Leadership isn't a title you inherit. It's a muscle you build through deliberate practice.

In this very special episode, Jon opens the doors to Sagan's Emerging Leaders meeting, a live session with Sagan team members that pulls back the curtain on how real leadership development happens in real time!

Struggling with feedback doesn't mean you're bad at leadership. It just means you haven't practiced enough yet.

Leadership is kind of like going to the gym. Nobody walks in on day one and expects to lift the heaviest weight. Yet too many emerging leaders treat their first fumbled feedback conversation or difficult personnel decision as evidence they don't have what it takes.

The team discusses the value of this recurring commitment. It's like taking classes on anything challenging. You dread seeing the next session on your calendar, but by the end, you're grateful you showed up. It’s important to normalize the discomfort of leading while emphasizing feedback flows in all directions: up, down, and across.

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As a business operator in 2026, one of your top responsibilities is to ensure your team knows exactly when AI stops and human judgment starts.

Jon and Peter tackle the confusing middle ground between "use AI for everything" and "never let AI touch our work”.

Drawing from Peter's engineering background, they introduce the concept of "stamping the drawings". That’s a professional engineering practice where junior staff produces work, but a licensed engineer must review and approve anything load-bearing.

Applying that to business, certain outputs demand human oversight. For other outputs, it may not be necessary.

Jon’s hard line is, if you're manually transcribing meeting notes instead of using Claude, you're fired. That said, if you're sending AI-generated responses to your biggest customer without review, you're also fired.

They discuss why employees are confused when leadership says "use more AI" but punishes them for using it in high-stakes contexts.

They argue that, rather than simply enforcing a new set of rules, companies should create frameworks that identify which tasks are procedural (automate freely) versus which are strategic, customer-facing, or load-bearing (human review required).

Your competitive advantage isn't some unique AI strategy. It's knowing which decisions only human beings should be making.

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Sales doesn't happen by magic. It happens through deliberately architected workflows.

Jon sits down with John Seiffer, author of Output Thinking, who walks through his framework for sales process engineering for small businesses. He breaks down what most companies treat as a black box into discrete, measurable steps: research, marketing, selling conversations, proposals, fulfillment, and account management.

Well-designed workflows are not an emergent phenomenon.

Just as Henry Ford wouldn't have succeeded by putting talented mechanics in a room and saying "go make cars," modern companies can't rely on generalist salespeople to handle everything from cold outreach to proposal writing to customer success.

This specialization enables technical sophistication that generalists can't match.

In some industries, however, the marketing function (getting the decision-maker on the phone) is more valuable than the sales function (running the actual call). A franchise sale is harder to schedule than to close. This challenges traditional compensation structures where salespeople are the rainmakers.

Finally, Jon and John touch on modern signal-based prospecting (ServiceTitan users, specific LinkedIn group members, mom Facebook group commenters) and how AI enables systematic hunting for situational signals that matter more than demographics.

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What is the actual job of a CEO?

Rather than treating leadership as a vague mix of hustle and charisma, Peter and Jon compare two competing frameworks that both come from highly successful operators. Peter argues the CEO’s job is to set the vision, build the team, and make sure the company never runs out of cash. Jon reframes the role as raising standards, increasing focus, and increasing pace.

Truth is, there’s no “better” framework. It’s more so about uncovering the deeper principles beneath both models and adapting it to your organization’s current needs.

The alternative framework is more operational and cultural.

Raising standards means teaching teams what excellence looks like, not just demanding it. Increasing pace is less about arbitrary deadlines and more about shortening the OODA loop (observe, orient, decide, act) so organizations can iterate faster on marketing channels, hiring strategies, or product features.

The frameworks aren't contradictory. They're complementary.

One addresses what to build; the other addresses how to build it. Together, they reveal that leadership isn't about answering emails or attending meetings. It's about the handful of things that won't happen without deliberate intervention: maintaining focus, enforcing standards, controlling speed, setting direction, building teams, and managing resources.

Everything else is noise.

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Have you ever bought new tech, spent months implementing it, and seen zero throughput improvement? You’re not alone. It's an age-old problem plaguing small businesses.

Whether it's switching property management software or adopting ChatGPT company-wide, the result is the same. Lots of disruption yet no meaningful change.

The culprit isn't the technology itself. It's how we deploy it. In the audiobook 'Beyond the goal', Dr. Eliyahu Goldratt identified four critical steps for technology rollout in the Theory of Constraints work, and most businesses overlook at least a couple of them.

Step one is easy: identify what the technology can do (it's on the vendor's website). Step two is to ask, “Does this technology diminish your actual constraint?”.

Step three is to identify old accommodations. These are the rules your team created to cope with historic limitations.

Step four is to identify new rules.

Technology becomes a burden if you keep operating under old policies. Companies spend millions on ERPs without updating the implicit rules designed around previous limitations, then wonder why productivity stays flat.

Jon extends this to the AI hype cycle, in which venture-backed firms are buying pool cleaning companies claiming AI will revolutionize operations. But until someone explains how AI solves managing $21/hour workers in wealthy homeowners' houses, it's just expensive posturing.

The constraint isn't following up on leads but managing low-cost local labor. Writing emails faster doesn't address that!

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Jon sits down with Brian Wilson, Head of Knowledge and Automation for Sagan.

They cover the critical importance of developing middle managers, why founders can't afford to choose their strengths, the unique advantages of founder-led sales, and the underutilized sweet spot of building internal software tools that attack your company's constraint while avoiding the overhead of external SaaS products.

Your job as a leader isn't to do the work but to have the work done through you by your team. This philosophical shift separates founders who scale from founders who stay trapped in tactical execution.

Regarding internal software development, Jon argues there's a sweet spot between individual AI tools (Brian sorting his email better) and full SaaS products (which require customer acquisition, uptime guarantees, OAuth integration). Internal tools capture more impact than individual productivity hacks without the overhead of external customers.

This is why companies spend millions on ERPs without harvesting gains. They never updated the implicit policies designed around the old limitation.

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The best operators in M&A make hundreds of millions because they "model deals elegantly," but billionaires "can barely do the math. They just only do deals where they can't lose."

At least that’s what Jon and Peter believe. It's Warren Buffett's philosophy in action; that price is your due diligence.

Metrics should be entered manually, not automated. The psychological weight of pulling numbers and inputting them weekly creates accountability that automated dashboards never achieve. It's the difference between ownership and passive observation.

They distinguish between dashboards (lagging indicators like revenue) and scorecards (controllable activities like reviews requested). This separation, learned from their EOS coach Chris Kaplan, prevents teams from chasing metrics they can't influence week-to-week.

Next we’re asking, “Should you judge people on outcomes or process?” Saban (echoing Bill Walsh) says focus on the controllables. That is, the score takes care of itself. But Jon admits he's "constantly ripped in half" between mandating process and demanding results. Peter suggests it depends on performance level: high performers get freedom, struggling performers get prescription.

They tackle paired metrics as protection against perverse incentives, using India's snake-bounty program as a cautionary tale. When the government paid for dead snakes, people started breeding them. Similarly, optimizing turn time without pairing it with customer satisfaction leads to cutting corners.

Finally, Jon and Peter riff on Saul Alinsky's "Rules for Radicals", particularly when he says that, when pressure increases, people try to diffuse responsibility.

As a manager, your job is keeping accountability focused: "You are responsible for everything that does and doesn't happen to make this number improve."

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Peter admits he's stuck in patterns. He’s not quite burnt out, but feeling the weight of deeply grooved neural pathways at 40. Jon responds with what he calls his "wacko" idea: ketamine therapy as a tool for breaking mental ruts.

Speaking metaphorically, he says that Ketamine fills in the snow tracks your mind has carved, giving you a chance to create new paths. But only if you do the work afterward, such as therapy, reflection, habit change. Without that follow-through, you slide right back into the same grooves.

This leads to their "barbell strategy" for change: either make tiny, effortless tweaks or commit to massive action. The middle ground never sticks.

It's too much effort to start, but not enough commitment to force follow-through.

Jon and Peter also discuss hard-coded solutions in software. A go-to-market engineer explained why his work couldn't be productized: the last 20% of customization drives 75% of the value. Peter sees this in his own business with Airtable, while Jon wrestles with it at Sagan.

There’s a tension that LeadSimple’s journey illustrates, and it’s that customers want self-service, yet implementation requires expertise.

The result is an awkward middle ground: $7,000 packages, third-party consultants, and confusion about what the product even is.

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The secretary problem is one of mathematics' most elegant solutions to a universal challenge: how do you know when to stop looking and commit?

Peter suggests interviewing 37% of your candidate pool without hiring anyone, then hire the next person who's better than everyone in that first group. It’s a pretty universal tactic, whether we’re talking house hunting, car buying, getting roofing quotes, or even picking a spouse!

There are two critical limitations to this, though. First, you need to know the total number of options, whether that's 100 candidates or 25 houses on the market. When that's unknown, you convert to time-based constraints.

The second limitation: the secretary problem only applies when you lack expertise. When Jon or a real estate agent has seen "5,000 of these," they can make absolute judgments, not just comparative ones.

Peter draws from a current predicament in which a Nicaraguan candidate has been asking for what seemed high compensation. Should he have paid based on her country's cost of living, or on the value she'd bring?

Jon pushes back on the entire concept of salary budgets. He argues everything should be discussed as trade-offs.

Peter admits his biggest mistake wasn't the salary negotiation. It was failing to sell the opportunity itself, assuming the candidate knew who he was and what Crane represented.

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The Theory of Constraints is arguably the most powerful framework for small business operations. Yet it's deeply counterintuitive.

Jon opens by calling this "the single most interesting concept" he's wrestled with in years, one that sits at the heart of everything he does at Sagan. On a more practical level, Peter sees the concept as answering two critical questions every business owner has: "Why am I not achieving X?" and "What should I work on?"

Eliyahu Goldratt's manufacturing classic The Goal might just have the answer: every system has exactly one constraint at any given time. Like a chain's strength determined by its weakest link, your business throughput is determined by your bottleneck.

It’s important to avoid optimizing non-constraint resources. Peter's executive assistant Monica doesn't need to be busy 40 hours per week because if Peter's time is the constraint, Monica's availability is actually a feature, not a bug.

Firefighters sit idle 85% of the time so they can respond in five minutes. F1 pit crews have 20 people working seven seconds per race because speed, not cost, is the constraint.

Jon and Peter get into the five-step process. These are to identify the constraint, exploit it (no lunch breaks for the bottleneck!), subordinate everything else (redistribute weight from Herbie's backpack), elevate through investment only when necessary, and repeat as the constraint moves.

And remember, idle employees facing "idleness aversion" will invent busywork, whether it’s creating SOPs, trackers, and communication cadences that generate noise and clog the constraint's queue.

The solution isn't just accepting idle time but directing it toward infinity tasks that support the actual constraint.

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