Why Robotics Takes Decades: Clearpath Founder Ryan Gariepy on Building in Hardware

Ryan Gariepy explains why robotics is slow, why humanoids are overhyped, and what founders get wrong about building hardware companies.

In this episode of the Founders in Arms podcast, we sit down with Ryan Gariepy, co-founder of Clearpath Robotics and Otto Motors, to talk about robotics, hardware startups, and why building in the physical world takes decades—not years.

Ryan explains why robotics is fundamentally a systems problem, why hype cycles keep repeating, and why many founders misunderstand what it takes to succeed in hardware.

The conversation also explores humanoid robots, venture capital dynamics in robotics, and why the most successful companies start with narrow, practical use cases.

This conversation dives deep into:

  • Robotics as a systems discipline

  • Why hardware compounds over decades

  • Bootstrapping when “nobody cared about robotics”

  • Why humanoid robots are overhyped

  • The role of venture capital in shaping bad incentives

  • Why robotics companies should start narrow

  • How talent dynamics differ in hardware vs software

  • The future of physical AI and real-world automation

In this episode, we cover:

(00:00) Robotics is a systems problem, not a single breakthrough

Ryan explains that robotics is not unlocked by one technology like AI or better sensors.

Instead, progress comes from many layers of technology compounding over time—hardware, software, manufacturing, and systems integration.

He compares it to semiconductor manufacturing, where no single company or invention created modern chips.

(06:30) Building a robotics company when nobody believed in it

In the early days, robotics was not seen as a viable business.

Ryan explains that from 2009 to 2014, Clearpath struggled to raise capital and had to bootstrap.

At the time, most people believed robotics could only work in defense, not commercial markets.

(08:18) Becoming profitable in 18 months

Despite limited funding, Clearpath became profitable quickly by focusing on real customers.

Their early customers were:

  • Universities

  • Research labs

  • Government institutions

This forced them to build practical products instead of speculative technology.

(10:28) Starting with a platform, not a full solution

Clearpath began by building robotics platforms for researchers.

They provided modular systems that allowed customers to experiment and build their own applications.

Only later did they expand into industrial automation, where the larger opportunity emerged.

(18:16) Why robotics is more exciting now than ever

Ryan argues that today is the most exciting time in robotics history.

This is driven by:

  • Better underlying technology

  • More available capital

  • Greater societal adoption

However, he warns that excitement often leads to unrealistic expectations.

(19:22) Why hype cycles keep repeating in robotics

Each generation believes a new technology will “solve” robotics.

Previously it was:

  • Deep learning

  • Convolutional neural networks

  • More data

Today it is LLMs and transformers.

Ryan argues that none of these are silver bullets—progress remains incremental and system-driven.

(22:17) Hardware vs software growth dynamics

Ryan contrasts software and robotics growth.

Software:

  • Fast growth

  • Quick scaling

  • Rapid saturation

Robotics:

  • Slower growth

  • Sustained over decades

  • Compounding impact

He warns founders not to expect software-like growth in hardware businesses.

(23:40) Why build a robotics company at all?

Despite the difficulty, Ryan says founders should build in robotics because:

  • It is fun

  • The problems matter

  • It creates real-world impact

He emphasizes that Clearpath was not started because it was financially optimal.

(25:27) Hardware attracts mission-driven talent

Ryan explains that hardware companies often attract people who genuinely love building physical systems.

This creates a unique advantage:

  • Stronger long-term commitment

  • Passion-driven teams

  • Lower sensitivity to short-term outcomes

(27:20) Physical AI and real-world impact

Ryan argues that software alone cannot solve many real-world problems.

At some point, physical systems are required:

  • Autonomous logistics

  • Manufacturing

  • Infrastructure

This is where robotics becomes essential.

(28:13) Humanoid robots: impressive but miscalibrated

Ryan believes humanoid robots are technologically impressive but overhyped.

The challenges include:

  • High cost

  • Complex deployment

  • Unsolved general intelligence

He also introduces the idea that robot form factors create expectations for users.

(32:41) The “promise problem” in robotics

A key insight:

The more a robot looks like a human, the more users expect from it.

A Roomba sets a narrow expectation (cleaning floors).
A humanoid suggests it can do everything.

When expectations are not met, adoption suffers.

(34:35) Why consumer robotics is still early

Even advanced consumer robots still face trust issues.

Users often:

  • Don’t fully trust them to complete tasks

  • Need supervision

  • Prefer manual control

This slows adoption despite technological progress.

(36:01) Why vertical robotics wins

Ryan points out that the most successful robots today are highly specialized.

Examples include:

  • Restaurant delivery robots

  • Airport cleaning robots

  • Warehouse automation

These succeed because they operate in controlled environments.

(41:15) Venture capital can distort robotics companies

Ryan explains that large venture funds often push companies toward unrealistic strategies.

Large check sizes force:

  • Bigger visions

  • Faster scaling

  • Riskier bets

Smaller, more patient capital allows companies to focus on practical progress.

(45:22) Why robotics is less competitive than software

Unlike software, robotics has:

  • Higher barriers to entry

  • Longer development cycles

  • Fewer competitors

This can make it attractive for investors despite slower growth.

(50:31) Biggest mistake: ignoring gut instinct

Ryan shares that one of his biggest mistakes was trusting a charismatic but inexperienced executive over his own instincts.

The result was a product decision that created long-term issues.

His takeaway:
Trust your instincts as a founder.

Key Takeaways for Founders

Robotics is a systems problem

There is no single breakthrough that unlocks robotics. Progress comes from multiple technologies compounding over time.

Hardware requires different expectations

Founders should not expect software-like growth. Robotics companies scale more slowly but can build enduring advantages.

Start narrow, then expand

The most successful robotics companies begin with specific use cases and expand over time.

Hype cycles are inevitable

Every generation believes a new technology will solve robotics. Founders should stay grounded in reality.

Form factor shapes user expectations

What your product looks like determines what users expect it to do.

Trust your instincts

Founders often have better judgment than they give themselves credit for—especially early on.

About the Guest

About Ryan Gariepy

Ryan Gariepy is the co-founder of Clearpath Robotics and Otto Motors, companies focused on autonomous mobile robots for industrial applications.

He spent over a decade building one of the leading robotics companies in North America before its acquisition by Rockwell Automation.

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