Corner Alliance

Founder

Working with government and non-profit leaders to innovate, communicate, and build better programs, including the Department of Homeland Security, National Institutes of Health, National Institute of Standards and Technology, and Department of Commerce.

OwnerRx.com

Building the always on AI-enabled strategic copilot for SMB owners.

Owner

Entrepreneurly

Board Member

OwnerInstitute

Owner Institute helps owners grow their businesses while achieving independence.

Entrepreneurs'​ Organization

James Lee Witt Associates

Director

SRA Touchstone Consulting Group

Principal

The Touchstone Consulting Group, SRA International, Inc.

extreme blue intern

US Senator Max Baucus

Speechwriter

CEO @ Corner Alliance | Author @ The Small Business Mentor

I spent 17 years and $200K+ hunting through every business course, mastermind, and guru to find the nuggets that actually work.

EOS? Implemented it. Scaling Up? Read it. EO/YPO? Joined both.

The result? 10,000+ hours distilled into OwnerRx - the AI coach that knows every framework, every playbook, every shortcut.

What it took me years and big dollars to learn, OwnerRx delivers in seconds for a fraction of the cost.

A consulting firm came to me at 15% margins.

Target: 20%.

Five years ago, I had a playbook for this:

Old playbook:

- Better hiring → get 1-2% back (maybe)
- Global talent → squeeze out 3-5% (with cultural pain)
- Cut overhead → another 1-2% (one-time gain)

We'd grind our way to 20% over 18-24 months.

Today? That playbook is obsolete.

Here's what I'm seeing with AI agents:

Get 10% margin expansion by holding back office costs constant and growing topline.

Not cutting. Not offshoring. Not grinding.

Growing revenue without scaling headcount.

The new math:

Professional services firm:

- Revenue: $5M
- Back office: 8 people
- Margin: 15%

Deploy AI agents for:

-Financial Analysis
-Client Reporting
-Marketing
-Proposals and Quoting
-Quality Control
-Meeting analysis and follow ups
-Employee onboarding and HR 
-Client research (80% faster)
-Hiring

Result:

- Same 8 back office people
- Revenue grows to $7M (+40%)
- Margin: 25%

Alan Pentz

Owner @ OwnerRx.com | OwnerRx uses battle-tested playbooks from decades of building and coaching SMBs to create AI agents that run your business for you. | Read my newsletter: newsletter.ownerrx.com

One of biggest PE firms just allocated $1.5B to buy businesses like yours at traditional multiples, deploy AI, and watch margins expand.

Their thesis? You won't adapt fast enough.

I keep having the same conversation. Four owners last month asked me: "Should I sell before AI disrupts my business?"

Meanwhile, I invested in a metal fabrication company. The owner was spending 20-30 hours per week processing purchase orders. Not sustainable when you're trying to grow.

We built an AI system in two weeks. PO processing now takes 5 minutes. He got 25 hours of his week back.

We're closing on our second acquisition next month. Same playbook: build the AI capability once, plug each new company into the same operating system.

That's exactly what the PE firms are doing. At scale.

Here's the data that matters:

95% of AI pilots fail. But the 5% who break through? 91% see revenue boost. 86% improve margins.

This isn't a technology problem. It's a commitment problem. Pilots are experiments nobody owns. The winners pick one process, assign ownership, and measure results until it works.

The rinse and repeat.

The gap between "wanting to use AI" and "actually transforming your business" is where most owners get stuck.

That's exactly the gap PE firms are exploiting.

I'm not going to pretend I'm not doing the same thing PE firms are. The difference: I'm showing you exactly how it works so you can do it yourself.

Build the capability yourself, or become someone else's margin expansion play.

What's the one process eating 20+ hours of your week that you keep saying you'll fix "next quarter"?

I spent 10 hours a day for 4 days in a row re-building all my AI workflows last week.

3 months ago, I was building OwnerRx, the newsletter, and my Linkedin. I had 4 vendors helping with each aspect. Spend was out of control at $30k a month.

Now I've replaced them all with AI agents. That saves $360k a year.

First came the client tracker agent - every interaction, deadline, and renewal date monitored automatically. 

Then the meeting analyzer that turns Zoom recordings into 5 different artifacts to track and follow up on the meeting content.

The content pipeline was the game-changer. What took 2 hours to write now takes 3 minutes to generate and 15 minutes to polish.

Total investment: 100+ hours of my nights and weekends. 
ROI: 20 hours a week saved and $360k

But there's a downside: the exhaustion is real.

Every improvement reveals 10 more possibilities. Fix the client tracker? Now you see how broken your invoicing is. Automate content? Your distribution system looks ancient.

Last week's 4-day marathon started as "quick workflow optimization." 

The shift from doing work to building tools that do work isn't optional anymore. Teams still manually tracking clients in spreadsheets are losing 15-20 hours weekly that automated teams invest in growth.

My clients now run smoother with zero employees than they would with 5. 

But the pace is picking up. Some people spend all day building tools to make their tools work more effectively.

I'm not sure how many of us can handle it but the productivity increases are real and some people are achieving breakout.

I built a fully agentic CRM for my company in 2 days.

It wasn'ta proof of concept. It was production system running 24/7 in Azure.

Here's what happened:

My business development team was drowning in manual work—monitoring government opportunities, researching competitors, qualifying leads, syncing everything to our CRM.

15+ hours a week on work that should be automated.

So I built an agentic system using Claude Code:

• 6 specialized AI agents (qualification, research, competition/teaming, pipeline analysis, capture coaching)
• An "antagonist agent" that challenges every recommendation
• Full integration with Microsoft Dataverse, Teams, and Azure Bot Service

Total build time: 2 days.

The revolution isn't the technology.

It's that you don't need to build from scratch anymore.

Microsoft's Agent Services. Google's Vertex AI Agents. Anthropic's Claude.

These platforms give you the primitives. The authentication. The hosting. The integrations.

Your job is now architecture and orchestration, not infrastructure.

The barrier to building intelligent automation just dropped from "hire a team for 6 months" to "focused weekend with AI coding assistants."

The companies that win in 2025 won't be the ones with the biggest IT budgets.

They'll be the ones whose leaders can translate business problems into agentic solutions.

What manual process in your business would you automate first if you could build a custom agent in days instead of months?

Every owner I coach learns ChatGPT in 2-3 weeks.

That's not where they get stuck.

They get stuck at: Which workflows do I transform first? How do I get my team to actually use this? What does a "proprietary AI advantage" look like for MY specific business?

The real question isn't "which AI tool should I use?"

It's "how do I turn my company into an AI learning machine?"

That's a completely different problem. And most owners have no idea how to solve it.

62% of SMB owners say their top barrier isn't the technology—it's understanding how AI actually helps their business (Salesforce, 2025). Same survey: 62% cite no in-house expertise.

The tools are easy. The strategy is hard.

That's why 95% of AI pilots fail. Owners solve tactical problems without a strategic plan. They buy solutions to problems they haven't defined.

The questions that actually matter:

1. What's the ONE workflow costing you the most time or money right now?
2. What would it look like if AI handled 80% of that?
3. Who on your team has authority to change how that work gets done?
4. What would you measure to know it's working?

If you can't answer these four questions, you're not ready for tools.

You're ready for a plan.

75% of SMBs are experimenting with AI. I'd estimate that less than 1% have achieved anything resembling scale deployment.

The gap isn't technology. It's strategy.

What's the AI tool you bought that's still sitting unused?

I spend a lot of time thinking about what a $5M business looks like in three years.

Here's what I see coming:

Significantly fewer employees doing the same revenue.

Not because AI replaced people. Because AI handles the stuff that eats most of everyone's day—first drafts, research, scheduling, follow-up, pattern recognition.

Humans do what humans are actually good at: relationships, judgment calls, strategy, creative problem-solving, managing the exceptions.

The real moat? Proprietary systems trained on years of YOUR client data.

Your competitor using generic ChatGPT can't touch the quality of insights you're pulling from your own history. They're guessing. You're predicting.

I'm already seeing early versions of this.

At the metal fab company I invested in, the owner was spending 20-30 hours a week on PO processing. Now it takes 5 minutes. That's not incremental improvement. That's a different business.

The firms that wait? They become acquisition targets for the ones that didn't.

The 2028 firm isn't about replacing humans.

It's about humans finally doing what only humans can do—while everything else runs without them touching it.

The question isn't whether this future is coming.

It's whether you're building toward it or drifting toward being acquired by someone who did.

Last month I had the same conversation with four different owners. All professional services - consulting, marketing, accounting. All asking the same question: "Should I sell before AI disrupts my business?"

Not one of them is failing. They're all profitable. But they see what's coming.

I asked each of them the same questions: 

-Are you willing to learn this yourself - not delegate it? 
-Can you force organizational change even when your team resists? 
-Will you commit 2-3 years to rebuilding how work gets done?

One went quiet. Then honest: "I'm 5 years from retirement. I don't want to spend them becoming a technologist."

That's not weakness. That's clarity.

Here's what's interesting: these are all knowledge work businesses. The consulting firm owner is more worried than the metal fabrication company I invested in. 

Professional services feels the threat more acutely because their product IS knowledge work - exactly what AI does well.

Here's what I'm seeing: Owners who built great businesses over 20 years are struggling because they can't make themselves learn new systems. 

PE-backed competitors are acquiring AI capability through rollups. Multiples that look reasonable today won't in 18 months.

So I've started having a different conversation. Three paths:

BUILD: Learn deeply, force change, create proprietary AI workflows that competitors can't copy. 2-3 year commitment minimum.

PARTNER: Bring in PE or an operator who already has AI capability. Trade some equity for transformation capacity.

EXIT: Sell while you can get 5-8x EBITDA instead of waiting until AI-enabled competitors compress your margins to 2-3x.

No wrong answer. The only wrong choice is "wait and see."

This isn't pessimism. It's strategic honesty.

Do you have an AI strategy yet ?

$300K.

That's what each failed sales hire costs when you add: salary + lost deals + operational chaos + owner time back in the weeds.

The owner I talked with last week had just gone through his third failed sales hire. 

The pattern?

"We hired for product knowledge... failed to look at character."

But here's the deeper mistake:

They were trying to hire ONE person who could do everything the founder does.

Product expertise + all the relationships + sales nuance + operations + strategy.

That's not a job description. That's a unicorn.

And unicorns don't exist.

Here's what happens when you track your sales process with AI and ask: "What am I actually doing?"

AI breaks it down:

- Marketing: 9 hours/week (lead gen and qualification)
- Admin: 5 hours/week (Writing and sending followups, updating the CRM and dashboards)
- Selling: 7 hours/week (actual conversations with buyers)
- Meetings and Reporting: 5 hours/week (in internal meetings and preparing for those meetings)
-Customer Service: 10 hours/week (Talking recent sales through onboarding issues)

You're not hiring for one role. You're trying to get one person to do a bunch of different stuff.

The AI insight:

Don't hire 1 "unicorn" at $150K who'll fail in 18 months.

Engineer it into 3 achievable roles:

- Sales Rep ($75K) - hire for relationship skills and ability to close
- Operations Coordinator ($55K) - hire for ability to track actions, update the CRM, and do follow ups.
- Customer Service Rep ($60K) - hire for deep product knowledge and ability to answer customer questions 

Then AI generates hiring scorecards for each:

- 5 character traits (integrity, ownership, learning ability, culture fit, resilience)
- 5 technical competencies (specific to THAT role, not "do everything")
- Interview questions revealing both dimensions
- Red flags from your past failed hires

The real problem:

You're not bad at hiring.

You're trying to hire another version of yourself.

The solution:

Stop looking for unicorns.

Start engineering roles AI can help you fill.

Drop your calendar export in ChatGPT and ask:

"What am I actually doing, and should this be 1 role or 3?"

Every SMB owner faces a choice in the next 18 months.

Here's the framework I walk through with every owner I work with:

BUILD: if you have 3+ years before exit, genuine interest in learning the tech, a team capable of change, and appetite for hard work. You'll create moats your competitors can't copy.

PARTNER: if your value is in your client base or team, you want to stay involved but not lead transformation, and you're open to being part of something larger. Trade some equity for transformation capability.

EXIT: if you're 5 years or less from wanting to stop, have no interest in learning AI deeply, or your team can't change. Sell while multiples hold.

There's no wrong choice among these three.

But there IS a wrong move: no choice.

Waiting is a choice. It's choosing to let the market decide for you.

I had four conversations last month with professional services owners asking whether they should sell. All profitable. All seeing what's coming. The honest ones are asking themselves hard questions about which path fits them.

The owners I worry about aren't the ones who choose to exit. They're the ones who won't build AND won't sell. Who hope disruption passes them by.

Which path are you on? And if you're honest with yourself—are you actually on a path, or are you just waiting?

OpenAI just launched ChatGPT Shopping 3 days before Black Friday. It's built for products.

But if you run a professional services firm, the behavior change matters more than the feature.

People are getting trained to ask AI for recommendations instead of searching Google. "What do I need?" "Who can help me?" "Who's best for my situation?"

Right now, that's mostly products. But the habit is forming.

So I ran an experiment.

I asked ChatGPT: "Who are the best fractional CFOs in Austin for manufacturing companies doing $5-10M?" (Congrats to vcfo Austin, you won)

What showed up varied each time I asked with a slightly different query (AI results aren't consistent like Google). But patterns emerged in what seemed to influence recommendations:

- Firms with clear website positioning about who they serve
- Those with substantial Google reviews
- People mentioned in industry publications
- Content that directly answered the type of question I asked

The firms with vague "we serve everyone" messaging? Didn't appear.

Here's my hypothesis for professional services:

Your next client might never Google you. They might ask AI. And AI appears to synthesize everything it finds about you into a recommendation. Or not.

This isn't proven science yet. But it's worth investigating.

Three things worth trying this week:

1. Ask ChatGPT who the best [your profession] in [your city] are for [your ideal client type]. Run it 3-4 times. See patterns in who shows up and what signals seem to matter.

2. Look at your Google reviews. Not just the star rating. The actual words clients use. AI reads those.

3. Check if your website clearly states who you serve and what problems you solve. Specificity seems to beat vagueness.

The shopping feature is for products. The behavior shift affects all of us.

What patterns did you notice when you ran the search for your profession?

One of my coaching clients delegated AI to an entry-level ops person.

She had no training. She had no authority. She had no idea what problem she was supposed to solve.

Three months later: nothing. Not because she failed. Because she was set up to fail.

Here's the hard truth: You can't delegate something you don't know how to define.

Most owners want to hand off "figure out AI" to whoever has bandwidth. It never works. Because AI transformation isn't a task. It's a fundamental shift in how work gets done.

Your employees need to go from "doing the work" to "building systems that do the work."

That's not a training problem. That's an identity problem.

The people who built their careers on being great at execution? They often struggle the most. Their value has always been doing the work well. Now you're asking them to make themselves obsolete.

Meanwhile, owners who lead it themselves—who learn the technology, pick the workflow, define the success metrics—see results in weeks, not months.

The gap isn't capability. It's ownership.

If you don't understand AI well enough to define what success looks like, you can't delegate it. Period.

You either learn it yourself or you hire someone who already knows. There's no third option where you hand it to whoever's available and hope it works out.

Who on your team could actually lead this? Not "who's available"—who has authority AND understands the work?

If you can't name them in 5 seconds, that's your answer.

Talked with an owner last week who runs a $10M compliance consulting firm for large construction projects.

$3M EBITDA. Niche expertise. Regulatory moat.

But AI is coming for the core deliverable. The environmental studies his team spends weeks researching and writing? AI can now draft those in hours. Not perfectly—but good enough to commoditize the work.

His question: When do I sell?

He's the sixth owner in two months who's asked me some version of this.

The trap: Actual disruption might be 3-5 years out. But buyers see the writing on the wall earlier. By the time your industry is visibly changing, your multiple has already dropped.

You're not racing disruption. You're racing the perception of disruption.

His business trades at 5-6x EBITDA today. If buyers start pricing in AI risk, that becomes 3-4x. That's a $6M swing on the same business.

My advice to most owners: Go BE the AI change. Use AI to produce studies faster and cheaper. Become the consolidator, not the consolidated.

But that's not everyone's game. Some owners are 5 years from retirement. Some don't want to bet a 20-year business on a tech transition.

Both paths are valid. What's not valid is deciding without understanding what AI can actually do today.

I've watched owners dismiss AI while competitors train it on exactly their workflows.

I've also watched owners panic-sell businesses with 10+ years of runway.

The only way to know which camp you're in? Get your hands dirty. Not reading headlines. Actually testing AI against your deliverables.

Then you can decide instead of guess.

Are you building toward disruption or planning your exit?

I had two AI agents argue about why their businesses would fail.

 Mike owns a $5M accounting firm. Sarah runs a $3M marketing agency.

 I told them the hard truth: 50% of entry-level white-collar jobs could disappear in 1-5 years.

 Then I asked about their most valuable asset.

 Mike: "Janet. Senior CPA, 20 years experience. Even if I document stuff, it's impossible to capture everything she knows."

 Me: "How many client calls has Janet been on in 12 years? 200 a year? That's 2,400 conversations of expertise that vanished the moment they ended."

 Mike got quiet.

 Sarah jumped in: "It's worse. Every time my strategist Jess explains why a headline doesn't work. Every Slack message with feedback. That's our IP. And we're just... letting it evaporate."

 Here's what landed:

 Janet sees 40 restaurant clients. She notices patterns—tip reporting differences between Texas and California, depreciation flags across the board, underused deductions.

 That pattern recognition? Locked in her head. Maybe mentioned at a staff meeting. Mostly just sits there.

 Now imagine Janet with AI surfacing: "17 of your restaurant clients haven't claimed the energy efficiency credit. 12 likely qualify."

 Janet goes from processing work to generating work. From reactive to proactive.

 The gap isn't "who has AI."

 It's who's been feeding it.

 A competitor who started capturing 6 months ago has 6 months of compounding knowledge you can't catch up to.

 What expertise walked out your door last night that you'll never get back?

$1.2M revenue. Paper invoices. No contracts longer than 90 days.

That's what "riding a macro wave" actually looks like up close.

I'm a small investor in a metal fabrication roll-up. The operators are driving it—I just saw the thesis and backed the right people.

Here's the thesis: deglobalization is real. The US needs onshore manufacturing for defense and infrastructure. Data centers, military rebuilding after Ukraine and Israel, reshoring—all of it needs domestic fab capacity.

But where does that actually show up for smaller operators?

In fragmented, blue-collar industries with antiquated systems. Metal fab shops doing $1-2M/year, run by craftsmen tracking jobs on index cards. No modern software. Books that make accountants cry.

These aren't bad businesses—they're undervalued businesses waiting for operators who can upgrade the systems.

What we learned 18 months in:

The first year was rough. It took almost a year to really learn how to run the business. Volatile revenue, no long-term contracts, steep learning curve.

But if you buy cheap enough—1-2x profits, not 3-4x—you can absorb that volatility while you stabilize operations.

Now we're acquiring a shop that serves defense contractors with significant contract backlog. The thesis is playing out.

Stack a few $1-2M shops together and you're in double-digit revenue with consistent work from defense and data center buildouts.

The real insight: you don't need to be in tech to profit from macro trends. Find the small, fragmented industries that support the big shifts. Get there before the investment wave.

My bet: we'll see larger players start rolling up metal fab over the next few years as they recognize the consistency of work coming from reshoring, defense, and infrastructure.

The opportunity is in boring industries that serve emerging priorities.

What's the fragmented industry in your world that's quietly riding a macro tailwind?

805% increase. That's how much AI-driven retail traffic grew this year.

And here's the split most SMB owners are missing:

ChatGPT is going to need to focus on consumer rather than enterprise —shopping features, product discovery, the new front door for buyers. Despite OpenAI's protestations the consumer market is just too big.

The stats tell the story:

- 57% of consumers will use AI for holiday shopping
- AI-influenced shoppers convert 38% better
- AI can increase service productivity by 30-45%

Two different numbers. Two different strategies.

If customers find you (retail, restaurants, local services):
ChatGPT is becoming a search engine. 805% traffic growth means if you're not showing up in AI answers, you're becoming invisible. This is SEO 2.0.

If customers hire you (law firms, accountants, consultants):
Being "found" by AI matters less than having AI that works. Claude and Microsoft are betting on agents—AI that handles the $85/hour work your team shouldn't be doing.

The mistake? Treating both like the same problem.

A bakery needs to rank in ChatGPT's "best birthday cake" answers.
A CPA firm needs agents that prep returns and flag anomalies.

Same technology. Completely different investments.

24,000 hours.

That's how much client interaction one consulting company records per year.

Most would say: "That's expensive storage."

They're thinking: "This is our competitive moat."

Here's what they discovered:

AI analyzed those recordings and found something competitors can never replicate:

Their methods deliver outcomes 1.5 standard deviations better than industry average.

Not "we think we're better."

Data-proven superiority from analyzing thousands of real sessions.

Now they can:

- Prove results to justify premium pricing
- Train new staff 3x faster using what actually works
- Continuously improve by spotting patterns in top performer sessions
- Show clients exactly why their approach works

*his is happening across industries:

A coaching business recording sales calls:

- AI identified: Top closer uses these 3 questions, bottom performers don't
- Automated quality coaching for entire sales team
- Conversion rate: 30% → 40% in 90 days

The dark data problem:

Right now, every meeting in your company contains:

- What actually works (buried in someone's memory and an unprocessed transcript)
- What clients really care about (mentioned once, forgotten)
- Patterns that predict success/failure (invisible without AI)
- Your team's best moves (can't scale what you can't see)

It evaporates the moment the meeting ends.

What AI can do with recordings:

1. Pattern recognition: What do top performers do that others don't?
2. Outcome correlation: Which approaches actually drive results?
3. Training acceleration: New hires learn from 100s of real scenarios
4. Competitive proof: Data-backed claims vs. competitor marketing fluff
5. Continuous improvement: Spot quality drift before it costs you clients

The 10x value play:

Companies recording systematically are building:

- Proprietary methodology (competitors can't copy)
- Pricing power (proven better outcomes)
- Faster onboarding (new hires effective in weeks vs. months)
- Quality consistency (AI catches drift)
- Category leadership (your data becomes industry benchmark)

First-movers are building 2-3 year leads.

The objections I hear:

"Storage is expensive" → Storage is $50/month. Lost knowledge costs $50K+
"No one will review it" → AI reviews it. Humans get the insights.
"Compliance nightmare" → SOC 2 + consent frameworks exist. Not harder than current QA.
"Clients won't consent" → Position as "quality improvement" + show benefit. 95%+ consent.

Most SMB owners think:
"We're too small for this."

Reality:
You're the perfect size. Big enough to have volume. Small enough to move fast.

The companies doing this wrong:

Recording but not analyzing. Terabytes of dark data, zero insights.

The companies doing this right:

Every recording becomes training data. AI finds patterns. Insights improve delivery. Better results justify premium pricing. Category domination.

Do you really want to share good content during Thanksgiving week?

I've got some gems saved up but kind of feel like everyone's still talking to their family at this point.

Maybe by Friday they are back on linkedin trying to do anything but talk with their family?

OpenAI's pricing dropped 99% in 18 months. Your competitor can copy your prompts in 30 seconds.

  So where's your edge?

  There's no moat in "using AI." Everyone has access to the same tools.

  The moat is in learning loops. AI that gets smarter from YOUR customers.
  Systems that improve from YOUR data. Feedback loops competitors can't
  replicate.

  That's what focusing on for each of my clients and each of my businesses. You need to use AI to start learning from YOUR customers. No one else can learn from that but you. 

  A competitor starting fresh would need months of your data to catch up.

  The same principle works at any scale:

  Your proposal tool learns what wins for YOUR specific buyers.
  Your service AI improves from YOUR customer conversations.
  Your operations system optimizes for YOUR quirks.

  Most SMBs buy tools. Few build loops.

  The question isn't "are you using AI?"

  It's "is your AI getting smarter every day in ways competitors can't
  replicate?"

I'm seeing a new pattern emerge.

SMB owners (not PE firms) doing their own roll-ups. Building AI into their operations first, then using that capability to acquire competitors who didn't.

I'm doing this myself. The metal fab company I invested in is closing on its second acquisition. Same playbook both times:

- Build the AI operating system once (quoting and PO processing went from 20-30 hours/week to 5 minutes)
- Acquire a competitor at traditional multiples
- Plug them into the system that already works
- Use their data to make the AI smarter
- Rinse and repeat

The competitors who were "waiting to see how AI plays out" are becoming acquisition targets.

This isn't just us. I'm watching coaching clients think the same way. The ones who built AI capability aren't worried about PE roll-ups anymore.

They're thinking about doing roll-ups themselves.

The math is simple: AI doesn't just improve your margins. It makes every future acquisition more valuable. The capabilities compound.

Two years ago, owners in the $5-10M range were worried about being acquired.

Now some of them are the acquirers.

Same revenue bracket. Different strategy. Completely different trajectory.

Are you building the operating system that makes you the buyer—or waiting until someone else's system absorbs you?

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