The Speed of Execution: What Actually Makes Teams Fast

The Speed of Execution: What Actually Makes Teams Fast

We all know Einstein, right? The famous, wild-haired scientist who gave us relativity. Turns out, his most famous formula, E = MC², can tell you (almost) everything you need to know about how to execute at the speed of light (almost).

Had I written this a year ago, I would have said that Speed has become a powerful competitive weapon. However, in the era of AI, speed is now an absolute must. And we are seeing how what looked like a formidable moat yesterday is fleeting today.

Even Microsoft, one of the largest and most dominant forces in the software world, which entered the AI arms race with a clear moat - distribution, strategic partnerships, and enterprise chops - is losing ground to competitors. To the extent that the CEO is now hands-on, reshaping how the company operates and builds products.

“If you don’t reinforce clarity, the team will invent their own and that’s how speed quietly dies.”

Guy Assedou, Head of Product @ Monday.com

If speed matters this much, why don’t more teams move fast?

Because moving fast is hard. Really hard.

In such times, when developers 10x their output, the hard truth is: Product can have a detrimental impact on speed.

As time-to-production declines with the advent of AI-generated code, it becomes less about effort and more about having the right mindset to deliver at the speed of light. This is no longer in a tech cycle; this is a mindset race. One where you run a marathon distance but at a sprint pace (not the agile sprint, the 100m one).

Which brings us back to Einstein, and how we can use it to gain speed.

Execution Speed = Meaning × Clarity × Chunking

Let’s break it down.

1. Meaning — Build with Purpose, Not Pasta

Meaning is the foundation of speed. If every feature is an experiment, every idea is “worth trying,” and every meeting ends with “let’s build both and see,” you’re just throwing pasta at the wall and calling it strategy. In the AI era, where code is cheap and "building" is easy, Meaning is the only filter that prevents bloat.

Look at Anthropic. They started small and narrow, and with a grudge (that helps too, apparently), focused on ‘Constitutional AI’ and high-performance coding tools. While others built everything for everyone, they had the raw conviction to stay focused. That "Meaning" allowed them to overtake giants in enterprise spend.

In real life, meaning comes from having conviction in your unique value and a deep understanding of your audience. Getting there requires consistent, unglamorous work: talking to customers, watching their workflow firsthand, and forming a POV you can commit to.

How can you tell when Meaning is missing?

Engineering and design start asking "what if" questions and architecting for every edge case. Today, AI is the ultimate pasta machine; it can generate ideas faster than you can vet them. Without a deep POV, you’re just making a mess at 10x speed.

2. Clarity — Row the Boat in the Same Direction

Meaning sets the direction; Clarity ensures no one is rowing sideways.

Picture a rowing team: eight top-notch athletes. They know where the goalposts are. Now imagine each row in a different direction. Some outward. Some sideways. One is still convinced this is practice. The boat moves, just not nearly as fast as it could.

I’ve been on both sides of this in my career. When clarity was obvious only to me, and later, when clarity was shared. It removed drag. It acted as a multiplier, making the boat glide. I could feel it.

To get to Clarity, everyone needs to have a shared understanding: what the problem is, for whom, why it matters, and what success looks like. Don’t be fooled - there is no vacuum. When clarity is missing, people will compensate; engineers over-architect. Designers optimize design for a different need. Leaders add one quick thing. Scope creeps, focus is diluted, and speed disappears with it. I felt that too.

Clarity isn’t a one-time event at kick-off. As people switch context and dive deep into execution, the bigger picture gets blurry. Repeatedly reinforce. It requires effort, but the upside is that clarity becomes an anchor — a shared frame of reference for decision-making. And when anyone can ship with vibe coding, they better ship the right thing. Or you risk getting feature slop and diluted value.

I challenge you to ask five team members tomorrow what they are solving for and what is the single most important measure of success. If you get different answers, you don't have a talent problem, you have a friction problem.

3. Chunking — Smaller Strokes, Bigger Impact

Moving fast is not enough. Speed needs to be visible and felt. That’s where chunking comes into play.

Chunking is the discipline of ruthlessly prioritizing the minimum delightful scope. Large, "perfect" V1s are where speed goes to die. It kills momentum and stifles learning. I know this can feel scary, putting a ‘small’ increment in front of a customer. But at the current pace of innovation, you risk being obsolete before you ever ship.

Chunking creates a strong sense of progress, felt by customers and competitors alike. It forces a reaction and puts slower teams at a disadvantage. It also creates rapid feedback loops that shape what gets built next, and make customers feel heard, building trust and loyalty.

Lovable is a great example. It leans into a minimum lovable product philosophy and rapid iterations. They ship something users adore quickly, refine it, as AI and use cases evolve. They ‘build in public’ through community-first tactics (GitHub launch, Product Hunt, social demos, co‑marketing) to generate rapid feedback loops. They got it to a point where they re-find product-market fit every 90 days. This high-frequency feature and product launches accelerate learning, monetization, and expansion, getting them to $200M ARR milestone in one of the fastest trajectories ever seen for a SaaS company.

In the age of AI, Chunking acts as a forcing function. Smaller deliverables require shorter cycles. Decisions must be made faster. Testing needs to be automated. Focus must be maintained.

Not everyone can be Lovable, but I’ve seen teams reclaim time and momentum simply by breaking a four-month initiative into four milestones. Nothing changed on paper, but everything changed in how they operated.

When teams chunk well, strategy rapidly becomes a reality, not just a pretty slide deck.

The Compound Effect

The most successful companies don’t excel at just one of these. They integrate all three.

Anthropic and Lovable demonstrate the power of speed. They anchor execution in meaning, reinforce clarity continuously, and operate through disciplined chunking. Together, these create a compound advantage. And the outcomes are undeniable.

E = MC² mindset doesn’t just lead to shipping faster. It changes how organizations operate, decide, and compete.

Adopt it, and deliver at the speed of light. Or don’t, and risk being left behind. In the age of AI, this will happen faster than you may expect.