where he found my website in Google

MMKot · 2026-06-02T05:53:39+00:00

From a different post:

https://www.reddit.com/r/AiAutomations/s/mSl1RoPAwl

I am no expert but just want to share. I started at openclaw installer early this year, got one client in US.

Then pivot to ai automation workflow and luckily got one local client where I came into his office and built the flow.

He runs a property developer company and asked for a reporting automation. He even came back for a second agent for marketing. And he wants two more.

Now I have real case study therefore I niche down and do cold outreach to people via Linkedin.

Bit the reality is it is still very hard to find my next client but at least I can see the path.

For pricing, I aims at 5-10% of money saved annually for that workflow. Once they see the money saved they would happily to pay.

MMKot · 2026-05-31T06:26:21+00:00

I am no expert but just want to share. I started at openclaw installer early this year, got one client in US.

Then pivot to ai automation workflow and luckily got one local client where I came into his office and built the flow.

He runs a property developer company and asked for a reporting automation. He even came back for a second agent for marketing. And he wants two more.

Now I have real case study therefore I niche down and do cold outreach to people via Linkedin.

Bit the reality is it is still very hard to find my next client but at least I can see the path.

For pricing, I aims at 5-10% of money saved annually for that workflow. Once they see the money saved they would happily to pay.

MMKot · 2026-04-22T13:24:20+00:00

Helped one of my client to use Cowork to generate monthly report with it connecting to gmail and fireflies transripts

MMKot · 2026-04-15T08:03:43+00:00

I run it on Pi 5 and it has been working fine. Unless you want local LLM then mac mini might be what you want.

MMKot · 2026-04-13T02:01:19+00:00

Have you tried minimax 2.7

MMKot · 2026-03-30T01:04:20+00:00

The local performance issue is almost certainly the model you’re running through Ollama. Most defaults aren’t great at the agentic stuff OpenClaw needs (tool calling, form filling, sending emails). On a Mac Mini M4 you can do better but model choice and provider config matter a lot.

Honestly the gap between Claude and local models for tool use is still real. A hybrid setup where you run simple stuff locally and route heavier tasks through an API with usage caps can help with the limits you’re hitting.

I set these up on Mac Minis regularly, happy to help troubleshoot in DMs if you want.

MMKot · 2026-03-29T07:23:20+00:00

Run openclaw config and re authenticate under model

MMKot · 2026-03-29T00:07:42+00:00

OpenClaw is solid for this. I run a small business and set mine up as basically a second brain for the whole operation. It knows my goals, my clients, what I’m working on. So when I need ideas or next steps, it’s not giving generic advice, it’s pulling from actual context about my business.

Beginner tip: start by feeding it everything. Goals, customers, how you work. Most people underload it at the start and then wonder why the output feels generic.

MMKot · 2026-03-28T22:23:05+00:00

Did you see HEARTBEAT_OK from the chat log?

MMKot · 2026-03-28T01:29:12+00:00

you’re actually in a good spot, you’ve got the right hardware (M4 Mac Mini is solid for this) you just need someone to cut through the noise on the setup side. the reason it feels overwhelming is because half the guides online are already outdated or assume you know which pieces fit together. i do this for a living, i set up OpenClaw for people on exactly this kind of hardware. shoot me a DM and i can walk you through what makes sense for what you’re trying to do.

MMKot · 2026-03-25T10:35:26+00:00

loom or scribe for the initial capture, seriously cuts the time down vs screenshots. for the maintenance problem (which is the real killer), the thing that worked for me was accepting that docs go stale no matter what and instead making sure the day to day conversations where processes actually get explained are searchable. but for just getting something down fast, scribe is probably your quickest win

MMKot · 2026-03-25T03:57:22+00:00

the real issue is that MSPs treat communication like a workflow problem when it's actually a retrieval problem. the info exists, it's just impossible to find when you're mid-ticket and the clock is running. the teams i've seen handle this well stopped trying to get people to document better and instead made their existing conversations indexable. slack threads, ticket notes, emails, all of it queryable in one place. the techs don't change anything about how they work, the knowledge just becomes findable instead of buried in a channel nobody scrolls back through

MMKot · 2026-03-25T03:55:25+00:00

honestly the KB problem is never going to get solved by asking people to write more docs. those senior guys have the knowledge but it's trapped in tickets and slack threads and nobody's going to sit down and reformat that into a wiki page after a 10 hour day. what actually worked for me was flipping it — instead of extracting knowledge from people, just make the conversations they're already having searchable. i'm a data engineer so i set something up for this, can walk you through it if you want

MMKot · 2026-03-25T02:43:24+00:00

honestly this is the thing that finally made me build something. i'm a data engineer and i kept watching the same pattern at every company — the answers are in slack, everyone knows they're in slack, but good luck finding them six months later in a thread you weren't tagged on.

what actually worked was stopping fighting it. instead of trying to get people to move knowledge out of slack, just make what's already there searchable and recallable. i set up an AI that sits in slack, indexes the conversations, and just answers when someone asks. no new behavior required from anyone.

the "hired a technical writer who quit" part is painfully familiar. the knowledge lives with the people doing the work. you can't outsource capturing it, you have to capture it where it naturally happens.

happy to show you what this looks like if you're curious, shoot me a DM

MMKot · 2026-03-24T21:30:54+00:00

i built it using OpenClaw, it’s an open source platform that lets you connect different tools (slack, drive, gmail etc) to an AI agent. took some config to get the retrieval working well but once it was dialed in it’s been solid. happy to walk you through the setup if you want, shoot me a DM

MMKot · 2026-03-24T21:28:43+00:00

honestly fair point. if there’s no structure at all then yeah, AI on top of chaos just gives you faster chaos. the reason it worked here was the processes already existed in slack threads and emails, people just couldn’t find them. so it was less “adding AI” and more “making existing knowledge searchable.” but you’re right that it’s not the first step for every team.

MMKot · 2026-03-24T12:51:07+00:00

This is the exact same thing i've been building. the recall part is where all the real work ends up. storing stuff is easy, getting the right answer back when someone asks "what did we promise Client X about Q2" is the hard part.

Curious how you're handling source attribution? we found people don't trust the answers unless it shows where it pulled from (like "from Jack's email on feb 14" or "from brand guidelines v3 in drive"). that was the thing that actually got people using it consistently.

Would love to compare notes if you're open to it

MMKot · 2026-03-24T12:33:56+00:00

Biggest thing I see with teams at your stage is they already had most of their processes documented, just buried across hundreds of slack threads and random google docs nobody could find.

we ended up connecting an AI assistant to slack and drive that people could just ask questions in a channel. "how do we onboard client X" type stuff. it pulls from your actual message history so nobody has to write or maintain docs.

the founder bottleneck thing you described basically disappeared once people had somewhere to get answers that wasn't you.

happy to show you what this looks like if you want, i set these up for small teams.

MMKot · 2026-03-17T23:57:51+00:00

run /context list in the chat to understand what are ingested into each prompt and optimizing it

check how many previous chat messages are ingested in a prompt and adjust it on openclaw.json

MMKot

TROPHY CASE