Software stocks lost more than 20% of their value in 2026, roughly $1 trillion, while the S&P 500 stayed flat. Companies that used to buy hundreds of thousands of dollars of software are buying a handful of AI subscriptions instead.

The technology at most of those companies is good. A lot of it is better than it has ever been.

Jeff spent twenty years as a fractional CRO evaluating, buying, and implementing technology for revenue teams. This episode covers three companies that handled trust very differently, and the checks an owner can run before signing anything.

Chapters

00:00 The SaaSpocalypse

00:25 Technology is a business

00:49 Why the SaaS model rewards stickiness

01:19 Sticky contracts

01:51 How trust gets built now

01:59 Twenty years buying technology

02:37 Example one: the frontman

04:26 The tells I found later

04:53 Why they never scaled

05:33 Example two: the partner network

05:57 Why most teams use a fraction of their CRM

06:12 How Salesforce built its ecosystem

06:54 HubSpot's version of the same move

07:34 Example three: the slow route

08:12 FDA clearance and Medicare billing

09:04 What trust actually does for a company

09:29 If you are buying

11:38 The real cost of switching

12:10 If you are selling

13:14 Trust closes, delivering renews

Links

The High-Stakes AI Playbook: https://goSOS.ai/playbook

SOS AI: https://goSOS.ai

Sources

Forbes, SaaSpocalypse Now? AI Is Disrupting SaaS, February 2026

Aidoc, CARE Body CT Multi-Triage receives eligibility for Medicare New Technology Add-on Payment, August 2026

Wildfires are closing businesses across the Okanagan right now. Owners here are asking whether they still owe their staff a paycheck when the doors are shut and no money is coming in.

Jeff went looking for the rule that answers this. The rule does not exist.

British Columbia protects job security for illness, maternity, parental leave, family responsibility, compassionate care, critical illness, reservists, bereavement, and jury duty. Wildfire and evacuation appear nowhere on that list.

This episode gives owners the People Policy, a three-question framework for making people decisions when nothing is written down. The same three questions apply when the disruption is a technology deployment instead of a fire.

Chapters

00:00 Watching the fire from our rooftop

00:39 The night we housed our staff

02:16 Growing up on fire and flood job sites

04:13 The bakery that never reopened

05:04 The owners nobody thinks about

06:03 One owner asked me: do I pay them?

07:44 What the law actually covers

09:35 Where insurance stops

10:03 You need your own principles

11:08 Why this is Decision 7

11:54 The People Policy: three questions

14:18 Applying it to fire, flood, and AI

15:19 Decide it, live it, be proud of it

Get involved

Mamas for Mamas Fire Support: https://www.mamasformamas.org/firesupport/ The High-Stakes AI Playbook: https://goSOS.ai/playbook SOS AI: https://goSOS.ai

Sources

Province of British Columbia, Leaves of Absence, Employment Standards Province of British Columbia, Termination of Employment, Employment Standards Government of Canada, Work-Sharing Program Insurance Bureau of Canada, Wildfire Season

Five years ago I sat on a panel with some of the top voices in sales, and we named AI the biggest loss of the year. Today I use these tools daily, and so do most of the owners I talk to.

The tools got good. The question of whether you can trust them got harder, because the models most people use are designed to make the output feel right.

In this episode I walk through the six or seven months of SOS Signals that taught me not to trust software I built myself, the controls I added because of it, and two live examples of what a trustworthy system looks like in practice.

IN THIS EPISODE

- Why the consumer models optimize for engagement, and what that costs you

- The point where the stakes outrun what an LLM can carry alone

- AI generated, human verified: the rule that caught a failure rate I did not expect

- Link validators, source gates, and confidence levels

- Twelve words, five vendors, and where deterministic software beats a reasoning model

- A weekend rebuild that took a tool from two out of seven to five out of seven

THE TEST: The Every Single Time Test

Pick one small task that is not important enough to think about and still eats real time. Ask three questions about the tool you use on it.

1. Do I trust the result?

2. Can I click the evidence and check it myself?

3. Does it give me the same result every single time?

I CHALLENGE YOU

Run those three questions on one tool you already pay for this week. Write down the exact point where the answer breaks.

This episode maps to Decision 6 in The High-Stakes AI Playbook: how will we know whether AI is creating value. Request a copy at goSOS.ai/playbook

Real Companies, Real People, Real AI.

Stay Human Boss.

There's always one person accountable in your business. If nobody below you owns the decision, that's you. AI doesn't change that. It just makes it easier to forget.

I get into why in this episode: the AI never answers for anything, it's a tool, your automation, your system. The buck stops with the person at the top, whether you did the work yourself or handed it to AI or an employee. That's not a new rule. Accountability's always worked that way.

Connecticut's Supreme Court just proved it. Their June ruling puts the blame squarely on the person who signs off, not the AI that helped write it. A public tracker has logged over a thousand US court cases, and close to fifteen hundred worldwide, where AI-hallucinated material got submitted and a court had to respond. The fines used to be four figures. They're climbing into five now.

I also tell you about the time I let an automation loose on my own business and it backfired, wrong emails, angry leads, a call I didn't want to get. I owned it. That's the whole point.

By the end, you'll have one test to run on your own business: name the decision, name the person, ask if they could defend it in front of a judge. If they can't answer clean, you've found the first thing to fix.

Request your copy of The High-Stakes AI Playbook: goSOS.ai/playbook

Listen to The Signal: jeffswan18.substack.com

#HumanBoss #AIforREAL #TheSignal

Meta and xAI are both moving to sell off their excess AI capacity. The headlines are calling it a retreat, proof the AI bubble is deflating and demand is drying up. I read it differently.

Owners aren't walking away from AI. They're worn down by broken promises and expensive tools that never delivered what the sales deck swore they would. Demand for results is still there. What's gone is the patience for hype.

In this episode I get into why the biggest players in tech spent billions and still ended up with a barely worth it share of the market, and what that tells you about your own AI spend. I bring it home with two stories: a promise I broke to my ten year old daughter, and a dairy farm that knew exactly what it was buying and could measure it down to the minute.

The question every owner should be able to answer before spending another dollar: what is this actually supposed to do for me, and can I prove whether it did?

The farm could answer it. Big Tech couldn't. That's the whole episode.

Request your copy of The High-Stakes AI Playbook: goSOS.ai/playbook

Listen to The Signal: jeffswan18.substack.com

#HumanBoss #AIforREAL #TheSignal

Is your best employee your biggest risk? I'm asking because I just lived the answer.

This week I recorded The Signal from the road because I finally took a vacation with my daughter, and the show still shipped. It shipped because I moved my agents off my home computer and onto the cloud, so the work runs whether I'm at my desk or on a beach. That small move is the whole episode.

Every business has one person who knows how it all works: the deals, the customers, the system in their head.

They are your most valuable person, and they are also your single point of failure. When they are out, the work waits. When they leave, it walks out the door with them.

In this episode, I walk through how I built SOS Signals to fix exactly this for two B2G sales teams, where the knowledge that drove every win was trapped in two people living out of suitcases. I get into the ER version of the same problem, where overcrowding turns into real harm, then hand you the four questions I run before AI or automation touches any task.

What you'll hear:

- Why the show shipped from vacation, and the home-PC-to-cloud move that made it possible

- The two key people whose knowledge left the building every time they traveled

- How SOS Signals shared that knowledge with the whole team, even when the experts were on a plane

- Why the goal is to protect your people and make the whole team stronger

- The four questions: what to outsource, what suits AI, what controls you need, what outcome is acceptable

This one is close to home for me, and I think it will be for you too.

What single point of failure is quietly running your business? Tell me in the comments.

Find a breakdown of how I make important business decisions with AI at goSOS.ai/playbook.

Stay Human Boss.

#HumanBoss #AIforREAL #HighStakesAI #AIAmplification

AI is winning real court cases right now, and I know the feeling firsthand. A few years ago I represented myself across five court appearances in a case that mattered to my family, using ChatGPT to build the case and local duty counsel to keep it legal. I won four of those five appearances. The fifth one still stings, and it taught me more than the four wins did.

In this episode, I walk through exactly how I built each case, where AI carried the load, where I needed a human, and the three mistakes that cost me that fifth appearance. Then I hand you the four-question framework I now run on every task before I let AI or automation touch it.

What you'll hear:

- How I paired ChatGPT with licensed duty counsel to prepare a self-represented case

- The verify-everything control that kept fabricated citations out of my filings

- Why trying to pay nothing at all was the real mistake

- The four questions: what to outsource, what suits AI, what controls you need, what outcome is acceptable

- A real UK case where a freelancer ran the corrected plan, AI for prep plus a licensed barrister in the room, and won

I'm sharing my own experience here. This is not legal advice, and in most court matters you should have a lawyer.

Apply the four questions to one task this week and tell me how it goes in the comments.

Request The High-Stakes AI Playbook at goSOS.ai/playbook.

Stay Human Boss.

#HumanBoss #AIforREAL #HighStakesAI #AIAmplification

Claude launched Fable as its most powerful model yet. Within days, the US government placed it under export controls, and Anthropic had to disable it for every customer to comply.

In E15, Jeff uses that overnight shutdown to make the case at the heart of Decision 5 of The High-Stakes AI Playbook. Never hinge your business on a single vendor, a single model, or a single platform.

He walks through the three layers of control that keep an operation running when a tool disappears: the tools you choose, the data you own, and the people you prepare.

IN THIS EPISODE

- Why the Fable shutdown is a real-world example of the Vendor Capture Trap

- The strongest case for going all-in on one vendor, and why it does not hold

- Layer one: choosing flexible tools you can switch between

- Layer two: owning your data so you can move between models

- Layer three: preparing your people to handle change without losing a step

CHAPTERS

00:00 The morning Fable disappeared

00:32 What the US government actually did

01:06 Decision 5: don't bet your business on one vendor

01:24 A disagreement with a friend in the industry

02:31 The $1,500 cap and what it tells you

03:32 Why I build with model-switching

04:53 Layer 1: Choose flexible, switchable tools

07:45 Layer 2: Own your data

10:36 Amplify, don't replace

12:16 Layer 3: Prepare your people for change

14:26 Take the driver's seat

KEY TAKEAWAYS

1. A tool can vanish overnight through no fault of your own, so build for that from the start.

2. Control over your inputs is what protects continuity, from the solo operator to the global CEO.

3. Amplify your people with AI, and never bet the business on one model.

LINKS

Request the book: goSOS.ai/playbook

The Signal on Substack: jeffswan18.substack.com

Follow Jeff: @jeffswan18

Stay human boss.

Episode 14: You Don't Need AI

A lot of operators are asking lately whether they really need AI. The honest answer surprises most of them.

Nobody really needs AI. It is a tool, and tools serve specific purposes. What most operators get wrong is treating AI as a category instead of as a deployment choice.

What you'll hear:

- Why AI tools are designed for engagement the same way social media platforms are

- The difference between structured automation (deterministic) and AI (probabilistic)

- How both technologies combine in the flood mitigation agent we have been building

- The Air Canada chatbot case and what unstructured tools do when they manage structured conversations

- Why the real failure point in most AI deployments is leadership culture, not the technology

- The three questions to answer before deploying any AI

The three-question test:

1. What problem are you actually solving?

2. How else could you solve it?

3. Who is going to make it work?

Three yes answers mean the deployment is worth committing to. Any no is a signal to slow down.

The framework is Decision Three in The High-Stakes AI Playbook, launching Q3 2026. The manuscript is open for early access reads. Reply to the newsletter or DM me on LinkedIn for a copy.

Find more at outboundsos.com

Subscribe to the #NoVendors newsletter at jeffswan18.substack.com

Episode 13: Your AI Bill Shouldn't Scare You

Most operators looking at AI see the headline pricing and budget for that. What they miss is the way AI tools actually charge, which is by token consumption. Long chatty inputs and detailed outputs both consume tokens, and the bill arrives at the end of the month based on what you used.

The fix is not about using less AI. The fix is matching the model you are using to the task you are trying to accomplish.

What you'll hear:

- Why AI bills surprise operators and what's actually being measured (tokens, not seats)

- The three model tiers - premium, workhorse, budget - and how they price differently

- A real comparison where the same task cost $1,000 on premium and $42 on budget

- Three questions for matching the model to the task (complexity, volume, judgment)

- How caching and batching compound the savings

- A real example of how SOS Signals uses all three tiers in a coordinated workflow

The framework is a compressed version of Decision Four in The High-Stakes AI Playbook. The book covers the full build versus buy decision tree and the architecture choices that determine whether AI is a cost line or a profit lever.

The manuscript is open for early access reads. Reply to the newsletter or DM me on LinkedIn for a copy.

Find more at outboundsos.com

Subscribe to the #NoVendors newsletter at jeffswan18.substack.com