Sunday morning, December 15th. Watching someone spend their fourth hour debugging a problem that a five-minute conversation with the right person would solve. They'll probably figure it out eventually. They'll feel proud of their persistence. They'll have learned the hard way. And they'll have wasted three hours and fifty-five minutes.

The Effort Myth

Here's what we're told:

  • Hard work always pays off
  • Persistence beats talent
  • Effort is its own reward
  • Keep grinding and you'll succeed
  • Winners never quit

Here's what actually happens:

  • Most effort is wasted
  • Persistence in the wrong direction compounds failure
  • Effort without learning is expensive procrastination
  • Grinding on the wrong problem makes things worse
  • Winners quit constantly—they just quit the right things

Thesis: We celebrate effort as inherently virtuous, but most effort is actively harmful. The real skill isn't working hard—it's knowing which problems deserve hard work and which deserve a completely different approach. Effort without strategy is just thrashing. The uncomfortable truth: being willing to NOT try hard is often more valuable than grit.

The Three Types of Effort

Not all effort is created equal. Most falls into one of three categories:

1. Productive Effort

What it looks like:

  • Deliberate practice on high-leverage skills
  • Work that compounds over time
  • Effort that builds irreplaceable knowledge
  • Progress toward clear objectives
  • Learning that transfers to other domains

Example: A programmer spending 100 hours learning type systems and functional programming patterns. This knowledge compounds—it makes every future project easier and helps them recognize entire classes of bugs before they happen.

Why it works: The effort creates lasting value. Each hour makes future hours more productive.

2. Neutral Effort

What it looks like:

  • Busy work that doesn't compound
  • Necessary but non-differentiating tasks
  • Maintenance work that preserves value
  • Effort that solves immediate problems but doesn't build capacity

Example: Spending 100 hours implementing a standard CRUD API using familiar tools. The work needs to get done, but it doesn't make you better at anything. Hour 100 is no more valuable than hour 1.

Why it's neutral: You're trading time for money or immediate value, but not building capability. It's not bad—it's just not investment.

3. Destructive Effort

What it looks like:

  • Grinding on problems that shouldn't be solved this way
  • Persistence in obviously wrong directions
  • Effort that reinforces bad habits
  • Hard work that prevents learning better approaches
  • Heroic effort to patch fundamentally broken systems

Example: Spending 100 hours manually testing a web application instead of learning automated testing. Or debugging a performance problem with print statements instead of using a profiler. Or optimizing code in the wrong bottleneck.

Why it's destructive: The effort actively makes things worse. It reinforces inefficient approaches, prevents learning better methods, and wastes time that could build actual capability.

The trap: All three types feel the same while you're doing them. Destructive effort often feels more virtuous because it's harder.

Why We Fall For It

The effort trap persists because:

1. Effort is Visible, Results are Delayed

The pattern:

  • Working long hours is immediately observable
  • Results take time to manifest
  • Effort feels like progress
  • Busyness is culturally rewarded

Result: We optimize for visible effort rather than actual results. "I worked 80 hours this week" gets more respect than "I solved the problem in 2 hours by asking the right person."

The trap: When results don't materialize, we double down on effort instead of questioning the approach.

2. Sunk Cost Makes Effort Feel More Legitimate

The pattern:

  • You invest significant time in an approach
  • Evidence suggests it's not working
  • Changing course feels like wasting the invested time
  • You keep going to "justify" the effort

Example: You spend 40 hours building a feature the hard way. Someone shows you a library that does it in 4 hours. But you're "almost done" with your approach, so you spend another 20 hours finishing instead of switching.

The trap: Past effort makes you more committed to failing strategies. The time is already wasted—continuing doesn't recover it.

3. Learning Feels Lazy

The pattern:

  • Spending time learning feels unproductive
  • Actually doing the work feels virtuous
  • "Just start" is common advice
  • Research is dismissed as overthinking

Example: You could spend 2 hours learning how experts approach a problem, then 10 hours implementing efficiently. Or you could "dive in" and spend 50 hours figuring it out the hard way.

The paradox: Taking time to learn the right approach is faster, but feels slower. Starting immediately is slower, but feels faster.

The trap: We mistake motion for progress and research for procrastination.

The Direction Problem

Here's what matters more than effort: direction.

The Multiplication Effect

Effort is a multiplier on direction:

Value = Direction × Effort

If direction is positive:

  • Effort compounds toward the goal
  • Each hour adds value
  • Hard work accelerates progress

If direction is zero:

  • Effort is wasted motion
  • Each hour maintains position
  • Hard work burns energy for no gain

If direction is negative:

  • Effort makes things worse
  • Each hour moves away from the goal
  • Hard work accelerates failure

The critical insight: If direction is wrong, reducing effort is more valuable than increasing it.

Example:

  • Good direction, moderate effort: Build simple automated tests (Value = 5 × 10 hours = 50)
  • Zero direction, high effort: Manually test everything each time (Value = 0 × 100 hours = 0)
  • Bad direction, high effort: Build an overly complex testing framework nobody will use (Value = -5 × 100 hours = -500)

The Slope vs. Speed Problem

Two ways to increase progress:

  1. Work harder (increase speed)
  2. Work smarter (increase slope)

The math:

  • Working 2x harder gets you there 2x faster
  • Finding a 10x better approach gets you there 10x faster
  • A 10x better approach with 0.5x effort gets you there 5x faster

The trap: We default to increasing effort because slope is harder to change. But effort has linear returns while slope has exponential returns.

The move: Before working harder, ask: "Is there a 10x better way to do this?"

When Effort is The Wrong Answer

Situations where trying harder actively makes things worse:

1. When You're Solving The Wrong Problem

Example: Carefully optimizing code that runs once per day instead of the code that runs 1000 times per second.

What effort does: Makes you deeply knowledgeable about an irrelevant problem.

What to do instead: Stop. Find the actual bottleneck. Apply effort there.

2. When You Lack Critical Information

Example: Debugging for hours without understanding the underlying system architecture.

What effort does: Reinforces guessing and trial-and-error instead of systematic thinking.

What to do instead: Stop. Learn the system. Then debug with understanding.

3. When You're Patching Instead of Fixing

Example: Adding special cases to work around a fundamentally broken design.

What effort does: Makes the system more complex, fragile, and harder to fix properly later.

What to do instead: Stop. Fix the root cause. Even if it takes longer upfront.

4. When The Problem Shouldn't Exist

Example: Building elaborate workflows to compensate for poor tool choices.

What effort does: Institutionalizes the wrong tools and makes switching harder.

What to do instead: Stop. Change tools. Don't build infrastructure around bad foundations.

5. When Someone Has Already Solved It

Example: Implementing a complex algorithm from scratch when a well-tested library exists.

What effort does: Creates buggy, unmaintained code that does exactly what a library does better.

What to do instead: Stop. Use the library. Apply effort to problems nobody has solved.

The Real Skill

The valuable skill isn't working hard. It's knowing when to work hard vs. when to:

1. Stop and Ask

When: You've been working for more than 30 minutes without clear progress.

What to ask:

  • "Am I solving the right problem?"
  • "Who has already solved this?"
  • "What am I learning by doing this the hard way?"
  • "Is there a 10x better approach I'm missing?"

Why it matters: 30 minutes of hard work in the wrong direction costs the same as 30 minutes in the right direction, but compounds in opposite ways.

2. Learn First, Execute Second

When: You're unfamiliar with the domain or problem space.

What to do:

  • Read how experts approach the problem
  • Study existing solutions
  • Understand the landscape before committing
  • Build a mental model before building code

Why it matters: 2 hours learning + 10 hours executing beats 50 hours learning-by-doing.

3. Seek Help

When: You're stuck or grinding without progress.

What to do:

  • Ask someone who knows
  • Find the 5-minute conversation that saves 5 hours
  • Trade status (admitting you don't know) for speed

Why it matters: The fastest way to solve most problems is to talk to someone who's already solved them.

4. Question The Premise

When: The work feels like it shouldn't be this hard.

What to ask:

  • "Why does this problem exist?"
  • "What if we didn't solve it at all?"
  • "Is this necessary or are we just doing it because we always have?"

Why it matters: The best solution to many problems is making them not exist.

5. Quit

When: Evidence suggests you're in the wrong direction.

What to do:

  • Abandon sunk costs
  • Try a different approach
  • Be willing to throw away work

Why it matters: Persistence is only valuable when direction is right. Otherwise it's just expensive stubbornness.

Takeaways

The core insight: Effort is not virtuous. Effort in the right direction is virtuous. Effort in the wrong direction is waste or harm.

What to stop doing:

  • Celebrating effort regardless of results
  • Grinding when evidence suggests you're in the wrong direction
  • Confusing hard work with progress
  • Using sunk costs as reasons to continue
  • Seeing asking for help as weakness

What to start doing:

  • Checking direction before increasing effort
  • Stopping to ask "is there a better way?" every 30 minutes
  • Learning before doing on unfamiliar problems
  • Seeking the 5-minute conversation that saves 5 hours
  • Being willing to throw away work that's going nowhere

Questions to ask before working hard:

  1. Am I solving the right problem?

    • Is this the actual bottleneck?
    • Does solving this matter?
    • What am I assuming that might be wrong?

  2. What's the 10x better approach?

    • How do experts solve this?
    • What tools/libraries/frameworks exist?
    • Am I reinventing wheels?

  3. What will I learn from doing this?

    • If the answer is "nothing new," why am I doing it this way?
    • Is there a learning-focused approach that's also faster?

  4. Who has already solved this?

    • Can I ask them?
    • Can I read their solution?
    • Can I use their tools?

  5. What would I do if hard work wasn't an option?

    • If I could only spend 10% of the time, what would I do differently?
    • Often the "cheating" approach is actually the smart approach

The controversial conclusion:

The ability to NOT try hard is more valuable than grit. Winners don't grind their way through every problem—they're lazy. They ask "how can I make this easier?" before asking "how can I work harder?"

The real differentiator isn't work ethic. It's judgment about where to apply effort.

Someone who works 40 focused hours in the right direction will accomplish more than someone who works 80 unfocused hours in random directions.

Stop celebrating effort. Start celebrating effectiveness.

The goal isn't to work hard. It's to work smart. And working smart often means not working hard—it means questioning the problem, finding better approaches, leveraging what exists, and being willing to quit when evidence suggests you're wrong.

The paradox: The people who accomplish the most often look like they're not trying that hard. That's not because they're naturally gifted—it's because they're ruthlessly efficient about where they apply effort.

They solve the right problems. They use the right tools. They ask the right people. They quit the wrong approaches quickly.

They don't celebrate hard work. They celebrate solved problems.

You should too.

Today's Sketch

December 15, 2025