Calvin Arterberry

Built & sold 2 startups | Techstars alum | CEO @ Flowbot Forge — AI that grows revenue, cuts costs, automates sales, marketing, customer service & internal work

[Calvin Arterberry @CalvinArterbery]

Great performance is never the result of one individual operating in isolation; it arises from collaborative effort and intense debate.

Build a team of clear thinkers who are not afraid to relentlessly challenge each other's assumptions

[Calvin Arterberry @CalvinArterbery]

When hiring executives, do not fall for the "halo effect" by judging someone based on general impressions, style, or charisma.

Use structured, scenario-based interviews to mitigate intuition and test their real-time cognitive skills and decision-making rigor

[Calvin Arterberry @CalvinArterbery]

CEOs often suffer from "extinction by instinct," where they rely too heavily on gut feelings and take immediate action without rigorous analysis.

Balance swift action with disciplined thought to avoid catastrophic corporate blunders

[Calvin Arterberry @CalvinArterbery]

The human brain instinctually assumes the world is causally connected, causing us to manufacture patterns and links that do not actually exist.

Over-reliance on historical patterns can stifle innovation and cause your company to miss critical threats to its core business

[Calvin Arterberry @CalvinArterbery]

Are you running 10,000 A/B tests? Even with high algorithmic accuracy, a vast majority of your "discoveries" might actually be false positives.

Understanding the False Discovery Rate is crucial so you don't confidently invest in failing strategies

[Calvin Arterberry @CalvinArterbery]

Big-bet decisions, such as major acquisitions, are infrequent but carry high risk and shape the company's future.

Improve these choices by explicitly assigning someone to argue the case for and against the potential decision to spur productive debate

[Calvin Arterberry @CalvinArterbery]

Beware of "Frame Blindness" when making decisions. The mental frames we use help us filter information, but they can magnify some aspects of reality while making other critical data virtually invisible.

Always consciously acknowledge the limitations of your perspective

[Calvin Arterberry @CalvinArterbery]

A core component of Executive Intelligence is self-evaluation, which is the capacity to critically assess one's own performance and adapt behavior accordingly.

Star executives actively encourage feedback that may reveal an error in their judgment

[Calvin Arterberry @CalvinArterbery]

In the AI era, classical recommendation systems will fail if they do not account for scarcity.

Merging recommendation systems with microeconomic matching markets prevents congestion and optimizes loads across the system

[Calvin Arterberry @CalvinArterbery]

Decision science bridges data with strategy by drawing on economics, psychology, and machine learning.

While pure data science might just find general insights, decision science focuses on answering specific business questions to make optimal choices under uncertainty

[Calvin Arterberry @CalvinArterbery]

CEOs, never accept the first version of a business question from your team. The initial question someone asks is rarely the most valuable one to answer.

Drill down to the root cause of the problem before you attempt to solve it

[Calvin Arterberry @CalvinArterbery]

Holding onto an underperforming business unit or project because of emotional or legacy attachment is known as the sunk-cost fallacy.

To beat this, change the burden of proof from asking why an asset should be cut to why it should be retained

[Calvin Arterberry @CalvinArterbery]

As you delegate tasks to AI agents, beware of the "authority gradient".

Effective AI teammates must be calibrated to challenge recognized human errors and overcome sycophancy, dynamically adjusting their standing based on the criticality of the task

[Calvin Arterberry @CalvinArterbery]

Do you ignore unpleasant information? The "ostrich effect" happens when leaders figuratively bury their heads in the sand to avoid difficult data.

Engage in readout processes and summarize discussions as they happen to ensure everyone faces reality together

[Calvin Arterberry @CalvinArterbery]

Two AI agents. One builds. One tests. Neither sleeps.

Multi-agent systems aren't a research project anymore. They are a production reality.

The CEO who understands recursive AI loops in 2025 has the same advantage as the CEO who understood the internet in 1998.

You already know how that story ended.

[Calvin Arterberry @CalvinArterbery]

Delegated decisions are the most frequent, yet often the least understood within many organizations.

You can improve these by empowering your employees with the authority, tools, and clear strategic guidance they need to act decisively

[Calvin Arterberry @CalvinArterbery]

Do not expect AI to make complex strategic choices for you. Expert systems are most valuable when viewed as tools for decision-aid rather than substitutes for human decision-makers.

The ultimate responsibility for framing problems, interpreting insights, and balancing tradeoffs remains yours

[Calvin Arterberry @CalvinArterbery]

Recursive prompting is the most underused skill in business right now.

You give AI an answer. Then you feed that answer back in and ask it to improve it. Then again. Then again.

Three rounds of this beats 90% of first drafts from any tool.
Most people stop at round one.

[Calvin Arterberry @CalvinArterbery]

Not all decisions are created equal, so organizations should quickly boost efficiency by categorizing decisions into big-bet, cross-cutting, and delegated types. Adjusting your approach based on frequency and risk will streamline your company's processes

[Calvin Arterberry @CalvinArterbery]

The mantra of "speed, speed, speed" can be dangerous; while making a quick decision is essential sometimes, in other circumstances taking more time to collect data is necessary.

Sometimes leaders have to "go slow to go fast" to ensure they actually understand the problem