GitHub开源工具：去AI味写作与自动化CRM工作流

I don't know about you, but I've been spending a lot more time on GitHub lately. And there's a real reason behind it. I mean, it's turned into one of the best places to get an unfair advantage in the Agentic era because you're seeing the tools people will be talking about in 6 months today. A lot of the things that eventually become SAS companies, agencies, workflows, and startup ideas show up there first. It's really like that uh famous quote, you know, uh the future is already here. it just isn't evenly distributed yet.

So, I'm trying something new with today's episode. I went through a ton of GitHub repos that have been getting attention over the last 30 days, and I picked the six that I think you should know about if you're trying to build products, if you're trying to make money, if you're trying to save time, or you just want to get more done with AI. Now, some are more technical than others, but I'll explain them all in plain English. you know what each one does, why it matters, how it actually use it, and how you can try it for yourself today.

The last one is from Nvidia. A couple of the other ones are from smaller devs, but every one of them is something I can picture someone using to make money or to save real time. All six are free and open source, meaning the code is free to use, but as a lot of you know, some have dependencies, like one has a dependency on 11 Labs, which does cost money. So, be aware of that. Uh, let's get into the episode. I'll see you at the end.

And if you haven't liked and commented and subscribed, just do it to get your algorithm pumping with a lot of valuable content like this. Let's go.

So, the first repo is my friend Peter Yang's no AI slop skill. And I like this one because everyone who uses AI for writing has felt this exact problem. I mean, you ask Chat GBT or claw to help you write something. It's a tweet. It's a LinkedIn post. And technically, the writing is fine, the grammar is fine, the syntax is fine, but it has this like weird smell to it. Maybe it sounds like too polish or too symmetrical or formulaic.

Um, sometimes it has like it's not X, but it's Y. uh you know or or uses the word quietly a lot. Um you know I think I feel like it feels like uh reading a keynote from a fake SAS conference and once you notice it I I feel like you can't unsee it. You know a lot of people are able to smell it now. So what's really cool is Peter Skill is basically an editor that strip strips those patterns out while trying to preserve your actual voice.

Um, the last part's important because a lot of the writing tools make your writing cleaner, but sand off the interesting parts and make everyone sound the same. And if you're going to sound the same, it's hard to stand out. Uh, you know, you you actually want to do the opposite. Um, so what's cool about uh this this uh repo is it hunts for the patterns that make writing feel AI generated and helps the draft feel like a real human being wrote it.

Uh, why does that matter? Like I said, if you're building products today, you're writing constantly and you want to stand out. You know, I I personally I'm writing tweets. I'm writing landing pages. I'm writing cold emails, uh, launch posts, product updates, onboarding copy. If you have investors, you're writing investor updates. And you don't want to sound like generic AI because, you know, people are going to feel it. uh they might not say this was written by AI, like they might not respond and say it.

Uh but they'll just trust you less. Um they're just going to keep scrolling. They're not going to reply. Uh they might even believe what you're saying because they're like, "This is AI written." So this repo isn't really about making writing nicer. It's it's really about making your communication more believable. So if you want to try this one, you can install it. You can install it as a skill. That's what I would do.

Uh, you know, you just type in npx skills add and then you put the GitHub link. And I'll include uh the link to the repo in the show notes in the description and actually all of them. So you can just go and do that. Then you can use it inside your agent workflow wherever you have a draft of it of something, right? So the practical way I would run it would be just to you know write a rough draft first. I wouldn't ask AI to invent the whole thing from scratch.

Uh just you know write like a an outline and get the real points down even if they're messy. And then you would ask the skill to remove the AI sanding patterns while keeping your voice. So that's the workflow to think about. you have a hu a human set of ideas first and then you have AI clean up second which is different than how a lot of people today are creating content uh they're just either asking AI to write everything basically trying to oneshot it uh and then and then ask saying hey this doesn't look good this doesn't look good um but this sort of like hybrid approach with the skill here super interesting um so there you go that's number one so the second repo is the is the CRM by try compai.

It's an open-source CRM built for AI agents. And that sounds a little technical and maybe boring. I'm going to try to break it down as simple as possible so you can understand how to actually get value out of this if you're building a business. A normal CRM is a place where you store your relationships and your customers and your leads. You know, it's basically a database with names, emails, and notes. Sometimes deal stages if people are using it for sales.

The problem is almost all of them depend on you doing the work. So you have to remember to update the person, you know, remember what happened last time, what they said, who went cold. Um, and just basically keep your CRM clean. Um, and because of that, uh, if you're anything like me, you you you've had a CRM and it's just turned into these graveyards that you just sort of stop updating. um it starts off really exciting and then a few weeks the data goes sta stale and the notes get messy and you just stop updating it and the people who could actually make you money end up sitting in a tool that nobody wants to open.

So what's interesting about this particular repo is that it treats your CRM as a workspace for an agent instead of a filing cabinet for you. So, the agent can look at records and research people and enrich company info. It could do uh scheduled follow-ups and then it could keep the notes current. All the stuff that basically you didn't want, you know, to do, it's it's going to it could do it for you and do those tasks.

The whole idea of this of this, you know, AI CRM is that it shouldn't just store information. It should maintain the relationship graph for you. Um, you know, it's a big deal if you're a founder. Um, because most businesses actually don't fail from a lack of opportunities. Um, a lot of times they fail uh because the opportunities are just scattered everywhere. You get this like warm intro maybe like 6 months ago or you said a you know you get like a feedback from a customer who says check back later and you forget about it.

Um, and there's real money sitting inside those in those emails. So the use case here isn't to replace uh Salesforce. Um not suggesting that um it's like a smaller useful use case. So the way I would do it is um say I I'm looking for sponsorships for my podcast. You know, I can run my sponsorship pipeline through it. Um you know, tracking agency leads. I can manage investor updates or if I have investors or I can follow up with everyone who's joined a wait list to a something that I've vibe coded or I can have it handle customer success uh just fully for a small SAS.

So if I were testing this, I would actually start with one small workflow. Uh I'd make a pipeline called something like warm leads I can't afford to forget. And then I'd drop in every person who shown any buying intent and then replied to any email or booked a call or ask about pricing or