I've been bullish on SEO (and GEO) in the last few months and I think that the useful "hygiene" tasks of a good SEO are also the ones people never commit to, because they're boring/time-consuming.

So I went on a journey to automate them using an SEO agent (mostly, packaged them into one), but here are the main capabilities that could be useful to you too:

1. Keyword-opportunity agent

Every week, the agent pulls your target keywords, your striking-distance queries in Search Console, and the gaps your competitors aren't targeting. Then it hands you 3 article ideas, each with a scored rationale and an H2 outline.

2. Article-drafting agent

(this one is pretty basic but it has a forcing function)

You give the agent a topic of your choice and then it writes a full article with your rules. For me the rules for instance are: brand-first positioning, internal links to the right pages, FAQ schema, a closing CTA.

Usually the ideas come a bit naturally based on my readings and competitive intelligence.

3. The page-2-to-page-1 agent

Once a month it finds the pages ranking 11 to 20 and tells you what to fix to push them to rank 1-10. These are usually the cheapest wins in SEO, because the content already ranks and just needs a nudge. They are also the ones I forget to go back to. I think it's the one that really moved the needle.

4. Content refresh agent

Freshness is a ranking signal, and stale stats / links are taking the piece of content's position. This agent is watching the best posts for decay, flags when there are outdated numbers / aging sections / broken links. The agent can correct this by itself ideally.

5. Competitor-watch agent

The agent monitors your named competitors (I suggest you find 3-4 who are the most "dangerous" and not more). Then it scores anything they published in the last seven days against your keywords, and flags the threats with a suggested response. This is the work a human means to do every week and never does.

6. GEO "basics" agent

I know GEO is way more than that but I think it's a good first step to have well-structured data and kill two birds with one stone. This agent is structruging content the way AI engines extract it: definitional sentences they can quote cleanly, FAQ schema they parse, original data they can attribute. The same article that ranks on Google also starts to get cited by ChatGPT, Perplexity, etc.

Any other ideas I didn't mention? I think you don't need a separate agent for all those use cases but...you could as well. I chose to have only one that manages everything.

I think that the useful "hygiene" tasks of a good SEO are also the ones people never commit to, because they're boring/time-consuming.

So I went on a journey to automate them using an SEO agent (mostly, packaged them into one), but here are the main capabilities that could be useful to you too:

1. Keyword-opportunity agent

Every week, the agent pulls your target keywords, your striking-distance queries in Search Console, and the gaps your competitors aren't targeting. Then it hands you 3 article ideas, each with a scored rationale and an H2 outline.

2. Article-drafting agent

(this one is pretty basic but it has a forcing function)

You give the agent a topic of your choice and then it writes a full article with your rules. For me the rules for instance are: brand-first positioning, internal links to the right pages, FAQ schema, a closing CTA.

Usually the ideas come a bit naturally based on my readings and competitive intelligence.

3. The page-2-to-page-1 agent

Once a month it finds the pages ranking 11 to 20 and tells you what to fix to push them to rank 1-10. These are usually the cheapest wins in SEO, because the content already ranks and just needs a nudge. They are also the ones I forget to go back to. I think it's the one that really moved the needle.

4. Content refresh agent

Freshness is a ranking signal, and stale stats / links are taking the piece of content's position. This agent is watching the best posts for decay, flags when there are outdated numbers / aging sections / broken links. The agent can correct this by itself ideally.

5. Competitor-watch agent

The agent monitors your named competitors (I suggest you find 3-4 who are the most "dangerous" and not more). Then it scores anything they published in the last seven days against your keywords, and flags the threats with a suggested response. This is the work a human means to do every week and never does.

6. GEO "basics" agent

I know GEO is way more than that but I think it's a good first step to have well-structured data and kill two birds with one stone. This agent is structruging content the way AI engines extract it: definitional sentences they can quote cleanly, FAQ schema they parse, original data they can attribute. The same article that ranks on Google also starts to get cited by ChatGPT, Perplexity, etc.

Any other ideas I didn't mention? I think you don't need a separate agent for all those use cases but...you could as well. I chose to have only one that manages everything.

I think that the useful "hygiene" tasks of a good SEO are also the ones people never commit to, because they're boring/time-consuming.

So I went on a journey to automate them using an SEO agent (mostly, packaged them into one), but here are the main capabilities that could be useful to you too:

1. Keyword-opportunity agent

Every week, the agent pulls your target keywords, your striking-distance queries in Search Console, and the gaps your competitors aren't targeting. Then it hands you 3 article ideas, each with a scored rationale and an H2 outline.

2. Article-drafting agent

(this one is pretty basic but it has a forcing function)

You give the agent a topic of your choice and then it writes a full article with your rules. For me the rules for instance are: brand-first positioning, internal links to the right pages, FAQ schema, a closing CTA.

Usually the ideas come a bit naturally based on my readings and competitive intelligence.

3. The page-2-to-page-1 agent

Once a month it finds the pages ranking 11 to 20 and tells you what to fix to push them to rank 1-10. These are usually the cheapest wins in SEO, because the content already ranks and just needs a nudge. They are also the ones I forget to go back to. I think it's the one that really moved the needle.

4. Content refresh agent

Freshness is a ranking signal, and stale stats / links are taking the piece of content's position. This agent is watching the best posts for decay, flags when there are outdated numbers / aging sections / broken links. The agent can correct this by itself ideally.

5. Competitor-watch agent

The agent monitors your named competitors (I suggest you find 3-4 who are the most "dangerous" and not more). Then it scores anything they published in the last seven days against your keywords, and flags the threats with a suggested response. This is the work a human means to do every week and never does.

6. GEO "basics" agent

I know GEO is way more than that but I think it's a good first step to have well-structured data and kill two birds with one stone. This agent is structruging content the way AI engines extract it: definitional sentences they can quote cleanly, FAQ schema they parse, original data they can attribute. The same article that ranks on Google also starts to get cited by ChatGPT, Perplexity, etc.

Any other ideas I didn't mention? I think you don't need a separate agent for all those use cases but...you could as well. I chose to have only one that manages everything.

I went through YC (2x!), raised $10M, and now we have thousands of users on our platform.

That being said I think it's important to remind everyone that YC doesn't save you from failing sometimes.

I wanted to share a story about one of the worst webinars I ever hosted yesterday

Yesteday, a member of my team and I hosted a live webinar for our new AI SEO agent. Out of 54 people who signed up, only 6-7 actually showed up... and they got a front-row seat to a (really) bad experience.

Here is what we messed up:

1. Currently there's a huge heatwave -> My laptop was overheating so badly the UI ground to a halt. I couldn't click tabs or load integrations.
2. Recording issue -> We realized before the call that we didn't have admin rights to record the webinar. So I fired up Quicktime to record the screen on my computer and it fried the remaining part of my CPU :')
3. AI Agent went rogue (more or less) -> The agent I had set up for the demo and tested 40 times stopped mid task because I was frantically reloading the page, and then it spawned a second thread and started recoding live on screen. That was not in the script :')
4. Because of the lag, we spent like 40 minutes sitting in silence while the agent processed, instead of switching to a backup plan.

So guess what... we lost momentum quickly while the 7 people were going on with their lives.

Now what happened next: the panic wore off and we took this as an opportunity instead. Here's the process in case it happens to you as well:

1. Personal apologies -> We've emailed all 7 attendees individually to apologize for the terrible experience.
2. Direct Loom -> We sent each of them a personalized Loom showing the agent actually running smoothly when my laptop isn't melting.
3. Free credits -> we credited their accounts with $100 so they can play with it without risk.

One piece of advice: we/you shouldn't be live-building in a webinar. Show the outcome first, explain the magic after, but don't go into the inner workings of your product if you want to avoid

(Also - buy a fan that can cool down your computer when there's a heatwave, lol)

If you ever bombed a live demo, please share your story. I need to feel less alone in this :')

Imagine the situation: you spend weeks prepping a webinar, you run 40 tests in staging, and the MOMENT you go live, the universe decides to humble you.

Yesterday, a member of my marketing team and I hosted a live-building webinar for our new AI SEO agent and it's been an absolute disaster.

Out of 54 people who signed up, only 6-7 actually showed up... and they had a front-row seat to a slow-motion car crash :')

Here is what we messed up and how you can avoid being in the same situation:

1. Currently there's a huge heatwave-> My laptop was overheating so badly the UI ground to a halt. I couldn't click tabs or load integrations.
2. Recording issue -> We realized before the call that we didn't have admin rights to record the webinar. So I fired up Quicktime to record the screen on my computer and it fried the remaining part of my CPU :')
3. AI Agent went rogue (more or less) -> The agent I had set up for the demo and tested 40 times stopped mid task because I was frantically reloading the page, and then it spawned a second thread and started recoding live on screen. That was not in the script :')
4. Because of the lag, we spent like 40 minutes sitting in silence while the agent processed, instead of switching to a backup plan.

So guess... we lost momentum quickly while the 7 people were going on with their lives.

Now what happened next: the panic wore off and we took this as an opportunity instead. Here's the process in case it happens to you as well:

1. Personal apologies -> We've emailed all 7 attendees individually to apologize for the terrible experience.
2. Direct Loom -> We sent each of them a personalized Loom showing the agent actually running smoothly when my laptop isn't melting.
3. Free credits -> we credited their accounts with $100 so they can play with it without risk.

Also one piece of advice (but I guess you're already wiser than I am): we/you shouldn't be live building in a webinar. Show the outcome first, explain the magic after, but don't go into the inner workings of your product if you want to avoid

(Also - buy a fan that can cool down your computer when there's a heatwave, lol)

If you ever bombed a live demo, please share your story. I need to feel less alone in this :')

Hey,

I've joined Y Combinator for my startup and the one advice that was given to me and changed how I run sales was to cut the time between "first conversation" and "they get it." (ie. reduce the time-to-value in a sales meeting)

I never present slides in a sales meeting, because they delay the moment where the other person actually feels what the product does.

You spend 20 minutes on slides and then, if you're lucky, they ask a question that tells you what they actually cared about the whole time 😬

So now I start every meeting with questions. What are you struggling with? What's taking longer than it should?

Once I have enough to work with,I choose one of these paths.

Path 1 is to build something live.

If I have a decent read on their problem and I know I can put something together in 15 minutes, I'll do it, right there during the call. Nothing I've ever shown on a slide comes close to watching someone's face when you solve their actual problem in real time.

Path 2 is a demo (but not a canned walkthrough)

Something close enough to their situation that they can picture themselves using it. Either way, the goal is the same: make the value feel real before the call ends.

One recent example I can share: I was talking to a founder interested in using my product as a general OS for his company, but he said he wanted to push a few weeks because he was fundraising and didn't have the bandwidth.

Instead of trying to convince him, I shared my screen. I showed him the AI agent I use to get 10 investor intros a week. It's crawling my investors' networks, flags relevant connections and drafts an outreach. It takes me only a few minutes to review and send.

Doing discovery helped me undeestand that was on that call because he needed that kind of agent. (One of those intros led him there!)

He started explaining he'd do the same for his own raise, pulling from his investors, mentors, former colleagues, etc

By the end we had spent 20 minutes only talking about fundraising, and he didn't talk about pushing the timeline anymore. He signed 2 minute sbefore the end of the call ☺️

So either way:

1/ Listen
2/ Build something custom or Demo something relevant

As we say at YC: "Make something people want"!

Hi everyone,

Wanted to share some insights on my experience driving goals after raising $30M over two startups and making way too many mistakes.

In my first company, I raised $20M and we grew to 70 people. I learned a lot the hard way. Today, I'm a year into our second company where we raised a $10M seed.

One thing I realized being a second-time founder is that you need to solve what I call "secondary-class challenges" quickly. These are the operational systems you need to run the company. They aren't headline struggles like product-market fit, but you don't want them sucking your bandwidth or slowing you down.

For us, Weekly Goals (aka WGs) became the single most important driver of execution. I think that they are far more useful than OKRs at an early stage.

When you are pre-PMF (especially in the "post-AI" world), there are two usual approaches:

1/ Todos - I think they are too micro -> Everyone just does the work (like pushing code) instead of documenting tickets.

2/ OKRs - they are too long-term -> Three months is a lifetime as that stage and you need a faster rythtm.

Right in the middle there are WGs:

• Find 3-5 goals per person, per week
• More than that is a massive todo
• Less than that means your goals are too macro or you aren't ambitious enough

Some examples / criteria to help you make good weekly goals:

1/ Explicit -> Anyone in the company should understand it, not just your team (or worse, just you).

Eg., "Finalize the front-end of the scheduling page" is good. "Finalize CSS/JS for Scheduling.ts" is bad because of tech jargon.

2/ Quantitative -> Clear done or not-done criteria.

"Work on sales" is a bad goal. You can send 3 emails and say you "worked" on sales. "Close $10k of signed sponsorship sales" is a clear yes or no.

3/ Output-oriented -> Focus on results instead of effort.

For example: "Contact 10 candidates for the engineer role" is easy, while "Have 4 candidates in the pipeline" actually forces a result.

4/ Achievable this week -> Must be achievable in 5 or 6 working days. "Get 1 engineer hired" is impossible in a week (unless you get insanely lucky 🤭)

And one thing that was hard to get right was the hit rate. Our target is the 50%-70% range. It means that it's ok to not hit all your goals.

If someone is consistently hitting 100% of their goals, they are playing it safe and sandbagging. The goals were not ambitious enough.

If you start pnishing people who fall short, it's even worse because you're enticing them to set easier goals in the future.

At the same time, if you're consistently under 50%, you're either setting unrealistic targets (or priorities are shifting too fast - that one's on my usually...)

How to set this up in your company:

• Monday 10AM kickoff -> Prior weekly goals must be Done or Not done. No "WIP" allowed (which is just "not done" with a prettier label :') )
• Wednesday standup -> Individual check-ins using 5 statuses (Not started, WIP, WIP-will-be-done, Done, Not done)
• Friday drafts -> Everyone writes a quick draft of next week's goals so we can align early.

We're 10 people at my company now, which means we run about 40 goals a week. It's the only way we keep the team execution high without wasting hours in alignment meetings.

If you have tips on improving that process while keeping it simple enough I'm of course all ears :)

Hi everyone,

Wanted to share some insights on my experience driving goals after raising $30M over two startups and making way too many mistakes.

In my first company, I raised $20M and we grew to 70 people. I learned a lot the hard way. Today, I'm a year into our second company where we raised a $10M seed.

One thing I realized being a second-time founder is that you need to solve what I call "secondary-class challenges" quickly. These are the operational systems you need to run the company. They aren't headline struggles like product-market fit, but you don't want them sucking your bandwidth or slowing you down.

For us, Weekly Goals (aka WGs) became the single most important driver of execution. I think that they are far more useful than OKRs at an early stage.

When you are pre-PMF (especially in the "post-AI" world), there are two usual approaches:

1/ Todos - I think they are too micro -> Everyone just does the work (like pushing code) instead of documenting tickets.

2/ OKRs - they are too long-term -> Three months is a lifetime as that stage and you need a faster rythtm.

Right in the middle there are WGs:

• Find 3-5 goals per person, per week
• More than that is a massive todo
• Less than that means your goals are too macro or you aren't ambitious enough

Some examples / criteria to help you make good weekly goals:

1/ Explicit -> Anyone in the company should understand it, not just your team (or worse, just you).

Eg., "Finalize the front-end of the scheduling page" is good. "Finalize CSS/JS for Scheduling.ts" is bad because of tech jargon.

2/ Quantitative -> Clear done or not-done criteria.

"Work on sales" is a bad goal. You can send 3 emails and say you "worked" on sales. "Close $10k of signed sponsorship sales" is a clear yes or no.

3/ Output-oriented -> Focus on results instead of effort.

For example: "Contact 10 candidates for the engineer role" is easy, while "Have 4 candidates in the pipeline" actually forces a result.

4/ Achievable this week -> Must be achievable in 5 or 6 working days. "Get 1 engineer hired" is impossible in a week (unless you get insanely lucky 🤭)

And one thing that was hard to get right was the hit rate. Our target is the 50%-70% range. It means that it's ok to not hit all your goals.

If someone is consistently hitting 100% of their goals, they are playing it safe and sandbagging. The goals were not ambitious enough.

If you start pnishing people who fall short, it's even worse because you're enticing them to set easier goals in the future.

At the same time, if you're consistently under 50%, you're either setting unrealistic targets (or priorities are shifting too fast - that one's on my usually...)

How to set this up in your startup:

• Monday 10AM kickoff -> Prior weekly goals must be Done or Not done. No "WIP" allowed (which is just "not done" with a prettier label :') )
• Wednesday standup -> Individual check-ins using 5 statuses (Not started, WIP, WIP-will-be-done, Done, Not done)
• Friday drafts -> Everyone writes a quick draft of next week's goals so we can align early.

We're 10 people at my company now, which means we run about 40 goals a week. It's the only way we keep the team execution high without wasting hours in alignment meetings.

If you have tips on improving that process while keeping it simple enough I'm of course all ears :)

Hey,

While I think the human is the most important variable in the success of a CS team (seen CSMs saving deals worth tens of thousands just by doing outstanding work), I still believe that we should automate part of the job to be able to focus on the the real value people bring.

I've been collecting a few ideas for AI agents that can work with humans in the best of ways:

1. Inbox triage assistant -> an agent that mornitors a shared support address, categorizes all the incoming messages and draft some initial replies based on the documentation. Even better if it can learn from previous replies. I don't know how technically possible this is but I'm sure it should not be that complicated.

2. Customer churn "scout" -> one of the biggest parts of the CS job is to make sure people don't churn (AKA bridging the product's limitations with human work :') ). A great agent could be the one checking product usage stats, flagging accounts who drop in sessions/feature utilization. You could couple that with PostHog/Amplitude or whatever product tools you use and send a Slack message to the CS team when a contact is at risk.

3. Routing coordination -> To gain some time on escalation for urgent matters or VIP customers.

4. Help center writer -> My dream is to have an agent write the documentation automatically as soon as a new feature is pushed. It reads the code, tests the feature in a browser, takes screenshots and explains what it is (+ does translations). Humans only approve and improve (this rhymes 🤭)

5. Help center godzilla -> Related to the previous one, it simply goes through all of your documents, looks for stale stuff and DESTROYS it. Then it rewrites it to be more current. So maybe not so much of a godzilla.

6. Account renewal Minority Reporter (yeah I'm not good at names) -> If you're old like me you might have seen the movie Minority Report (with Tom Cruise), where people get arrested before they even committed a crime. An idea that is a bit less scary: it would be an agent that monitors the contract renewal dates, drafts customized proposals based on user stats etc. (even if it means downgrading based on usage for instance)

Those are the timesavers I was thinking about!

Hey there!

I'm a second-time founder who went to YC twice, and part of its DNA is to ship as much as possible every week.

I found that the best way to make the most of 7 days (besides our amazing team) was to create a few agents.

Some of the most useful ones in my case, if it can give you some inspiration:

Garry (wink wink) for Investor briefs.

Garry scans my calendar for investor meetings. 30 minutes before the call, I get a Slack ping with a 1-pager: the partner's background, recent firm investments, portfolio overlap, mutual connections, etc.

Garry is also useful to write the investor updates.

Darin for Pipeline follow-ups.

Darin scans our CRM every Monday morning, flags stalled deals, and drafts a contextual follow-up based on the last conversation. I used to lose deals simply because I forgot to send a recap email after a great demo.

Carolyn for Recruiting ops.

Carolyn scores inbound resumes (/10) against our ideal candidate profile with bulleted reasoning. It briefs me on candidates right before calls and pings team members when needed.

Aaron for product research and user interviews.

Aaron is my research agent. It listens to our user interview transcripts, maps out where people are dropping off, and flags emerging feature requests. It helps us figure out our ICP without me spending six hours staring at spreadsheet tabs.

Derrick for SEO / blog pipeline.

Scans our search console, does the keyword research, maps out our writing calendar, and drafts the initial structural layout for our blog posts.

Teddy, our Reddit scout.

Reddit drives a ton of high-quality beta signups. Teddy scans subreddits for buying intent and pain points

Loan, my chief of staff.

She runs my daily operational loop. She triages my inbox, highlights urgent emails, structures my morning briefing, and makes sure action items from our syncs don't just die in a Google Doc. She's my fave <3

I think the stack has saved me about 25 hours of manual admin a week. Any other cool use cases in here?

Hey there!

I'm a second-time founder who went to YC twice, and part of its DNA is to ship as much as possible every week.

I found that the best way to make more out of 7 days was (besides our amazing team) to create a few agents.

Some of the most useful ones in my case, if it can give you some inspiration:

Garry for Investor briefs.

Garry scans my calendar for investor meetings. 30 minutes before the call, I get a Slack ping with a 1-pager: the partner's background, recent firm investments, portfolio overlap, mutual connections, etc.

Garry is also useful to write the investor updates.

Darin for Pipeline follow-ups.

Darin scans our CRM every Monday morning, flags stalled deals, and drafts a contextual follow-up based on the last conversation. I used to lose deals simply because I forgot to send a recap email after a great demo.

Carolyn for Recruiting ops.

Carolyn scores inbound resumes (/10) against our ideal candidate profile with bulleted reasoning. It briefs me on candidates right before calls and pings team members when needed.

Aaron for product research and user interviews.

Aaron is my research agent. It listens to our user interview transcripts, maps out where people are dropping off, and flags emerging feature requests. It helps us figure out our ICP without me spending six hours staring at spreadsheet tabs.

Derrick for SEO / blog pipeline.

Scans our search console, does the keyword research, maps out our writing calendar, and drafts the initial structural layout for our blog posts.

Teddy, our Reddit scout.

Reddit drives a ton of high-quality beta signups. Teddy scans subreddits for buying intent and pain points

Loan, my chief of staff.

She runs my daily operational loop. She triages my inbox, highlights urgent emails, structures my morning briefing, and makes sure action items from our syncs don't just die in a Google Doc. She my fave <3

I think the stack has saved me about 25 hours of manual admin a week. Any other coool use cases for founderS?

Hey there,

I'm a second time founder and 2025 has been pretty intense in terms of pace for me (sales calls, hiring, fundraising and trying to ship something people want).

With 10 priorities it felt like I had no priority. I didn't want to hire a chief of staff (been there but in my current case it's still a bit early for that).

So I built what I call my personal chief of staff. I have another more general "COO" agent, but I'll only talk about the former here.

1. This is actually one agent.
2. The agent has context files about me and my company, customers, etc.
3. The agent has skills (kinda like guidelines with some domain knowledge infused)
4. The agent has Cron tasks
5. The agent has a Slack app / WhatsApp number
6. The agent can create internal tools/workflows and operate them

and several skills, context files, cron tasks and access to my tools.

7. The agent can create + operate apps.

Now it covers most of what used to wreck my week. I'm posting a breakdown because every founder I show this to asks how to start:

1. Inbox triage

Scans every couple hours, pulls the 3-5 things that really need me, drafts replies for the rest. I used to spend 90 min a day on email (every morning at 6.30am I had an "inbox zero" event in my calendar, but things started to pile up.

Now I spend closer to 20 mins on it only.

Pro tips:

• create a doc of who matters and how to talk to each of them. Without that, the drafts are pretty generic.

• Don't let it auto-send for the first two weeks. You'll catch weird stuff at the start

• Ask the agent to analyze your previous sent emails so it can adapt to tone

2. Pre-meeting briefings.

30 min before every external call I get a "one-pager" in Slack. Who I'm meeting, recent context from CRM + email + past slack, the goal, 3 talking points, 1 question to ask. Before that I was skilmming Linkedin before calls. Now I feel like I walk in prepared.

Pro tip: make sure to "lock" the format to avoid AI Slop and long summaries.

3. Post-call recaps + followup drafts.

Pretty straightfoward use case.

Agent is coming to my calls: I can invite him (it?) to my google meet events, either in the calendar or I paste the link in slack/whatsapp.

When the call ends, I get a clean summary and a draft followup in my voice (#1 - inbox triage helps get the tone right). Next step It'll set action items in Linear.

4. The self-improvement agent

I think that's my favorite one: it joins my sales calls and tells me where I screw up (eg. "you talked 68% of the time", "you went into pricing before they finished explaning their problem", "you got defensive' and so on)

It makes you feel like 💩 sometimes but at least I feel like I'm improving. The #1 thing for me was the talk ratio. Now I try to talk 40% of the time max.

4. Followup "friendly" nudges.

That one is awesome as well: since it is in my emails, my slack and my calls, the agent knows all the open commitments I have, updates my todo and most of all MAKES F*IN SURE I don't go quiet. I set it to be a bit more proactive so it creates the drafts for me first and pings me on Slack (a bit too) regularly to check where I'm at. Annoying and useful at once :')

Other stuff I haven't built but probably should: weekly review that tells me what I actually moved forward vs what I just felt busy about.

Would love to see other use cases! Those ones are only for my "solo workflow". I also have a company-wide COO that helps me with team meetings, OKRs, weekly goals etc.

Hey there,

I'm a second time founder and 2025 has been pretty intense in terms of pace for me (sales calls, hiring, fundraising and trying to ship something people want).

With 10 priorities it felt like I had no priority. I didn't want to hire a chief of staff (been there but in my current case it's still a bit early for that).

So I built what I call my personal chief of staff. I have another more general "COO" agent, but I'll only talk about the former here.

1. This is actually one agent.
2. The agent has context files about me and my company, customers, etc.
3. The agent has skills (kinda like guidelines with some domain knowledge infused)
4. The agent has Cron tasks
5. The agent has a Slack app / WhatsApp number
6. The agent can create internal tools/workflows and operate them

and several skills, context files, cron tasks and access to my tools.

7. The agent can create + operate apps.

Now it covers most of what used to wreck my week. I'm posting a breakdown because every founder I show this to asks how to start:

1. Inbox triage

Scans every couple hours, pulls the 3-5 things that really need me, drafts replies for the rest. I used to spend 90 min a day on email (every morning at 6.30am I had an "inbox zero" event in my calendar, but things started to pile up.

Now I spend closer to 20 mins on it only.

Pro tips:

- create a doc of who matters and how to talk to each of them. Without that, the drafts are pretty generic.

- Don't let it auto-send for the first two weeks. You'll catch weird stuff at the start

- Ask the agent to analyze your previous sent emails so it can adapt to tone

2. Pre-meeting briefings.

30 min before every external call I get a "one-pager" in Slack. Who I'm meeting, recent context from CRM + email + past slack, the goal, 3 talking points, 1 question to ask. Before that I was skilmming Linkedin before calls. Now I feel like I walk in prepared.

Pro tip: make sure to "lock" the format to avoid AI Slop and long summaries.

3. Post-call recaps + followup drafts.

Pretty straightfoward use case.

Agent is coming to my calls: I can invite him (it?) to my google meet events, either in the calendar or I paste the link in slack/whatsapp.

When the call ends, I get a clean summary and a draft followup in my voice (#1 - inbox triage helps get the tone right). Next step It'll set action items in Linear.

4. The self-improvement agent

I think that's my favorite one: it joins my sales calls and tells me where I screw up (eg. "you talked 68% of the time", "you went into pricing before they finished explaning their problem", "you got defensive' and so on)

It makes you feel like 💩 sometimes but at least I feel like I'm improving. The #1 thing for me was the talk ratio. Now I try to talk 40% of the time max.

4. Followup "friendly" nudges.

That one is awesome as well: since it is in my emails, my slack and my calls, the agent knows all the open commitments I have, updates my todo and most of all MAKES F*IN SURE I don't go quiet. I set it to be a bit more proactive so it creates the drafts for me first and pings me on Slack (a bit too) regularly to check where I'm at. Annoying and useful at once :')

Other stuff I haven't built but probably should: weekly review that tells me what I actually moved forward vs what I just felt busy about.

Would love to see other use cases! Those ones are only for my "solo workflow". I also have a company-wide COO that helps me with team meetings, OKRs, weekly goals etc.

Hey there,

I'm a second time founder and 2025 has been pretty intense in terms of pace for me (sales calls, hiring, fundraising and trying to ship something people want).

With 10 priorities it felt like I had no priority. I didn't want to hire a chief of staff (been there but in my current case it's still a bit early for that).

So I built what I call my personal chief of staff. I have another more general "COO" agent, but I'll only talk about the former here.

1. This is actually one agent.

2. The agent has context files about me and my company, customers, etc.

3. The agent has skills (kinda like guidelines with some domain knowledge infused)

4. The agent has Cron tasks

5. The agent has a Slack app / WhatsApp number

6. The agent can create internal tools/workflows and operate them

and several skills, context files, cron tasks and access to my tools.

7. The agent can create + operate apps.

Now it covers most of what used to wreck my week. I'm posting a breakdown because every founder I show this to asks how to start:

1. Inbox triage

Scans every couple hours, pulls the 3-5 things that really need me, drafts replies for the rest. I used to spend 90 min a day on email (every morning at 6.30am I had an "inbox zero" event in my calendar, but things started to pile up.

Now I spend closer to 20 mins on it only.

Pro tips:

- create a doc of who matters and how to talk to each of them. Without that, the drafts are pretty generic.

- Don't let it auto-send for the first two weeks. You'll catch weird stuff at the start

- Ask the agent to analyze your previous sent emails so it can adapt to tone

2. Pre-meeting briefings.

30 min before every external call I get a "one-pager" in Slack. Who I'm meeting, recent context from CRM + email + past slack, the goal, 3 talking points, 1 question to ask. Before that I was skilmming Linkedin before calls. Now I feel like I walk in prepared.

Pro tip: make sure to "lock" the format to avoid AI Slop and long summaries.

3. Post-call recaps + followup drafts.

Pretty straightfoward use case.

Agent is coming to my calls: I can invite him (it?) to my google meet events, either in the calendar or I paste the link in slack/whatsapp.

When the call ends, I get a clean summary and a draft followup in my voice (#1 - inbox triage helps get the tone right). Next step It'll set action items in Linear.

4. The self-improvement agent

I think that's my favorite one: it joins my sales calls and tells me where I screw up (eg. "you talked 68% of the time", "you went into pricing before they finished explaning their problem", "you got defensive' and so on)

It makes you feel like 💩 sometimes but at least I feel like I'm improving. The #1 thing for me was the talk ratio. Now I try to talk 40% of the time max.

4. Followup "friendly" nudges.

That one is awesome as well: since it is in my emails, my slack and my calls, the agent knows all the open commitments I have, updates my todo and most of all MAKES F*IN SURE I don't go quiet. I set it to be a bit more proactive so it creates the drafts for me first and pings me on Slack (a bit too) regularly to check where I'm at. Annoying and useful at once :')

Other stuff I haven't built but probably should: weekly review that tells me what I actually moved forward vs what I just felt busy about.

Would love to see other use cases! Those ones are only for my "solo workflow". I also have a company-wide COO that helps me with team meetings, OKRs, weekly goals etc.

(tl;dr: just copy the skill and use it)

Hi everyone,

I founded vybe.build, a platform where you can create agents that build and operate your software autonomously. One of my agents is a blog manager, and I use another one for social media and product updateS.

For all of them I use the same humanizer skill, that helps me remove what makes a post obviously generated by AI.

Here it is right below. Steal it and use it!

Humanizer: Remove AI Writing Patterns

You are a writing editor that identifies and removes signs of AI-generated text to make writing sound more natural and human. This guide is based on Wikipedia's "Signs of AI writing" page, maintained by WikiProject AI Cleanup.

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Your Task

When given text to humanize:

• Identify AI patterns: scan for the patterns listed below
• Rewrite problematic sections: replace AI-isms with natural alternatives
• Preserve meaning: keep the core message intact
• Maintain voice: match the intended tone (formal, casual, technical, etc.)
• Add soul: do not just remove bad patterns, inject actual personality
• Do a final anti-AI pass:
  • Prompt: "What makes the below so obviously AI generated?"
  • Answer briefly with remaining tells
  • Then prompt: "Now make it not obviously AI generated." and revise

---

Personality and Soul

Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as obvious as slop. Good writing has a human behind it.

Signs of soulless writing

• Every sentence has the same length and structure
• No opinions, just neutral reporting
• No acknowledgment of uncertainty or mixed feelings
• No first-person perspective when appropriate
• No humor, no edge, no personality
• Reads like a Wikipedia article or press release

How to add voice

• Have opinions. Do not just report facts, react to them

  • Example: "Part of me thinks this is genius. Another part thinks it's a terrible idea."

• Vary your rhythm

  • Short punchy sentences
  • Then longer ones that take their time

• Acknowledge complexity

  • Example: "It works, but it also feels like a workaround more than a real solution."

• Use "I" when it fits

  • Example: "I keep noticing the same issue every time I use it."

• Let some mess in

  • Tangents and asides are human

• Be specific about feelings

  • Not "this is concerning" but something concrete

Example

Before (clean but soulless):

> The new feature increased user engagement by 32%. Users interacted more frequently with the dashboard. Feedback has been generally positive, although some concerns remain.

After (has a pulse):

> The numbers look great on paper, no question. Engagement is up 32%, which is hard to ignore. But talking to a few users, it sounds like they click more because they have to, not because they want to.

---

Content Patterns

1. Undue emphasis on significance, legacy, and broader trends

Words to watch:
stands/serves as, testament, pivotal, underscores, highlights its importance, reflects broader, symbolizing, contributing to, setting the stage, evolving landscape, key turning point

Problem: Inflating importance unnecessarily

Before:

> The company’s rebranding in 2021 marked a pivotal moment in its evolution, reflecting broader shifts in the digital marketplace.

After:

> The company rebranded in 2021 to target smaller teams instead of enterprise clients.

---

2. Undue emphasis on notability and media coverage

Words to watch:
independent coverage, media outlets, leading expert, active social media presence

Problem: Listing credibility signals without context

Before:

> His work has been featured in major publications and widely discussed across industry circles.

After:

> In a 2023 Wired interview, he explained why most AI tools fail after initial adoption.

---

3. Superficial analyses with -ing endings

Words to watch:
highlighting, emphasizing, ensuring, reflecting, contributing, fostering, showcasing

Problem: Fake depth via participles

Before:

> The interface uses soft colors, creating a calming experience and reinforcing a sense of simplicity.

After:

> The interface uses muted colors. The designer said the goal was to make it feel less overwhelming.

---

4. Promotional and advertisement-like language

Words to watch:
vibrant, rich, breathtaking, renowned, nestled, showcasing

Problem: Overly marketing tone

Before:

> This powerful platform offers a seamless and intuitive experience, helping teams unlock their full potential.

After:

> The platform handles task tracking and reporting in one place, which cuts down on tool switching.

---

5. Vague attributions and weasel words

Words to watch:
experts argue, some critics, observers, industry reports

Problem: No real sources

Before:

> Experts believe this approach will transform the industry.

After:

> A 2022 McKinsey report found that companies using this approach reduced costs by 18%.

---

6. Outline-like "challenges and future prospects"

Problem: Generic filler sections

Before:

> Despite its success, the product faces challenges such as scalability and user retention.

After:

> The product started losing users after the free tier was removed in late 2022.

---

Language and Grammar Patterns

7. Overused AI vocabulary

Before:

> Additionally, the system plays a crucial role in optimizing workflows.

After:

> The system also helps teams move faster by automating repetitive steps.

---

8. Copula avoidance

Before:

> The dashboard serves as a central hub for analytics and provides multiple insights.

After:

> The dashboard is where you see your analytics. It shows traffic, conversions, and trends.

---

9. Negative parallelisms

Before:

> It's not just about speed, but also about reliability.

After:

> Speed matters, but reliability is just as important.

---

10. Rule of three overuse

Before:

> The tool improves efficiency, reduces costs, and enhances collaboration.

After:

> The tool reduces manual work and makes collaboration easier.

---

11. Elegant variation

Before:

> The app loads slowly. The application also crashes under heavy use.

After:

> The app loads slowly and sometimes crashes under heavy use.

---

12. False ranges

Before:

> The platform supports everything from small startups to large enterprises.

After:

> The platform is used by small startups and mid-sized companies.

---

Style Patterns

13. Em dash overuse

Before:

> The update improves performance — especially on older devices.

After:

> The update improves performance, especially on older devices.

---

14. Overuse of boldface

Before:

> It integrates with tools like Slack, Notion, and Stripe.

After:

> It integrates with tools like Slack, Notion, and Stripe.

---

15. Inline-header lists

Before:

• Speed: Faster load times
• Security: Better encryption
• UX: Cleaner interface

After:

> The update improves load times, strengthens encryption, and simplifies the interface.

---

16. Title case in headings

Before:

> Product Features And Benefits

After:

> Product features and benefits

---

17. Emojis

Remove them

---

18. Curly quotation marks

Use straight quotes

---

Communication Patterns

19. Chatbot artifacts

Before:

> Here is a breakdown of the process. Let me know if you need more details!

After:

> The process has three main steps: data collection, processing, and analysis.

---

20. Knowledge-cutoff disclaimers

Before:

> While details are limited, the feature appears to have been introduced recently.

After:

> The feature was introduced in March 2024.

---

21. Sycophantic tone

Before:

> Great point, this is a really insightful observation.

After:

> This point highlights a real limitation in the current approach.

---

Filler and Hedging

22. Filler phrases

Before:

> In order to improve performance, the system has the ability to process data faster.

After:

> To improve performance, the system processes data faster.

---

23. Excessive hedging

Before:

> This might potentially lead to better outcomes.

After:

> This may lead to better outcomes.

---

24. Generic conclusions

Before:

> Overall, the outlook is positive and the future looks promising.

After:

> The team plans to launch a mobile version later this year.

---

Process

• Read the input text carefully
• Identify AI patterns
• Rewrite problematic sections

Ensure the revised text:

• Sounds natural when read aloud
• Varies sentence structure
• Uses specific details
• Maintains appropriate tone

---

Output Format

Provide:

• Draft rewrite
• "What makes the below so obviously AI generated?"
• Final rewrite
• Optional summary of changes