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14 people. Remote. The internal wiki was comprehensive. 140+ pages covering processes,

policies, and SOPs. It was also unread. Page view analytics showed 6 of 14 team members

visited it in the past quarter.

The wiki existed so that when someone asked "how do we handle X," I could say "it's in the

wiki." It was a reference system that nobody referenced.

Replaced it with two things:

Loom recordings for process explanations. 3-5 minutes each. Recorded by whoever owns the

process. Stored in a shared Drive folder. View rate: 89% within 48 hours of posting.

Visual one-pagers built in Gamma for policies and quick-reference information. One page per

topic. Shareable link. Updated in place when the policy changes. View rate: 78%.

The wiki had a search problem. 140 pages meant nobody could find anything without already

knowing the page title. The visual one-pagers have no search problem because each one

covers exactly one topic and the titles are literal.

Total time to replace the wiki: roughly 12 hours across 2 weeks. Recorded 24 Loom videos. Built

18 one-pagers. Archived the wiki.

The information quality is identical. The consumption rate went from "6 people occasionally visit"

to "12 people consistently watch/read." Same knowledge. Different container.

Cost of the wiki: $450/year for the wiki tool. Cost of the replacement: $0 (Loom free tier) +

$16/month (Gamma). Saved roughly $260/year and the team actually reads the materials.

We're at 15 people now. $28K MRR. Two things changed when we crossed ~12 employees that

I wasn't prepared for.

First, I stopped being able to hold the entire company state in my head. At 8 people I knew

every customer conversation, every pipeline deal, every product decision. At 15 I'm discovering

things a week late through secondhand Slack messages. The information surface area grew

faster than my ability to track it.

Second, the board updates I used to write in 30 minutes now take 3 hours because I'm

assembling information from 4 people before I can even start. I rebuilt the format in Gamma last

quarter because the old Google Doc was becoming unmanageable. But the tool isn't the

problem. The problem is that I'm still the single point of assembly for information that lives in

other people's heads.

What I'm realizing: the jump from 8 to 15 isn't a hiring problem. It's an information architecture

problem. The founder who was the router for all company knowledge needs to build a system

that routes without them.

I haven't built that system yet. Currently trying: each team lead writes a 3-line weekly update

(metric, win, blocker) in a shared doc. I synthesize. It's better than chasing people. Not good

enough yet.

For founders at the 12-20 person stage: what does your internal information system look like?

Not the tools. The actual habit. Who updates what, when, in what format. Curious what works

because every blog post says "have regular standups" and that answer stopped being useful at

person 10.

Offered a 14-day free trial since launch. Standard SaaS playbook. Let people try before they

buy. Conversion from free trial to paid: 12%.

In March I removed the free trial and replaced it with a low-cost first month ($9 instead of $49,

then full price from month 2).

Trial-to-paid conversion was 12%. $9-first-month conversion: 8%. A drop.

But the churn data tells a different story. Free trial converts churned at 18% within 90 days.

$9-first-month converts churn at 7% within 90 days.

The free trial was converting people who weren't sure. The $9 entry was converting people who

were willing to invest, even minimally. The willingness to spend $9 is a filter that the free trial

didn't provide.

Revenue math after 6 months:

Free trial model: 100 signups → 12 convert → 10 survive 90 days → revenue from survivors:

~$2,450/month.

$9-first-month model: 100 signups → 8 convert → 7.4 survive 90 days → plus $9 from all 8 in

month 1 → revenue from survivors: ~$1,832/month plus better LTV trajectory.

At 6 months, the revenue converges. At 12 months, the $9-first-month model overtakes

because the retained cohort is larger as a percentage of converts.

The free trial was optimizing for conversion volume. The $9 model optimizes for customer

quality. Fewer customers who stay longer are worth more than more customers who leave

faster.

Not saying free trials are always wrong. For products with strong activation loops and high

switching costs, they work well. For my product, where switching costs are low and the

commitment signal matters, the $9 entry performs better on lifetime revenue despite worse

upfront conversion.

The metric that matters is not how many people start paying. It's how many people keep paying.

This is the post I've been avoiding writing because the nuance doesn't fit a headline.

In September I replaced 3 roles with AI-powered workflows. A customer support agent (replaced

with an AI chatbot + escalation system). A data entry clerk (replaced with automated form

processing). A junior marketing writer (replaced with AI content generation + my editing).

Monthly savings: $11,400 in total compensation. The AI tools cost approximately $380/month.

Net savings: $11,020/month. $132K annualized. The math looks spectacular.

Here's what the math doesn't show.

Customer satisfaction scores dropped 14% in the first 3 months. The chatbot handles 80% of

queries well. The 20% it doesn't handle get escalated, but the escalation adds a delay that

human support didn't have. Customers who hit the 20% are more frustrated than they would

have been talking to a person from the start.

The data entry automation processes 95% of forms correctly. The 5% error rate creates

downstream issues that take longer to fix than the original manual entry. One misprocessed

form in January led to a $3,200 billing error that took 2 weeks to resolve.

The AI content generation is the most successful replacement. Output quality is 70-80% of the

human writer. I edit everything, which takes about 6 hours per week. That's 6 hours of my time,

at my billing rate, that the savings calculation doesn't include.

Updated honest accounting:

Gross savings: $132K/year. AI tool costs: $4,560/year. My editing time (valued at my rate):

$31,200/year. Customer satisfaction recovery costs (training, escalation staffing): ~$8,000/year.

Error remediation: ~$5,000/year.

Net real savings: approximately $83K/year.

$83K is still significant. It's a real number. But it's $49K less than the headline number I was

telling people at networking events.

The other cost I can't quantify: the team culture changed. We went from 8 people to 5. The

remaining 5 are more productive individually but the ambient knowledge-sharing that happened between 8 people doesn't happen with 5. Questions that used to get answered by asking the

person next to you now require finding the answer in documentation or prompting the AI.

I'm not arguing against AI automation. The $83K in real savings is funding product development

that wouldn't otherwise exist. But the narrative that AI replacement is a clean swap of human

cost for tool cost is dishonest. The swap has friction, error, and hidden time costs that the

vendors selling the tools don't mention and the founders implementing them don't track.

Track them. The real number matters more than the headline number. And the real number is

still good enough to justify the change. You just don't need to lie about it.

Built with this guy for 14 months. Not a cofounder. A contractor who became a collaborator who

became a partner in everything but paperwork. He had access to the codebase, the customer

database, the revenue dashboard. I gave him all of it because we were building together.

The customer who told me was one of our first. She emailed asking why she was getting

marketing emails from "a product that looks just like yours but cheaper." Attached a screenshot.

The UI was almost identical. The pricing was 30% lower. The landing page used phrases from

our marketing copy. Not similar. Verbatim.

I checked the domain registration. His name. Registered 6 weeks before I found out, which

means he was building this while sitting in our shared Slack workspace helping me plan the next

quarter.

The customer list thing was the part that broke me. Our early customers, the ones I personally

onboarded, were receiving cold emails from his product. He hadn't scraped the list. He had

exported it before he left, 3 weeks before he told me he was "taking a step back to focus on

personal projects."

I called a lawyer. The lawyer asked if I had a non-compete. I did not. A non-disclosure? I did not.

An IP assignment? I did not. Anything in writing about the partnership terms? I did not.

Without documentation, I had almost no legal recourse. The code he wrote was arguably his.

The customer list he had legitimate access to. The product he launched was different enough

legally even if identical functionally.

Total cost of the experience: roughly $40K in lost customers who switched, plus $6K in legal

consultation fees that confirmed I couldn't do anything meaningful. Plus the specific, persistent

feeling of having trusted someone who used the trust as a blueprint.

The product recovered. I rebuilt the features he'd been responsible for. The customers who

stayed were the ones who valued the relationship with me specifically, not the product in

isolation.

Three things I did immediately after and should have done from day one. IP assignment

agreement for any contractor or collaborator. Non-compete with a specific duration and

geography. Customer data access restricted to people who need it operationally, not given as a

trust gesture.

The documentation isn't about distrust. It's about acknowledging that people's interests change

and the time to define boundaries is before those interests diverge. By the time you need the

protection, it's too late to create it.

Still building. Revenue is back to where it was. The competitor is still operating. We coexist in a

market that's big enough for both, which is the most anticlimactic ending a betrayal story can

have.

VP of engineering at a series c. 80-person eng org. roughly 15% women on the team, which is

industry-bad and worse than i want it to be. been doing the job 18 months.

we are hiring three senior eng roles in the next quarter. i want at least two to be women. the

data says we have to do something different, because the current approach (post the role, get

inbound, interview) does not produce candidate pools that resemble the candidate pools we

want.

one thing i am building is a candidate pitch deck specifically for senior women i am

cold-reaching out to. it is meant to communicate: this is a real engineering org, we have hard

problems, we have other senior women you would be working alongside, here is what is and

isn't true about the gendered dynamics on the team.

what i am using:

notion for the actual content. each section is a one-page brief. the message has to be specific,

not "we value diversity." women have heard "we value diversity" and they read it as a flag.

granola transcripts of conversations i had with the senior women already on the eng team, with

permission, about what they would tell another senior woman considering joining. the deck

quotes them directly (with their consent and review).

gamma for the actual slide deck. the ai slide generator handles the layout work. i spent the time

on the writing instead.

loom for a short video version that goes out alongside the deck. some candidates engage with

the video, others with the deck. having both broadens the funnel.

what i am asking the women in this sub:

if you got a recruiting pitch deck like this from a hiring manager you did not know, what would

make you trust it vs roll your eyes? what specific signals would tell you the org actually means it

vs is performing?

what would make you delete the email?

i would rather know what trips your detector early than send something that comes across

exactly the way i am trying to avoid.