Work expands to fill time, and organizations expand to fill available work. People instinctively want to hire direct reports to increase their status, creating a supply of labor that then invents low-value tasks to justify its existence, leading to bloat and inefficiency.

As companies scale, the supply of obvious, valuable work dwindles. To stay busy, employees engage in "hyper-realistic work-like activities"—tasks that mimic real work (e.g., meetings to review decks for other meetings) but generate no value. It's a leader's job to create a sufficient supply of *known valuable work*.

When a team presents a timeline that feels instinctively too long, trust that gut feeling. It likely signals an over-engineered solution. Complex systems never become simple; they only breed more complexity, causing timelines to expand endlessly. It's better to reset the team or the approach early on.

Don't hire more reps until your current team hits its productivity target (e.g., generating 3x their OTE). Scaling headcount before proving the unit economics of your sales motion is a recipe for inefficient growth, missed forecasts, and a bloated cost structure.

Instead of over-analyzing and philosophizing about process improvements, simply force the team to increase its cadence and ship faster. This discomfort forces quicker, more natural problem-solving, causing many underlying inefficiencies to self-correct without needing a formal change initiative.

Saying yes to numerous individual client features creates a 'complexity tax'. This hidden cost manifests as a bloated codebase, increased bugs, and high maintenance overhead, consuming engineering capacity and crippling the ability to innovate on the core product.

At scale, the biggest threat isn't a lack of opportunity but mental overload. The key is to treat your focus as a finite resource and actively protect it. This means becoming comfortable saying "I'm done for today" and disappointing people, realizing that protecting your mind is more strategic than satisfying every request.

When offered a choice between an extra hire or expensive AI coding subscriptions for their team, line managers almost always choose the headcount for team growth. VPs, focused on broader business metrics, often prefer the AI tool for its potential productivity gains across multiple teams.

Biologist William Muir's 'super chicken' experiment revealed that groups of top individual performers can end up sabotaging one another, leading to worse outcomes than more cooperative, average teams. In business, this 'too much talent problem' manifests as ego clashes and a breakdown in collaboration, undermining collective success.