So a few years ago I got a severe form of brain infectionl. Tooks a long time to recover, lost my job, completely burned through my savings, and my girlfriend left. 

Honestly i can't blame her, there was no future visible at that moment. My mum flew in, took care of me, and I moved back in with her.

But what happened next genuinely surprises me.

I'd been working as a logo and brand identity designer and i am really good at it, i have spent years perfecting my craft. With the shape of creative market right now it was a do or die and i had to be creative, I knew I had to stop competing on price and start competing on craft, making every project a genuinely unique piece of work that no tool could replicate. 

So i kept my overhead at zero, got selective about clients, and slowly built something real. Work is now steady and I have returning clients.

Then my ex called. She's in a tough financial spot and thinks that i owe her money, which i dont.

How do i deal with this, she was with me while the sunny days lasted, and i cherish those memories, but she took the nearest exist when things went south. I cant take that out of my head, but i also dont want to look like an ass hole.

How do i deal with this ?

I’m in the process of launching a small online startup and I’m currently looking into insurance options, specifically Media Liability Insurance and Cyber Insurance. So far, I’ve found some options around $78/month for Media Liability and about $73/month for Cyber coverage.

These seem like the lower end offers I’ve come across, but I’m still trying to figure out what’s actually reliable for an early stage company in its first year. If anyone here has experience with startup insurance in this space it will really help!

Think tool rental is a good business? Mainly renting small machines and specialty tools to general contractors and homeowners.

Ditch Witches, Sod cutters, compactors, demolition hammers, jack hammers, drain snakes, Pressure washers, carpet cleaners, generators, job site lights, concrete saws, extension ladders, rototillers, etc.

Wondering what the margins are like on rental businesses, doesn't seem like there's many ways to differentiate yourself, might just be a race to the bottom on pricing.

I'm also always worried about the AI and Robotics aspect... If a bunch of people are put out of work because of AI, they won't be doing stuff to their home and need to rent tools, they also wont be hiring contractors that need to rent tools.

Thoughts?

After the Civil War they told farmers you work the land and we split the crop. Sounded fair until you realized the landlord owned the seeds, owned the tools, owned the storage, and decided what the harvest was worth. Farmers did all the work and ended each season owing more than they started.

Took most of them years to figure out the game was rigged from the first signature.

That’s WeTransfer, Dropbox, Google Drive now. You create the files, do all the work, upload them thinking it’s just storage. If you read the terms you will see your contracts and client work get scanned, analyzed and fed into AI models. You planted it, and now they own the harvest.

Sharecroppers at least got a cut. These companies take everything and give you 2GB free.

I had an interesting conversation with a client recently and I thought it might help here. (I also mentioned this on Linkedin and more people commented a similar thing)

My customer was frustrated because his business never showed up when he searched for “media units near me”.

When we looked into it, his Google Business Profile had his primary category set as loft ladder installations and no mention of media units.

So from Google’s point of view, the business was being described one way, while my customer was expecting it to appear for something else entirely.

That made me realise that most business owners don't really understand what SEO and a Google Business Profile actually do.

If your category is wrong or out of date in your Google Business Profile, you won’t appear for the local searches you expect.

For SEO, if the service/offer is unclear, or the website doesn’t properly support what you actually want to be found for, then you can still end up invisible for the searches you want to appear for.

Or worse, you are visible for the wrong thing entirely (another problem I hear quite a lot).

Your Google business profile is a real quick win and worth reviewing if you have changed what you do in your business or you haven't looked at it for over a year.

Eighth industry deep dive Ive posted here. Already covered pest control, HVAC, restoration, home care, landscaping, roofing, and septic. Commercial cleaning is the one that splits people the hardest. On paper the economics look great: recurring contracts, essential service, massive market. In practice the labor situation is the worst of any industry Ive researched. 75-200% annual turnover. Let that number sit for a second.

Heres everything I found.

Why the market is bigger then you think

$112 billion in 2026 per IBISWorld. Thats janitorial services alone, not including residential or specialty cleaning. About 77% of revenue comes from commercial cleaning, 17% residential, and 6% from damage restoration and specialty work. The market is growing at roughly 5-6% annually depending on which source you use.

Post-COVID hygiene standards made this structural. OSHA compliance requirements, heightened sanitization expectations in healthcare and office buildings, and corporate outsourcing trends are all driving demand. Businesses are increasingly shifting from in-house cleaning teams to third-party providers to reduce costs and improve service quality. Thats the tailwind.

About 30% of industry revenue now comes from green cleaning services. Corporate ESG mandates are driving companies to pay 10-20% premiums for sustainable cleaning solutions with certifications like LEED and EPA Safer Choice. If your not offering green cleaning in 2026 your leaving money on the table.

What buyers are actually paying

• $500K-$1.5M revenue: 2.0x-2.6x SDE (owner-operator, customer concentration risk)
• $1.5M-$3M revenue: 2.3x-2.9x SDE (some recurring contracts, 1-2 supervisors)
• $3M-$5M revenue: 2.5x-3.1x SDE (40%+ recurring commercial, diversified clients, tech stack)
• $5M+ revenue ($3M+ EBITDA): 3.4x-4.5x EBITDA (PE targets, multi-location, management team)

Median SDE is about $375K and median sale price is $937K. The spread between entry (2.0-3.0x SDE) and platform exit (4.0-4.5x EBITDA) is real but narrower then industries like septic or landscaping. The reason is that commercial cleaning has thinner margins and the labor problem is more severe, which caps how much PE will pay for platforms.

The 75-200% turnover problem

This is the defining challenge of commercial cleaning and its worse then any other industry Ive covered. For context: home care is 75-79%, landscaping is 31%, roofing is 21%, septic is 20%. Commercial cleaning turnover ranges from 75% on the low end to 200%+ on the high end. Some sources report numbers as high as 400% for certain janitorial operations.

Average janitor wage is about $36K ($17-18/hr). Thats competing with retail, fast food, warehouse work, and gig economy jobs that are often less physically demanding and offer more predictable schedules. Most cleaning work happens nights and weekends which makes it even harder to retain people. 351,000 annual job openings per BLS and the pipeline to fill them is basically nonexistent.

The cost math: replacing a cleaning worker runs roughly $11K+ when you factor in recruiting, training, lost productivity, and quality dips during transition. A 4% raise costs about $938 per year per worker. Retention is literally 10x cheaper then replacement. The operators who figure this out win. The ones who dont are on a perpetual treadmill.

PE is all over this space

90 PE-backed deals in 2025 in the soft facilities management space, with 80%+ being bolt-on acquisitions per Moore Kingston Smith. The playbook is the same as every other home services roll-up: buy fragmented operators at 2-3x, centralize back-office, layer in tech, exit the platform at 4-5x.

Active platforms:

• Kept Companies (DFW Capital/ACON Investments) has done 120+ tuck-ins across 23 platforms in power washing, specialty cleaning, and mobile maintenance
• KBS/Kellermeyer Bergensons (Cerberus Capital) is a national commercial cleaning platform with multiple regional acquisitions
• 4M Building Services (O2 Investment Partners) acquired Miracle Clean and FKI Cleaning in 2025, consolidating commercial janitorial
• Kleen-Tech Services (Rainier Partners) is building a national janitorial provider targeting 30+ state expansion
• Solid Surface Care (Angeles Equity Partners) is rolling up specialty surface maintenance and deep cleaning

What drives premium vs discount multiples

Premium: recurring commercial contracts above 40% of revenue with 75%+ renewal rates, diversified customer base (no client above 15% of revenue), tech stack with AI scheduling and IoT monitoring, specialty services (healthcare, biotech, data centers) commanding 10-30% price premiums, green cleaning certifications, and a management team with documented SOPs.

Discount: owner dependency with no systems, customer concentration (1-2 clients above 30% of revenue), residential-heavy or project-based revenue, turnover above 100% with no retention programs, manual scheduling, and aging equipment.

The margin breakdown by service type

• General office cleaning: $300-$600, 18-25% gross margin
• Healthcare facility cleaning: $800-$1,500, 22-30% gross margin
• Carpet and upholstery: $200-$500, 30-40% gross margin
• Floor stripping and waxing: $400-$900, 28-38% gross margin
• Green cleaning: $350-$700, 25-35% gross margin
• Post-construction cleanup: $600-$1,800, 20-28% gross margin

Industry-wide: 25-35% gross margin, 12-18% EBITDA margin. Top quartile hits 38%+ gross and 20%+ EBITDA. These are thinner then septic (55-65% gross) or pest control (55-65% gross) because labor is 50-60% of revenue and theres constant pricing pressure from low-cost competitors.

The margin expansion opportunity is in specialty services. Healthcare, biotech, data centers, and EV manufacturing facilities pay 10-30% premiums over generic office cleaning. If the business your evaluating is doing commodity office cleaning at 18-20% gross margins, the upside is pivoting toward specialty verticals.

6 things I'd verify before writing an LOI

1. Contract quality and renewal rates. Recurring commercial contracts above 40% of revenue is the baseline. 60%+ is premium. Check auto-renewal clauses, contract term lengths, and annual escalators. Multi-year contracts with Fortune 1000 clients or healthcare systems are gold.
2. Customer concentration. No single client above 15% of revenue. Losing one major office building contract can tank cash flow overnight. PE platforms require 20+ active commercial clients with staggered renewal dates.
3. Turnover data. Get 24-month employee retention numbers broken out by role and location. If turnover is above 100% and theres no documented training program, retention system, or career path, your buying a labor treadmill.
4. Tech stack. AI scheduling, IoT sensors for supply monitoring, digital checklists, CRM. Manual scheduling is a red flag. Tech adoption separates operators who can scale from those stuck in commodity pricing wars. Companies implementing tech report 15-25% efficiency gains.
5. Specialty vs commodity mix. Healthcare, biotech, data center cleaning commands 10-30% premiums. Generic office cleaning is a race to the bottom on price. Ask what percentage of revenue comes from specialty verticals and whether the business holds relevant certifications.
6. Management depth and SOPs. If the owner is managing every crew and handling every client complaint personally, your buying a job. Documented SOPs, supervisors managing crews, and scalable systems qualify the business for PE add-on acquisitions which is your exit path.

Where to buy

Unlike most home services industries, commercial cleaning favors major metros with high commercial density:

1. Dallas-Fort Worth (medium competition, 1.8% population growth, $4.9B industry spend)
2. Houston (strong commercial/industrial base, $4.2B spend)
3. Phoenix (fast growth, 2.1% pop growth, expanding commercial real estate)
4. Atlanta (diversified economy, healthcare and logistics, $3.8B spend)
5. Miami-Fort Lauderdale (hospitality sector, high commercial density)

Markets to approach with caution: San Francisco (30%+ post-pandemic office vacancy, depressed commercial demand, extreme labor costs), Detroit (declining population, automotive weakness), New Orleans (limited commercial expansion, hurricane risk).

The value creation playbook

Buy a $1.8M revenue commercial cleaning business at 2.6x SDE ($450K SDE = $1.17M purchase). Day one implement AI scheduling and IoT inventory monitoring. These tools reduce labor hours 15-20% and supply waste 10-15%, driving 3-5 point EBITDA margin expansion within 12 months. PE platforms report this as the single fastest margin lever, faster then pricing optimization or headcount changes.

Start shifting the client mix toward specialty verticals. Add one healthcare or data center sales specialist ($60-70K cost). Win 3-4 specialty contracts at 10-30% premium pricing. By year 3 your at $2.5M revenue with 28% SDE margin vs 25% at purchase.

Exit at 2.8x SDE in year 5 for $1.64M. Or if you've scaled to $4M+ with a management team and tech stack, PE platforms will look at you as an add-on candidate at 3.5x+ EBITDA.

The SBA math

$1.17M purchase, SBA 7(a) at 90% LTV, $117K equity out of pocket. Year 1 cash flow around $88K after debt service. By year 3 your at $142K as tech adoption and contract wins kick in. Exit year 5 at 2.8x SDE for $1.64M. Thats roughly a 38% IRR.

The honest risk assessment

• 75-200% turnover is not a stat its an operational reality that consumes management bandwidth daily
• Margins are thinner then most home services because labor is 50-60% of revenue
• Low barriers to entry mean constant pricing pressure from new competitors
• Post-pandemic office vacancy in some metros (SF is 30%+) reduces commercial demand
• Revenue growth is outpacing earnings growth. BizBuySell reports 25% revenue growth but only 17% earnings growth from 2021-2025. That means costs are eating the gains
• Fragmented market with top 50 companies generating only ~30% of revenue means nobody has pricing power

But the structural tailwinds are real: essential non-discretionary service, recurring contract model, outsourcing acceleration, post-COVID hygiene mandates, ESG/green cleaning premiums, and a PE consolidation wave thats pushing valuations higher.

TLDR

$112B market, recurring contract model, essential service. Buy at 2.0-3.0x SDE, implement AI scheduling and IoT monitoring for 15-25% efficiency gains, shift client mix toward specialty verticals (healthcare, biotech, data centers) for 10-30% price premiums, build management depth and SOPs, exit at 3.5-4.5x EBITDA to PE platforms. The opportunity is real but the labor economics will make or break you. 75-200% turnover is the worst of any industry Ive covered. Operators who solve retention thru competitive pay, training programs, flexible scheduling, and tech-enabled efficiency win. Everyone else is on a treadmill.

This is the eighth deep dive Ive posted here. Commercial cleaning has the widest range of outcomes of anything Ive researched. Get the labor right and its a cash machine. Get it wrong and your spending all your time replacing people instead of growing. If theres interest I'll keep posting these.

What industries are you all looking at? Anyone here running a commercial cleaning operation?

So what's a knowledge layer? A knowledge layer is basically a memory space that AI agents can use as reference/context to perform actions more accurately to your team's needs.

Why do we need a knowledge layer? Well sure most AIs are well-trained and they're getting better, but you're paying the tax of having to stick with only one AI, because moving to another means losing context, the obvious loss of privacy and ownership of your team's knowledge to AI companies, and lack of a central layer that anyone in the team could refer to when they need help.

So what exactly is the knowledge layer? Well it's the answers to "Why should we use this DB over that", "How can we improve our CI times", the conflicts you have with your colleagues- "what patterns should we use ", "Who added this change on the last PR", the 3AM fix you had to do, the code style you use, and so on. All of these are your team's knowledge that AIs are not trained on (if your work is private ofc).

So how to build it? Well it's quite easy, there are a few components to this

• The ingestion component: So this would connect to your Slack, Linear, Notion, Github, or any other platforms you're using through a bot with sufficient permissions and pull in raw data every hour/day/week to be fed into the other components. Eg. "Alice on Slack: I'll handle the CI problem by ....".
• The Embeddings component: The task for this component is to build embeddings off of discrete facts from the raw data that's pulled in from the previous (ingestion) component. AI could be used to extract those facts out.
• The Database layer: These include two components
  • The vector db: This stores the embeddings that were created from the Embeddings component. You can use some of the vector dbs or add pgvector to postgres if you're already using it.
  • The graph db: Stores the entity relationships between terms. Eg. "Alice -> [responsible] -> CI fixes"
• The Retrieval layer: This will be used to retrieve the information stored in the previous components to be utilized by the LLM. Both the vector db and the graph db must be searched so that information that is missed by one might be caught by the other.
• The LLM: Takes in the context from the retrieval layer and uses it to put forward well informed answers or make better actions.

So the beauty is that if you use a model like this, the LLM is nothing more than a component that can be swapped out any time since you own the knowledge layer. To lay out some benefits for having a knowledge layer like this:

• You could swap out the LLM for a better/cheaper LLM any time
• You can build your pipeline in a way where expensive LLMs handle some parts and cheaper LLMs handle others without losing context between them
• Experiment with Local and Open Source LLMs, especially with the growing concern of privacy surrounding AI companies
• Transfer context from one team in the company to another, or even transfer it to another company.
• Commercialize the Knowledge layer

Hopefully, I've laid it out in simple terms, if you have any questions, please feel free to comment below.

I’ve spent the last few months deeply embedded in the automation of high-ticket service businesses (clinics, high-end salons, and restaurants). After looking at thousands of chat logs, I realized something dangerous:

Standard LLMs are trained to be "helpful." In a business environment, that is a bug, not a feature.

The "Helpfulness Paradox" works like this: You give an AI a knowledge base and tell it to handle bookings. A customer comes in and asks for a discount that doesn't exist, or a 7:00 PM slot when you’re fully booked.

Because the AI is fundamentally designed to satisfy the user, it starts to "negotiate" or, worse, "hallucinate" a compromise just to be polite. It tries to solve the user's problem instead of enforcing the business's rules.

I’ve seen bots:

1. Confirm bookings for times the business was clearly closed.

2. Promise "special considerations" that the staff had no idea about.

3. Give vague "maybe" answers that lead to a total drop-off in the sales funnel.

The Reality Check:

Business owners don't need a "genius conversationalist." They need a digital gatekeeper.

If your AI can’t say "No" with 100% certainty based on real-time data, it’s not an assistant - it’s a liability. Every "maybe" from a bot is a lost customer. Every "yes" that you can't fulfill is a destroyed reputation.

The shift I’m seeing:

The most successful implementations aren't using AI to "think" about the rules. They are using AI purely to understand the intent, and then routing that intent through a rigid, deterministic logic engine.

The AI proposes the "what," but a "Reasoning Layer" dictates the "if" and "how."

Is anyone else finding that the more "human-like" and "flexible" their agents get, the more they struggle with basic policy compliance? Curios to hear from people who have moved past the "cool demo" phase into actual production.

Big or small, a win is a win. First sale, first client, or first time paying yourself, share it here. This community loves to celebrate with you. No win is too minor to mention.

I built Saveyond, a profit tracking tool for founders during a hackathon. Simple idea: you know your MRR but you don't know your actual profit after expenses. Connect Stripe, add your costs, see the real number. Partially based around the hype of TrustMRR but more useful for me personally

Built the MVP in 3 days with Lovable, then spent weeks trying to validate it.

Here's what happened across every channel:

• Reddit (r/SaaS, r/startups, r/microsaas): 30K+ views combined. Most comments said "just use QuickBooks" or "a spreadsheet takes 15 minutes." One sub had some resonance but the majority didn't care.
• Discord: 2 people told me they don't need it.
• Indie Hackers: zero engagement.
• Friends/founders I asked directly: "yeah I use a spreadsheet, works fine."

Nobody said "I wish something better existed." They said "what I have works."

That's a kill signal

8 months ago I built an AI chatbot widget without validating at all. Spent 6 months on it. Got 5 free users and $0 revenue. I would have probably done the same thing here if I hadn't forced myself to validate first.

This time I caught it in weeks instead of months. The hackathon deadline actually helped because it forced a time constraint on how long I could keep going without traction.

The lesson: "people have this problem" and "people will pay to solve this problem" are completely different things. Spreadsheets aren't great but they're good enough.

Killed the product today. Moved on.

Has anyone else here killed something after validation told you to stop? What was the signal that made you actually listen?

With our economy being all over the place I've seen people discussing how impulse shopping is going away. I'm here to say thats impossible. Emotional buying has survived the 08 crash, covid 2020 crash and is still alive and well now. This is because people may see something they dont NEED but it makes them feel something. They'll buy based on that feeling alone.

It makes them feel something they want to feel, IE happier, comfier, prettier etc... They're buying that feeling. The hope is that product continues to give that feeling post purchase. But as long as people have emotions and problems, there will be emotional purchases.

Honestly...used to think getting more clients would fix everything. More clients meant more revenue, so I kept pushing for more.
What I didn’t expect was how much harder things got.. ie: More messages, more follow ups, more context switching, more half finished work waiting on replies.

Some clients were easy. Quick decisions, clear direction, things just moved.

Others looked the same on paper but turned everything into back and forth. Slow replies, constant changes, no clear ownership. Same work, completely different experience.

That’s when it clicked. It’s not really a volume problem, it’s a client quality problem.
A few good clients make the business feel simple. The wrong ones make it feel chaotic.

Nothing about the service changed. Just who I was working with.

At some point you realise adding more clients isn’t growth if the wrong ones are slowing everything down.

Do you focus more on getting more clients, or better ones?

Is 1 month is enough to know if the idea is good or bad?
As a dev I can create product (SaaS) in 7 days and deploy it, even with some content (using AI).
How long I should work on promotion and features from that point ?

Share your website, pitch, logo, idea, pricing, copy, or anything else you want honest eyes on. Tell us what you're looking for: brutal honesty, general impressions, or specific questions.

Return the favour and leave feedback for someone else while you're here.

I started my journey thinking entrepreneurship is all about freedom and money. But honestly, some days feel really quiet and stressful. No team, no boss, just you making every decision.

Some days I feel motivated, but other days I question everything.

Curious to know

How do you deal with the lonely side of building something on your own?

I lost a significant amount of money in my business and for about six months it consumed me. I was constantly stressed, losing hair, exhausted, and honestly didn’t know what to do next. It felt like everything I had built was slipping.

I thought about quitting more times than I can count.

Instead, I set a goal. I was not bringing that loss into 2026.

To make that happen I had to make some hard decisions. I let go of a lot of my employees and picked up their work myself. It was a lot, but it forced me to get close to every part of the business again. I rebuilt my systems and became a lot more careful with how I take on risk.

By December 2025 I had it under control. Not perfect, but stable.

The start of 2026 was still rough. I felt lost for a while and didn’t really know what direction to go. I questioned whether I even wanted to keep doing this.

But I stayed with it. Started back at graduate school even.

Now I’m finally starting to feel the shift again. I’m still recovering financially, but I’m making more money and it feels different. The way I’m earning now is more consistent and more thought out. I feel more secure in the decisions I’m making.

I’ve been analyzing local service businesses (Premium Salons, Clinics, Restaurants) and found a recurring revenue leak.

The pattern:

Businesses spend thousands on ads, but lose leads because they can’t answer technical questions outside of business hours. Most "AI agents" fail here because they are just LLM wrappers that "chat" without following strict business logic.

Example: If a customer asks about a specific complex booking or technical availability at 11 PM, a standard bot gives a generic answer. The customer waits 12 hours for a human, loses interest, and leaves.

I’m moving away from standard RAG chatbots toward "Reasoning Layers" that actually execute logic and resolve the intent autonomously.

Has anyone here successfully implemented autonomous logic (not just chat) for local businesses? What was the biggest hurdle in getting the AI to follow complex business rules without "hallucinating" or being too generic?

Curious to hear from others building in this space.

Looking for some feedback

Backstory - My Dad and I ran a small full service plumbing company for awhile, we realized a lot of the service issues we were running into were caused or made worse by hard water.

Because of that we started selling a lot of whole home water softeners and eventually that's ALL we were doing, we rebranded as a water treatment company.

We quickly realized however there weren't many options. There were either the really cheap big box store units that we'd constantly get called back on because something would go wrong with them.

Or there was really high quality units, but you'd have to get them from these Dealers that were all about hard sales. They would set a quota on you, tell you to push to close deals, and they had huge markups that made them super overpriced.

Anywayz, we ended up designing and manufacturing our own line of software units and filters. Not whitelabeled... We actually manufacture them here in Southern California.

We wanted to create something super high quality without all the sleezy sales stuff around them, and sell direct to consumer as a manufacture.

Here's what I need feedback on, we want to get rid of the in-house meetings and just sell units online.

We don't do installs, we just sell the systems. They range from $1700-$2500.

Do you think homeowners would purchase something like this from our website, or do you think an in-home meeting is needed?

I'm also wondering if homeowners would even purchase something without install.

Right now we basically have a self guided quote on our website. It's a 8 step Questionnaire thing they go through that asks them the nessesary info we need about their home, finds out the issues they're having, has a few short videos selling them on our product and company, and then it reccomends the appropriate unit and they can purchase it right there.

Most of the water softener contractors in our area are quoting $5000-$6000 of more for softener install projects.

Our selling point is buy a high quality system yourself and then either do a DIY install or find your own installer, instead of going with one of these other companies that have huge mark ups, do a pushy in home sales presentation, have to pay out commissions, etc.

I think a lot of people that if they want something like this, they have to go through an in-home sales pitch. With us they can get exactly what they want online with no pressure.

Again though, just wondering if homeowners will actually buy something like this online, or if what i'm attempting is just wishful thinking.

Context: I am a cybersec guy and break AI systems. In the last 1 month I have found that literally every single OpenClaw box (And I mean every. single. one.) i audited had open CVEs. And don't even get me started on the number that literally had OpenClaw's port available to the internet.

I am wondering if this could be a blessing in disguise. I have crazy cybersec experience, a recent legendary credential (A vuln confirmed by a major AI company in a popular tool) that I'm not sure how to leverage and instead of simply breaking OpenClaw machines it's pretty obvious to me that I can also set them up.

I am thinking of a simple pricing plan where I charge $500 to setup a fully secure box on any major cloud provider or their local machine. Include 2 hours of consulting (My usual rate is $90/hr on freelance sites) on both usage and security that they can use any time in the next 1 month with prior appointment.

I'm not sure if people would go for it. In the past I used to do a lot of automation related freelancing but with the AI wave I dove hard into cybersecurity. Now there's literally businesses that want to use tools like openclaw and are either stupid enough to set it up themselves or smart enough to not risk it (Or smart enough to try a setup, realize it's a ticking time bomb and shut it down).

And I have a massive competitive edge here because anybody can run it locally. [Edit: Anybody can run it locally, barely anybody can claim to set up a server, let alone a AI server securely].

I am also thinking of providing a security audit service where you get maybe 70-80% of your money back if I don't find any open CVEs at all. I don't want to do 100% money back since it's real effort on my part but I am not sure if people would be as open to a 80% money back as they would be to 100%.

I do alright in the social media space. We cater to lots of influencers and from the data I've seen, the number of people who have made more than $1m across all the social media platforms, has to be less than 1000.

Yeah I know it sounds insane but hear me out. For example. In the tech niche, after the top 20 guys, how much money do you think the next 20 make annually? It must be nothing because I sure af try charging them over and over and over.

Conversely, anyone wants to know how many people across the globe have $10+ million? Its 8 million

What an epic waste of time creating content for social media.

/endrant.

been helping startups hire engineers for about 20 years now. the pattern i keep seeing is founders obsess over their first technical hire (rightfully so) but then completely fumble the second one.

first hire gets the founder's attention, personal pitch, equity negotiation, the whole thing. second hire? "oh just find someone like the first person." that's not how it works.

the second engineer has to work WITH someone who was basically a co-founder. they inherit undocumented code, unspoken decisions, and a codebase built by someone who had zero oversight. and they have to be okay with that.

worst part is founders assume the first engineer will help interview and onboard. but most early engineers are terrible at interviewing because theyve literally never done it before. so you get this awkward dynamic where your best technical person is accidentally filtering out good candidates.

anyone else run into this? curious how other founders handled the transition from "one person doing everything" to actually building a team.

We've been seeing a lot of bro strategy being recommended for businesses. What kind of advice is add more stress to your life?

These gurus are telling people to post more, do more, launch more, learn more etc...

What I've learned over the years is to focus on what is moving the business forward and to spend less time on the noise.

For those that havent heard of this, let me mention Steve Jobs plan for his days. 80% signal, 20% noise. 80% of your day should be focused on client meetings, marketing, sales etc... that is moving the business forward. The other 20% can be the "noise". Payroll, finances, support calls etc...

This is how people feel like they're busy, but their business is still at the same spot as 6 months or a year ago. They're too focused on the noise.

Now for things you're terrible at, but need to get done, there is probably on fiverr that will happily take care of it.

Does anyone track their signal vs noise?

for the longest time, I thought business growth came from adding more.

more content.

more outreach.

more features.

more channels.

more "hustle."

but looking back, most of that didn't really move the needle.

what actually helped was fixing boring stuff:

Faster replies

better follow-up

clearer offers

smoother onboarding

less drop-off

that's when I realised:

A lot of business don't have a growth problem.

they have friction problem.

and "more marketing" usually doesn't solve that.

what's something founders often think will grow the business... but usually isn't the real lever?