July 2026

In 2008, the financial world was coming apart at the seams. I was at Morgan Stanley, and no one knew what was coming next. But when leadership came in to talk to us, they did it in a way that let us exhale. They didn’t paint a rosy picture. They were direct, and they brought us into the process of solving the problem. At a time when giants like Lehman Brothers and Bear Stearns were crumbling, they gave us a lifeline of confidence. They reinforced the idea that we were partners in finding a way forward, and they rallied the team at a moment when morale was at rock bottom.

Every leader will eventually have to deliver disappointing news — a missed target, a restructuring, a canceled initiative, a budget reduction, a layoff. These conversations are hard for everyone involved. Behind every business decision are people whose work, plans and expectations may be affected.

Over the course of my career, I’ve learned that trust isn’t damaged by the news itself. Trust is damaged when people feel surprised, confused or excluded from understanding why decisions were made. Trust gets built one transparent conversation at a time.

When leaders communicate difficult news with clarity and honesty, people are far more likely to stay engaged — even when they disagree with the outcome. I rely on a simple four-part framework whenever I have to deliver a hard message. It helps people understand what is happening, why it is happening and how we move forward together.

Start with the facts

When people sense bad news is coming, they want clarity. Leaders often spend too much time building up to the message. They provide excessive background, soften the language or avoid the core issue altogether. As a result, people become distracted trying to figure out what is actually being said.

State the decision clearly and early. We are reducing the size of the organization. We will not hit the target we committed to this quarter. We’ve decided to stop this initiative.

Direct communication is a form of respect. It gives people a clear understanding of the situation and lets them focus on the information that follows.

Explain the business context

Once people understand the decision, they need to understand the reasoning behind it. Context matters because it connects the decision to the broader realities the organization is facing. Without it, assumptions and skepticism fill the gaps.

Whenever feasible, share the factors that led to the decision — the business conditions, strategic priorities, market changes or operational realities that shaped the outcome. The goal isn’t to justify the decision or win consensus. It’s to help people understand it. When people understand the circumstances leaders are navigating, they are better able to accept difficult outcomes and maintain confidence in the team steering the ship.

Acknowledge the impact

Business decisions affect people differently. Some will feel disappointed. Others may feel uncertain, frustrated or worried about what comes next. Leaders should acknowledge that reality directly.

If you hired well, these are sharp, capable people — they need information, and they need to know you’re mindful of them. Leaders who cling to platitudes miss the chance to create alignment and squander the trust of their team in the process.

People want to know that leadership understands the consequences of the decision. They want to know that leaders have considered the human side of the equation. Acknowledging impact doesn’t require lengthy emotional discussions. It requires awareness, sincerity and respect.

Provide a path forward

After difficult news is delivered, attention quickly shifts to the future. People want to understand what comes next, what priorities remain unchanged and where to focus their efforts.

This is where leaders need to create direction. Be forthcoming about next steps. Clarify expectations. Explain where the organization is headed and how the team will move forward. Even when circumstances are challenging, clarity creates stability. People can navigate uncertainty when they understand the mission and their role within it.

The moment that matters most

It’s easy to be a good leader when the news is good. The moments that actually shape trust are the difficult ones. People remember whether leaders communicated openly. They remember whether they got honest, authentic explanations. They remember whether they were treated with respect.

In my experience, difficult conversations become far more effective when leaders focus on four things: communicating the facts, providing context, acknowledging impact and creating clarity about what comes next.

The news may still be hard. The relationship doesn’t have to be.

In 2008, the financial world was coming apart at the seams. I was at Morgan Stanley, and no one knew what was coming next. But when leadership came in to talk to us, they did it in a way that let us exhale. They didn’t paint a rosy picture. They were direct, and they brought us into the process of solving the problem. At a time when giants like Lehman Brothers and Bear Stearns were crumbling, they gave us a lifeline of confidence. They reinforced the idea that we were partners in finding a way forward, and they rallied the team at a moment when morale was at rock bottom.

Every leader will eventually have to deliver disappointing news — a missed target, a restructuring, a canceled initiative, a budget reduction, a layoff. These conversations are hard for everyone involved. Behind every business decision are people whose work, plans and expectations may be affected.

Over the course of my career, I’ve learned that trust isn’t damaged by the news itself. Trust is damaged when people feel surprised, confused or excluded from understanding why decisions were made. Trust gets built one transparent conversation at a time.

Brendan Foody, the 23-year-old CEO of AI talent and data-labeling platform Mercor, thinks that young job candidates should stay at companies for longer stretches of time. When reviewing young applicants, Foody found that average tenure was shorter than he expected; they were staying at jobs for a year before jumping to the next big thing. 

Earlier this week, Foody wrote on X that he received “too many” job applications from young people who were “serial job hoppers.” These candidates “jump to the hottest company every year” because they are under the mistaken belief that “it looks good on a resume,” he said. 

“Too many people in my generation underestimate how much relationships, reputation, equity, and trust compound over time,” Foody wrote. He added, “But look at almost anyone who’s built something extraordinary: they weren’t serial job hoppers.”

Josh Elman, partner at Silicon Valley venture capital firm Andreessen Horowitz, replied to Foody’s post on X. 

“You are right that going from job to job without meaningful contributions nor closure is a bad pattern,” Elman wrote. “But it is worth going deeper with people who continue to work on important things at important times. That perspective compounds.”

Foody added in an email to Business Insider this week that employees should pursue new jobs for the “right reasons.” For example, they could have stopped learning at a particular job. 

“Moving because the work is better is very different from moving because a logo looks good on a resume,” he noted.

Foody is one of the youngest billionaires in the world, with a net worth of $2.2 billion at the time of writing, per Forbes.

Why Gen Z is prone to job-hopping

Gen Z has earned a reputation as the job-hopping generation. A 2021 report from careers site CareerBuilder found that Gen Z workers spent an average of two years and three months in a role, compared with two years and nine months for millennials, reinforcing the idea that younger workers cycle through jobs faster than older ones.

In a 2023 survey by consulting firm Oliver Wyman, 70% of Gen Z respondents in the U.S. and UK who described themselves as “loyal” to their employer were nonetheless actively looking for a new role.

Why has Gen Z taken to job-hopping? For years, switching jobs was closely linked with higher pay, which helped normalize frequent moves as a rational strategy rather than a red flag. For example, one employment attorney who spoke with Business Insider last year grew her salary from $40,000 to $225,000 in six years by strategically job-hopping. 

Foody said he was aware of the potential financial upside to job-hopping. “Switching jobs can often be the fastest way to get a raise or a title bump in the near term, so the incentive feels real,” he said in the email to Business Insider.

He added that compensation was increasing rapidly in San Francisco, the city he lives in, contributing to the desire to switch jobs. 

“In tech, and especially in AI right now, the pull is strong,” he wrote. “The grass always looks greener.”

Brendan Foody, the 23-year-old CEO of AI talent and data-labeling platform Mercor, thinks that young job candidates should stay at companies for longer stretches of time. When reviewing young applicants, Foody found that average tenure was shorter than he expected; they were staying at jobs for a year before jumping to the next big thing. 

Earlier this week, Foody wrote on X that he received “too many” job applications from young people who were “serial job hoppers.” These candidates “jump to the hottest company every year” because they are under the mistaken belief that “it looks good on a resume,” he said. 

“Too many people in my generation underestimate how much relationships, reputation, equity, and trust compound over time,” Foody wrote. He added, “But look at almost anyone who’s built something extraordinary: they weren’t serial job hoppers.”

Scott Winters turned to ChatGPT to explain his dizzy spells that once forced the Florida pastor to stop mid-sermon. Over time, the chatbot stopped recommending he see a doctor and instead told him his symptoms were “not something dangerous,” even telling him to trust that “God did not design your body to endlessly fail.” Winters spent weeks stuck in a recliner before he was hospitalized in July 2025 with a life-threatening pulmonary embolism, the New York Times reports.

He’s now suing OpenAI and CEO Sam Altman in San Francisco Superior Court, accusing the company of negligence and the “unauthorized practice of medicine.” It’s reportedly the first lawsuit claiming a chatbot’s health advice directly harmed someone seeking medical guidance.

The case lands just as OpenAI pushes deeper into health tools like ChatGPT Health. An OpenAI spokesman said the chatbot isn’t intended for diagnosis or treatment, but that the company takes health-related safety seriously. As AI increasingly stands in for medical advice, especially for people who can’t easily see a doctor, the case raises real questions about who’s liable when that advice goes wrong.

Scott Winters turned to ChatGPT to explain his dizzy spells that once forced the Florida pastor to stop mid-sermon. Over time, the chatbot stopped recommending he see a doctor and instead told him his symptoms were “not something dangerous,” even telling him to trust that “God did not design your body to endlessly fail.” Winters spent weeks stuck in a recliner before he was hospitalized in July 2025 with a life-threatening pulmonary embolism, the New York Times reports.

He’s now suing OpenAI and CEO Sam Altman in San Francisco Superior Court, accusing the company of negligence and the “unauthorized practice of medicine.” It’s reportedly the first lawsuit claiming a chatbot’s health advice directly harmed someone seeking medical guidance.

The case lands just as OpenAI pushes deeper into health tools like ChatGPT Health. An OpenAI spokesman said the chatbot isn’t intended for diagnosis or treatment, but that the company takes health-related safety seriously. As AI increasingly stands in for medical advice, especially for people who can’t easily see a doctor, the case raises real questions about who’s liable when that advice goes wrong.

I run a healthcare technology company, and I did not come into this with a formal background in AI. What I have are views shaped by building and testing these systems inside a live business, and those views are evolving fast.

Some leaders I know are all in. They are testing tools, prompting systems, learning what works and what does not. I am one of them. We are also providing ongoing, individualized training to make sure every leader on our team has the support to do the same. We are not asking people to figure it out on their own. We are asking them to engage, and we are giving them what they need to succeed.

Others are waiting. They want the technology to feel more polished, more proven, safer. That instinct creates a false sense of control. You do not need a perfect system to get value from AI. The advantage is built by working through imperfect ones. That is how you learn where they break and how to make them better.

The gap you cannot see until it is too late

There is a real difference between understanding what AI can do in theory and knowing how to apply it inside your organization. That difference is not closed by reading about it or watching a demo. It is built through experience. It comes from prompting a system, iterating on the results, course-correcting and refining your inputs over time.

That last part matters more than most people realize. You are not refining the outputs. You are refining your prompts and your inputs. The outputs are what happened. What you are actually developing is the ability to translate how your organization works into instructions a system can act on. That skill does not exist without practice, and it cannot be built from the outside.

While one group is avoiding early mistakes, another is building internal knowledge. And the gap compounds. By the time the technology feels stable to those who waited, the leaders who engaged early are no longer learning the basics. They are optimizing, scaling and embedding these systems into how their organizations actually operate.

What educating AI actually looks like

Most people understand large language models in the abstract. AI goes out to the world, processes an enormous volume of information and generates outputs. What is less understood is the work of educating that model on your specific business. That is where the real leverage lives, and it requires intentional effort.

In practice, it starts with loading the system with everything your organization knows as it exists today. That means your policies and procedures, your legal documents, your existing workflows, your financials, your sales activity data, your onboarding process, your customer history. Then you layer in user experience. In our business, that sounds like this: What does a case manager actually do today? What does an intake specialist handle? What does an account resolution specialist deal with? You are describing the business as it is, not as you wish it were.

Once that foundation is in place, you prompt toward outcomes. Not toward how you think those outcomes should be achieved — toward the outcomes themselves. Show me where our time-to-funding dropped from 14 days to two. Show me what our customers said they wanted and where we are falling short. Show me the activity our sales team is running versus what the close rate actually requires. Review the materials, identify the gaps and suggest the improvements. All of it aimed at more revenue, better margins and stronger customer satisfaction.

This is not the same as workflow redesign. Workflow changes are a much later output. What you are doing in the early stage is education and prompting for iterative change. Think of it as a second set of eyes on the business, one that can analyze across more variables than any individual could and surface opportunities you might not have identified on your own.

Before you implement anything the system recommends, you review it. You iterate. You train around it. That process is how trust gets built, and it requires genuine engagement from leadership.

What the shift from doing to prompting actually requires

The organizations getting the most from AI are not just adopting tools. They are rethinking how work flows through the business. This shift is less about technology and more about clarity. If your workflows are unclear, if ownership is vague, if success is not well defined, the system will not expose those problems. It simply will not be able to answer well. Garbage in, garbage out is not a cliché. It is an accurate description of what happens when a system is educated poorly.

What used to be execution is now direction. What used to be programming is now prompting. The leaders getting the most value understand their product, their customer and their workflows deeply enough to educate a system on all of them. Then they prompt toward their whiteboard goals without telling the system how to get there. That discipline — staying out of your own way and letting the system suggest the path — is where most leaders struggle at first.

This is also why I believe the real competitive skill here is not technical. I would take a strong operator with deep business knowledge over a technical expert any day. The person who understands what the organization does, how it does it and what it is trying to achieve is better positioned to educate and prompt these systems effectively than someone who can only describe how they work mechanically.

The risk is already here

Concerns about reliability are legitimate. In regulated environments, a flawed output is not always contained. It moves through a workflow, influences decisions, reaches customers or patients and can create legal or compliance exposure that is difficult to unwind. Those risks are real, and they are why early experimentation should happen in lower-stakes environments with clear human review built in.

But waiting does not eliminate that risk. It shifts it. The organizations sitting on the sidelines are accumulating a different kind of exposure: a widening capability gap, an inability to attract talent that expects these tools to be part of how work gets done, and a slower response time when the competitive environment demands it.

In our organization, I am direct about where I stand. AI is not replacing humans. It is replacing humans unwilling to utilize it. That is not a threat. It is a description of what is already happening. We are providing every leader with the training, support and access they need to engage. Those who choose not to will eventually face that reality regardless of where they work.

The companies that are winning are not waiting for a better version. They are building their knowledge base right now, educating their systems on how the business actually works and prompting toward outcomes their competitors are not yet positioned to achieve. That head start does not wait for anyone.

I run a healthcare technology company, and I did not come into this with a formal background in AI. What I have are views shaped by building and testing these systems inside a live business, and those views are evolving fast.

Some leaders I know are all in. They are testing tools, prompting systems, learning what works and what does not. I am one of them. We are also providing ongoing, individualized training to make sure every leader on our team has the support to do the same. We are not asking people to figure it out on their own. We are asking them to engage, and we are giving them what they need to succeed.

Others are waiting. They want the technology to feel more polished, more proven, safer. That instinct creates a false sense of control. You do not need a perfect system to get value from AI. The advantage is built by working through imperfect ones. That is how you learn where they break and how to make them better.

I have spent most of my professional life sitting at the intersection of ideas and capital. Over time, you develop a sense for when something is working and when it is not.

Price is meant to be a signal. It is supposed to communicate information between people who are building something and people who are deciding whether to support it. When price works, it coordinates behavior. It tells creators where to focus and gives investors a way to measure progress over time, but there are moments when price stops discovering value and starts suppressing it. This shift changes what gets built, how long companies are allowed to mature and who gets to participate in growth. When that happens, we still talk about valuation, but what we are really doing is negotiating around fear. 

When valuation becomes compression

Modern finance is extremely good at measuring what already exists. It is far less effective at recognizing what is still forming. If it exists on a balance sheet or inventory, a good financier can estimate its value. When the thing of value is still in development, the waters become much murkier.

I have advised entrepreneurs for decades on raising capital for their businesses — real companies with customers, employees and momentum. Again, I have watched valuation conversations turn into exercises in leverage. Whoever controlled capital dictated the structure, the pace, and ultimately, the price. This outcome is the product of incentives that reward certainty over development and speed over patience.

I saw this dynamic clearly while working alongside the founders of Archipelago ECN, one of the earliest platforms to execute equity trades over the internet. We solved fragmentation in the markets, improved pricing efficiency and increased speed. When trading volume became the dominant driver, entire categories of companies, particularly smaller and earlier-stage public companies, quietly stopped mattering to the system.

The consequences show up quickly. The number of publicly traded companies dropped. The immediate result was a shrunken marketplace with a reduced pipeline of new entrants. 

Those that remained found themselves competing against the giants in the market. The necessity to show growth over everything else led founders to begin optimizing for near-term benchmarks instead of building durable businesses. Capital providers prioritize early extraction over long-term participation to avoid opportunity cost. 

When companies are pushed toward premature exits or forced to remain private far longer than what makes sense, the price is wrong because the system never allowed it to be right.

Equilibrium pricing as alignment

Equilibrium pricing begins with a simple observation: Value does not arrive fully formed. Before there is revenue, there is effort. Before there is volume, there is work. Before there is certainty, there is risk taken by people who believe in an idea enough to build it. Equilibrium pricing respects that process. Capital must be aligned with a company’s stage of development. When it is not, timelines compress and decision-making distorts. 

I have seen this alignment change outcomes instantly. For example, a company I advised struggled to secure a $5 million working capital line while private, despite steady operations and clear growth prospects. Shortly after becoming public, without any meaningful change to the business itself, its bank extended a $20 million credit facility. The difference was transparency, liquidity and price discovery operating in an environment designed to recognize development, not discount it.

Misalignment is often visible in how capital behaves under pressure. Capital that demands certainty before development has occurred, or accelerates timelines unnaturally or prioritizes extraction over progress, signals that alignment has already been lost.

Markets function best when valuation occurs in environments where information, participation and discipline can coexist. 

Too much of today’s valuation happens behind closed doors. Numbers are attached to ideas through private negotiation, but the broader market never sees how those numbers were reached or participates in the growth that follows. 

AI, algorithms and repeating the same mistake faster

Artificial intelligence (AI) now sits at the center of modern financial analysis. It processes information faster than any human ever could. But speed does not equal wisdom. If valuation models are built around short-term outputs, algorithms will optimize relentlessly around those outputs. If markets reward volume over development, AI will accelerate that preference. The result is faster repetition of the same blind spots.

This is where market design becomes inseparable from technology. Algorithms are only as good as the environments in which they operate. Public markets structured for smaller companies generate different data than private negotiations. They introduce transparency, discipline and participation without forcing premature scale. Outside of those environments, algorithms risk making the same mistake perfectly, millions of times over. 

The greatest risk is the systematic failure to recognize opportunity because the tools are pointed in the wrong direction.

Letting price discover value again

Price is one of the most powerful coordination tools ever created. When it functions properly, it allocates resources, rewards contribution and supports growth. 

Equilibrium pricing is about restoring balance. It means aligning incentives, matching capital to stage and designing public infrastructure that values development alongside liquidity. That is how durable value has always been created.

If we want capital markets to support the next generation of transformative companies, we must give price the conditions needed to work. When alignment exists, price starts revealing possibility. 

For leaders, restoring alignment requires deliberate choices:

• Examine how you define risk.
  Ask whether your valuation frameworks allow time, effort and development to register as information.
• Match capital to the stage of growth.
  Capital that aligns with development allows price to emerge.
• Separate speed from insight.
  Faster analysis does not guarantee better valuation. Ensure technology is operating meaningfully.
• Favor environments where price can evolve.
  Valuation works best where transparency, participation and discipline coexist. 
• Design incentives that reward participation, not extraction.
  When incentives prioritize early control over long-term contribution, price becomes distorted. Alignment corrects that.

Markets fail when the systems meant to recognize value are pointed in the wrong direction.

I have spent most of my professional life sitting at the intersection of ideas and capital. Over time, you develop a sense for when something is working and when it is not.

Price is meant to be a signal. It is supposed to communicate information between people who are building something and people who are deciding whether to support it. When price works, it coordinates behavior. It tells creators where to focus and gives investors a way to measure progress over time, but there are moments when price stops discovering value and starts suppressing it. This shift changes what gets built, how long companies are allowed to mature and who gets to participate in growth. When that happens, we still talk about valuation, but what we are really doing is negotiating around fear. 

When valuation becomes compression

Modern finance is extremely good at measuring what already exists. It is far less effective at recognizing what is still forming. If it exists on a balance sheet or inventory, a good financier can estimate its value. When the thing of value is still in development, the waters become much murkier.

Artificial intelligence can write business plans, removing the grunt work from an otherwise laborious process. But that doesn’t mean the plans it creates are good — and investors can spot a generic plan from a mile away. They aren’t interested in funding companies that simply have their ducks in a row. They want to fund conviction. They’re looking for founders who deeply understand their market, numbers and risks.

As a regular advisor to early-stage startups, I see the limitations of automated content daily. And while AI is a powerful tool for structure, it lacks the nuance needed to build trust. In a landscape flooded with AI-generated templates, the competitive advantage lies with those who can refine the output into a human strategy.

AI business plans offer clean documentation and a polished deck. But checking that format box is just the first step. Founders must infuse their plans with passion and expertise — and be specific about how AI helps them achieve their goals.

What investors really look for in a business plan

The venture firm Navigate Ventures argues that investors want to peek below the surface of a business plan. They look for the real problems a startup addresses and whether a growing market exists for that solution. 

Is there a clear, scalable business model and a credible path to profitability? What about the team behind the plan? Successful founders must demonstrate deep domain knowledge or have a strategy to recruit commercial expertise.

A strong business plan is only the tip of the iceberg. Investors know a document does not run a company — people do. A winning plan is only effective if it reflects the founder’s deeper passion and expertise. It should serve as a strategic roadmap, turning that knowledge into a sustainable competitive advantage.

Shift your mindset and understand your audience

Anyone can create a plan that looks good. But you need to shift your mindset if you want to court investor cash. Think of your plan like your resume in an interview. You can put anything on there you want — but if you can’t back it up — you won’t get the job.

Spotting the weakness in AI business plans

AI-generated business plans often sound good on paper (or in a chat window). In reality, though, they’re often full of fluff or, in some cases, worse. 

Intuition Labs points out that LLMs (large language models) often hallucinate because they aren’t trying to speak the truth. They are trying to predict the next token. AI doesn’t just lack research depth. It follows a method that involves literally guessing the next word in a sentence based on pattern recognition.

This leads to blatantly incorrect or difficult-to-back-up statements. That’s fine for a social media post. But if it’s in your business plan and gets in front of an investor, it’s a disaster.

Gut check how you’re using AI in your business planning

Along with a lack of passion and unique conviction, AI-generated business plans can set you up for major issues. It’s a great tool to frame out what you want your plan to say. But before you send your business plan up the ladder, make sure you review it, back it up with facts and edit it.

Using AI beyond iteration

If you’re nervous about using artificial intelligence for a business plan, don’t throw the baby out with the bathwater. You can still use AI, but go beyond good prompts and copy-pasting. Flesh out your thoughts and add original ideas throughout your plan. Run it through a detector like Undetectable AI, too, to make sure it sounds human.

It’s also a good idea to treat AI use within your business with a similar “human touch.” Don’t just say you’ll use generic AI tools, templates or consultants to speed things up. That can be unsettling when security and bloated tech stacks are common concerns, especially in a lean startup phase.

Instead, be specific about how AI factors into your launch. Look for ways to show unique and innovative uses for the technology that go past the planning phase. For instance, your pitch might involve using AI to remain lean and efficient. In that case, identify a tool like LivePlan that helps you stay on track as you go. 

Platforms like this are just starting to emerge. They use AI-powered business planning and financial forecasting grounded in real market data, verified industry benchmarks and a fully interconnected financial model. This lets founders confidently validate every assumption, number and strategy, not just at the start, but throughout the life of the business. 

Start building AI into your full business plan

Signaling the use of these kinds of tools shows you’re not just using AI for flash. You’re building systems that depend on an AI-backed iterative methodology. Look for ways to call out specific tools and strategies that allow you to document, validate and refine as you go. This shows investors you can make informed decisions with clarity as you execute your business plan over time. 

Building investor-approved, AI-backed business plans

AI is rewriting the business planning game. It helps startups launch and assists in drafting their business plans. But don’t let the overuse of AI erode investor trust. 

Use AI as a tool, but refine everything it creates. Add your own passion and conviction. Then call out your specific AI use throughout the plan, finding tools that will support your strategy as you scale. If you bridge the gap between automated efficiency and human expertise, expect investors to bite.

Artificial intelligence can write business plans, removing the grunt work from an otherwise laborious process. But that doesn’t mean the plans it creates are good — and investors can spot a generic plan from a mile away. They aren’t interested in funding companies that simply have their ducks in a row. They want to fund conviction. They’re looking for founders who deeply understand their market, numbers and risks.

As a regular advisor to early-stage startups, I see the limitations of automated content daily. And while AI is a powerful tool for structure, it lacks the nuance needed to build trust. In a landscape flooded with AI-generated templates, the competitive advantage lies with those who can refine the output into a human strategy.

AI business plans offer clean documentation and a polished deck. But checking that format box is just the first step. Founders must infuse their plans with passion and expertise — and be specific about how AI helps them achieve their goals.

Let’s face it. There’s nothing fun or entertaining about a Financial Disclosure Document (FDD), which your prospective franchisor is legally required to provide, so you will have full transparency into the deal you’re considering. It’s a contract, with page after page of dry, densely composed legal language for your attorney to wade through and explain.  

Like all contracts, the FDD is a roadmap to the kind of business relationship you will have with your franchisor. Different areas are important to different people, but there are some critical concerns to look for with your attorney. They can identify potential red flags and explain the pros and cons, but it’s up to you to ask the franchisor to clarify any provisions or questions until you’re satisfied with the answers. 

The agreement length

The length of the agreement can tell you whether you’ll have a stable, predictable relationship or may have to deal with unexpected, unwanted changes. I lean towards a longer franchise agreement that’s assignable down the road, rather than a five- or ten-year agreement. Five years go very quickly; just as you’re getting your footing, it’s time for a new agreement with any or every item changed, including a higher royalty fee. 

A longer agreement is better for both parties. It protects the franchisee’s investment and makes the franchisor more stable. At United Franchise Group, our brands have agreements that are 25 or even 35 years; I’m glad we’re not constantly renewing and renegotiating. However, make sure you’re not locked into a decades-long agreement without being able to transfer or sell the business if you wish. 

Brand rules

The agreement should spell out exactly what products are offered and how much freedom you have to change them. A successful brand is going to give you very little freedom, which you should know long before you even get to the FDD stage. You’d be surprised at how many people have tried to “tweak” things that go completely against their franchisor’s brand. 

The brand, not the franchisee, determines things like the products you sell. If you buy into a burger chain, you’ll be selling hamburgers, not hot dogs. And if you try to change the main menu, you’re going to have a problem. Your franchisor is selling brand awareness and may have locations all over the world. Customers want and expect the same customer experience at every location. 

The same goes for things like service hours, employee uniforms and store design. A 24-hour coffee brand won’t be happy if you decide to close on Sundays, change the store’s colors, or otherwise deviate from the brand profile. 

Look at it this way: You’re joining a club. This club says, here’s what we do and here are our rules. Your choice is whether you want to join that club or not. If you want to change it, what’s the point of joining it? 

Now, that doesn’t mean a franchisee can’t make suggestions that align with the brand. We get our best ideas from our franchise owners. Talk to your franchisor about what procedures are in place for accepting ideas from franchisees. If having input into the customer experience is important to you, be sure the agreement makes room for that. 

Relationships matters

Beyond the legal and financial issues spelled out in the FDD, you are entering a business that’s all about relationships. The FDD goes into a filing cabinet, and we never take it out. In fact, we pray we will never have to use it, which would mean a franchisee relationship has deteriorated so badly we have to resort to legal actions. 

To avoid that, we build on our relationships and work with each other personally and help each other grow. If you provide ongoing training and support, maintain honest communication and stay abreast of how each franchisee is operating, you’re a lot less likely to need to pull the document out of the drawer. 

Like any other brand, we have occasionally had a store owner depart from policies clearly spelled out by the FDD. But I don’t think we’ve ever handled it by saying, “Well, look here. According to page three, paragraph four, you’re supposed to do this or that.” Instead, we might say, “Here’s how many of our best store owners do this. We have a proven way of doing things, but you’re not following the program. Is there a reason? What’s stopping you?” 

We do a lot of things that go beyond the scope of the franchise agreement while making sure everyone adheres to the formal contract. The FDD is just one of many tools that both sides use to assess each other. Talking to other franchisees is also essential for the would-be franchisee.  

At the end of the day, the FDD is an irreplaceable part of the franchise process. Understanding it (with an attorney’s guidance) can help you learn whether you and the brand are a good fit.

Let’s face it. There’s nothing fun or entertaining about a Financial Disclosure Document (FDD), which your prospective franchisor is legally required to provide, so you will have full transparency into the deal you’re considering. It’s a contract, with page after page of dry, densely composed legal language for your attorney to wade through and explain.  

Like all contracts, the FDD is a roadmap to the kind of business relationship you will have with your franchisor. Different areas are important to different people, but there are some critical concerns to look for with your attorney. They can identify potential red flags and explain the pros and cons, but it’s up to you to ask the franchisor to clarify any provisions or questions until you’re satisfied with the answers. 

The agreement length

The length of the agreement can tell you whether you’ll have a stable, predictable relationship or may have to deal with unexpected, unwanted changes. I lean towards a longer franchise agreement that’s assignable down the road, rather than a five- or ten-year agreement. Five years go very quickly; just as you’re getting your footing, it’s time for a new agreement with any or every item changed, including a higher royalty fee. 

When I first stepped into leadership, I believed something that many ambitious professionals believe: Leadership meant having all the answers.

I thought my responsibility as a leader was to be the person everyone turned to for solutions. If a problem surfaced, I needed to solve it. If uncertainty emerged, I needed to eliminate it. If my team had questions, I was expected to provide immediate direction.

At the time, that seemed logical.

After all, many people are promoted into leadership because they’ve demonstrated expertise. They know the product. They understand the industry. They consistently deliver results. The natural assumption is that the more senior you become, the more answers you’re supposed to have.

What I’ve learned over the years is that leadership is not about having all the answers. In fact, the leaders who believe they must always have the answers often become the biggest obstacle to their organization’s growth.

The most effective leaders I’ve worked with, advised and learned from share a different mindset. They understand that leadership isn’t about being the smartest person in the room. It’s about creating an environment where the smartest ideas can emerge from everyone in the room.

That realization fundamentally changed how I lead.

The trap of expertise

One of the most common leadership traps is confusing expertise with leadership.

Many executives earn their positions because they excelled in a specific function. The top salesperson becomes the sales leader. The strongest engineer becomes the technology executive. The best operator becomes the division president.

The skills that helped them succeed as individual contributors often revolve around personal knowledge and execution.

Leadership requires a different set of skills.

When leaders continue to rely exclusively on their own expertise, they unintentionally create dependency. Team members stop bringing ideas. Innovation slows. Decisions become bottlenecked around one person.

I’ve seen organizations where every significant decision had to pass through the CEO because the leader believed no one else could make the right call. The result wasn’t better decisions. The result was slower growth, frustrated employees and missed opportunities.

The irony is that many leaders create these bottlenecks with good intentions. They want to help. They want to protect the company. They want to ensure success. But leadership isn’t about being indispensable. It’s about building organizations that can thrive beyond your individual contribution.

The power of asking better questions

One of the most transformative leadership lessons I’ve learned is that questions often create more value than answers.

Early in my career, I entered meetings looking for opportunities to contribute solutions. Today, I enter meetings looking for opportunities to ask better questions.

Questions uncover assumptions. Questions create dialogue. Questions encourage critical thinking. Questions invite participation. Most importantly, questions help people discover answers for themselves.

When leaders constantly provide answers, employees become conditioned to wait for direction. When leaders ask thoughtful questions, employees become empowered to think independently.

That shift creates something every organization needs: ownership. People are far more committed to solutions they help create than solutions they are simply told to execute.

The strongest leaders don’t dominate conversations. They guide conversations. They create space for others to contribute. They understand that leadership is less about broadcasting expertise and more about facilitating insight.

Why humility has become a leadership superpower

The pace of change in today’s business environment makes it impossible for any one person to know everything.

Artificial intelligence is reshaping industries. New technologies emerge constantly. Consumer behavior evolves rapidly. Market dynamics shift overnight. The idea that a leader can possess all the necessary knowledge to navigate every challenge is no longer realistic.

That’s why humility has become one of the most important leadership traits. Humility doesn’t mean lacking confidence. It means recognizing that no matter how much experience you’ve accumulated, there is always more to learn.

Some of the most successful executives I’ve met are also the most curious. They ask questions. They seek feedback. They challenge their own assumptions. They remain students even after becoming leaders.

Unfortunately, some leaders view admitting uncertainty as a sign of weakness. In reality, the opposite is true. Teams trust leaders who are authentic. People respect leaders who are willing to say, “I don’t know, but let’s figure it out together.”

Authenticity builds credibility. Humility builds trust. Trust builds strong organizations.

Why great leaders build great teams

One of the biggest mindset shifts in my leadership journey occurred when I stopped focusing on being the smartest person in the room and started focusing on assembling the smartest room possible.

No great company is built by one person. No major innovation is created by one perspective. No lasting organization succeeds because of a single leader.

The best leaders understand that their greatest competitive advantage isn’t their personal knowledge — it’s the collective intelligence of their team. This is why hiring matters. This is why culture matters. This is why diversity of thought matters.

A leader surrounded by people who think exactly the same way gains very little value from those relationships. Progress comes from different perspectives. It comes from constructive disagreement. It comes from people who challenge assumptions and offer insights that leadership may not have considered.

When leaders surround themselves with talented people and genuinely empower them, remarkable things happen. The organization becomes stronger. Decisions improve. Innovation accelerates. Growth becomes sustainable.

The importance of advisors and mentors

This lesson extends beyond internal teams.

Throughout my career, I’ve become increasingly convinced that no leader should navigate growth alone. This belief is one of the reasons I’m so passionate about boards, advisors and mentorship.

The most successful executives understand the value of external perspective. They actively seek advisors who bring different experiences and expertise. They recognize that wisdom often comes from people who have already traveled the path they’re currently navigating.

An effective advisor doesn’t provide all the answers. They help leaders ask better questions. They challenge blind spots. They share lessons learned through experience. They provide perspective during moments of uncertainty.

In many cases, the most valuable advice isn’t a solution. It’s a different way of looking at the problem.

Leadership is about multiplying others

Perhaps the most important lesson I’ve learned is that leadership is not about personal achievement. It’s about multiplying the potential of others.

The leaders who leave the greatest legacy are not remembered because they had all the answers. They’re remembered because they developed people, built teams, created opportunities, inspired growth and helped others become leaders themselves.

Leadership is not measured by how many people depend on you. Leadership is measured by how many people become stronger because of you.

When I look back on my own journey, I realize I spent too much time early on believing leadership required certainty. Today, I understand that leadership requires curiosity. I believed leadership was about directing people. Today, I believe it’s about empowering people.

I thought leadership meant being the person with all the answers. I was wrong.

The best leaders don’t have all the answers. They create environments where the best answers can be discovered, challenged, refined and implemented together.

And in a world that is changing faster than ever before, that may be the most important leadership lesson of all.

When I first stepped into leadership, I believed something that many ambitious professionals believe: Leadership meant having all the answers.

I thought my responsibility as a leader was to be the person everyone turned to for solutions. If a problem surfaced, I needed to solve it. If uncertainty emerged, I needed to eliminate it. If my team had questions, I was expected to provide immediate direction.

At the time, that seemed logical.

The two-word term “customer experience” contains a whole world in itself, defining the success of the company. Regardless of the scale of the business, it’s the top priority of the customer success department to collect, optimize and refine the user’s journey. But with the advancement of tech, traditional strategies are now being replaced with the latest AI-enabled frameworks that are much more effective and ensure better ROI.

Here’s how you can transform your customers’ journey to its peak and set autonomous development as a default framework.

Before AI

Once, the customers’ research department used to develop the heat map, which was shocking in its time. Marketers took it as a futuristic tool that keenly observes and visualizes the user’s behavior on a platform. Though the concept was borrowed from conventional thermal energy sensor gadgets, some advancements, as per the digital demands, crafted a fully functional software.

Sports, tech, retail and even every industry reap the perks of the heat mapping algorithm that provides companies with real-time data of a visitor’s scrolling habits. Yet, that’s the thing of the past, as now we have far more advanced observational capabilities that are empowered by AI.

Each click, scroll and submission tells us more intelligently than the brand ever imagined. Previously, the input we gathered in the raw form was now more organized and even mature enough to portray the whole picture of what’s going on.

The journey of raw to real

Each bit is meaningful in our era, where data is becoming the new standard of supremacy. The real challenge begins with the utilization of the scattered information that doesn’t contribute to the productive growth of the systems. For every governing body that is questionable to the improvement and enhancement of the company, they have to tackle the challenges critically and act proactively before their competitors do.

Here, some organizations develop their own ecosystems to level up the customer experience on a scale. Unfortunately, for some, it isn’t feasible for entities to afford the in-house upgrades due to the nature of the business and resource availability. That’s where base-level systems allow the organizations to deploy their systems in an integrated manner and tune them as per the business’s tailored demands.

AI-backed frameworks to enhance the user’s journey

Going back to the basics, the core mission of the brands is to offer a best-in-class experience that reflects their value-driven approach for customers. Below are the frameworks that can be implemented in an altered manner to reap their perks.

Predictive analysis

Sales aren’t the end objective of the brands, but influencing, shaping customers’ mindset and retaining them is. Theoretically, the process may sound simple, but in practice, it is resource-consuming and demands back-and-forth alterations.

An organization hires data experts who forecast the business growth trend based on the input of the customer’s history. No doubt the insights are valuable for the companies, but unless they’re used to train the self-empowered algorithms, the real challenge stays there until it’s fixed.

Thankfully, we now have the opportunity to enable our existing systems with the artificial intelligence frameworks and tools. That tweaked software’s capable of processing and squeezing the raw input into meaningful results that can enrich the end customer experiences.

Reduce the friction

Transitioning isn’t an easy process that happens overnight, especially in complex structures. It takes time and resources to seamlessly integrate the new developments into an existing ecosystem. Sometimes organizations unintentionally get trapped in unforeseen circumstances in the middle of the upgrade phases.

Meanwhile, they’re aware of the potential risks and rewards, but the disturbance gets triggered when the unexpected error gets contagious. Strategically controllable, the situation cools down when the “Beta” versions are first run among cross-platform devices. Doing so exposes the vulnerability and critical errors of the development and allows the developers to fix them on a priority basis.

Hyper-personalization

Customers don’t appreciate it if the brand targets them and has no prior understanding of their preferences. Leaving an unexpected impression, the user experience can make or break the brand’s perception. That’s why catering to the stakeholders with a tailored approach is now more than a necessity in the era where every click counts.

For instance, a practical approach to offer customers a unique experience is by offering an all-in-one platform that is intelligent enough to adapt as per the scenario. Here, ML (Machine Learning) and LLMs (Large Language Models) play a pivotal role in laying the foundation of an exceptional user experience.

Measure the results

The change will be unseen unless it’s measured as per the standards. Sometimes, the benchmark will be the peer’s growth, while it can also be the organization’s own if they’re the trendsetters. But the essence remains the same as the results are gauged, reflecting the growth in all aspects from leads to post-sale activities and beyond.

For instance, if your organization is running multiple experiments at once as an A/B approach. Those should be categorized to reduce the hassle of finding what works best and what doesn’t. That’s the ideal pathway to gain impact measurement insights and strategically plan the rest of the actions.

The never-ending cycle

For growth, the sky isn’t the limit, but the growth itself is if the establishments put AI to work the right way. Regardless of how much perfection the organization achieves in refining its customers’ experience. There’s always some room left to improve unless there’s a paradigm shift. For the entities who assume they’re at the top of the cliff, for others, it’s just a new normal, and it’s just a platform for them to amplify their growth trajectory.

The two-word term “customer experience” contains a whole world in itself, defining the success of the company. Regardless of the scale of the business, it’s the top priority of the customer success department to collect, optimize and refine the user’s journey. But with the advancement of tech, traditional strategies are now being replaced with the latest AI-enabled frameworks that are much more effective and ensure better ROI.

Here’s how you can transform your customers’ journey to its peak and set autonomous development as a default framework.

Before AI

Once, the customers’ research department used to develop the heat map, which was shocking in its time. Marketers took it as a futuristic tool that keenly observes and visualizes the user’s behavior on a platform. Though the concept was borrowed from conventional thermal energy sensor gadgets, some advancements, as per the digital demands, crafted a fully functional software.

Every week, you enter the same loop. You have to pull the stats, sample the calls, file the reports. One week goes by. Nothing happens. You didn’t miss a goal. You missed a phase.

As a result, your business ultimately doesn’t grow.

It’s not because you have a discipline, motivation or procrastination problem. You’ve got a flow problem, and you’ve never been taught how to solve it.

As a business owner striving for growth you look for two things:

1. The activities that truly move the needle in your business.
2. A productive state where you execute at a high degree.

However, you can’t grow a business with just the activities. You need the state. The most productive state a human being can experience is flow, that state of optimal consciousness in which you feel and perform at your best, where you’re fully immersed in a task and time seems to distort.

However, people rarely reach this state, because they’re not aware of the flow cycle, and the initial phase that most get stuck in (and how to overcome it).

Why working on growing your business feels like a snake in the room

If you’re a practice owner within the medical space, for example, you’re probably a great dentist or a skilled surgeon. You’re good at what you built this business around. But despite your professional skills, your business stalls because you don’t do well with the development side.

Business development has abandonment and rejection woven into it. For many practice owners, the uncomfortable activities that have nothing to do with the actual deliverables can feel like facing the snake in the room.

That is why you recoil.

Specific business development tasks have higher resistance than others because of the conditioned angle or previous experiences. Maybe your family fought over money so nowadays you hate quarterly budget planning and refuse to look at spreadsheets. When you see this task, your brain sees a threat. What it should be seeing is an opportunity.

A destination called flow with a gate in front of it

In his book Flow: The Psychology of Optimal Experience, Mihaly Csikszentmihalyi explains that true flow begins when the challenging task matches your high skill level.

But when it comes to business development activities, the challenge is there, but your confidence leaves the room. That’s the reason you can’t reach the flow.

People who don’t know that the flow is a cycle, not a single event, never achieve it.

And most business owners never go past stage one.

Stage one is called the struggle, and it’s supposed to feel exactly like this

The flow starts with the struggle. It starts with the queasy stomach feeling when you have to sit down with the numbers, and a sudden urge to pick up your phone or eat something arises. You will do anything that relieves you of the discomfort of doing something you don’t feel like doing right now.

The feeling and the discomfort are confirmation you’ve started the cycle, not a stop sign to quit and move to something else. For business development, how you feel is completely irrelevant.

The chemicals confirm it: During the struggle phase, stress neurotransmitters are released, cortisol rises and serotonin drops. This is just a common biochemical reaction, not a signal to stop. So, next time it feels bad, the correct response is: Brilliant. This is exactly how this stage is supposed to feel.

The reset nobody talks about

You can go through the struggle phase and embrace the flow. There is no shortcut through it, but there is a shortcut to the flow: Don’t pick up your phone. Don’t eat a donut. Don’t do anything else except that activity for 23 minutes.

You’ve done this a hundred times without realizing the clock reset each time. And you keep telling yourself you just aren’t cut out for it — false.

There is something you’ve never considered: You’ve never liked certain activities because you have never sat in the discomfort of the struggle phase for 23 minutes without distractions.

The 23-minute rule: What marathon runners understand that sprinters don’t

Business growth doesn’t happen in 100 meters. It begins at the 10th mile of the 26-mile marathon. Sprinters exhaust themselves. A marathon runner keeps going long after it feels hard.

If you don’t feel like doing it, run it past 23 minutes to get in the flow. Everything will align from there. This applies to everything from difficult conversations to numbers reviews and performance discussions.

In practical terms, apply time-boxing. Schedule your day in 30-minute blocks for each activity. The activities remain the same as yesterday, but you are the one who changes.

Each time you sit through those 23 minutes, something shifts. And according to Dr. Andrew Huberman, it matters because the brain releases its reward signal, unlike anything else, after sustained effort through discomfort.

How to use the 23-minute rule to grow your business

Don’t let your emotions run you. Ignore them. That is what’s pulling you out before you enter the flow.

Unsuccessful people are driven by their emotions; the 23-minute rule is the first step to stop being one of them.

You want to grow. The activities aren’t hard. Your ability to sit there and build an intimate relationship with them is what you need to work on. Now you know where to start.

Every week, you enter the same loop. You have to pull the stats, sample the calls, file the reports. One week goes by. Nothing happens. You didn’t miss a goal. You missed a phase.

As a result, your business ultimately doesn’t grow.

It’s not because you have a discipline, motivation or procrastination problem. You’ve got a flow problem, and you’ve never been taught how to solve it.