If You Can’t Explain It, You Don’t Understand It

Let me start with a confession:  I’ve been in situations where I thought I understood something — a tool, a hack, a system — until I tried to explain it to someone else. That’s when the truth hits you in the face harder than a failed exploit in the middle of a live pentest.

If you can’t explain what you do clearly, you don’t fully understand it.  It’s not just a quote you see floating around LinkedIn. It’s reality. And for an ethical hacker, it’s mission-critical.

Because in cybersecurity — and now in the age of AI agents — clarity is not optional. It’s the difference between a controlled test and a catastrophic misunderstanding.

The Myth of “I Know What I’m Doing”

Many professionals — not just hackers — walk around with an illusion: If I can do it, I must understand it.

But here’s the trap: being able to execute something by habit or muscle memory doesn’t mean you grasp it well enough to teach it, delegate it, or automate it.

Think of it like this:  You might know the exact command to run in Metasploit to exploit a certain vulnerability. But if I asked you, Why does that command work? What’s actually happening under the hood? What preconditions need to exist for success? — could you answer without Googling?

If the answer is “maybe not,” then you’ve just identified a gap in your understanding.

From Ethical Hacking to AI: The Same Core Principle

When I train junior pentesters or write scripts for AI agents to automate tasks, I face the same challenge:  If I can’t articulate exactly what needs to be done — including the “why” behind every step — the result will fail.

With AI agents, it’s even more brutal.  Unlike a human colleague who might guess your meaning, AI takes instructions literally. If you skip steps, use vague terms, or assume the agent “just knows,” you’re going to get garbage output.

It’s like giving an intern a mission to “find vulnerabilities in the system” without specifying:

• Which system?

• What tools to use?

• What’s in scope?

• What defines “vulnerability” here?

• How should the results be documented?

The intern will be lost. And so will your AI.

Clarity is a Security Skill

In ethical hacking, ambiguity is risk.  When we report vulnerabilities to clients, we don’t just say:

“Your site is vulnerable to SQL Injection.”

We specify:

• Where it was found (exact endpoint)

• How it was tested (payloads used)

• Impact if exploited

• Proof of concept screenshots or logs

• Steps to fix it

Without that level of clarity, the report is useless.

That’s why clarity isn’t just good communication — it’s leadership. You are guiding others (humans or AI) through complex territory, making sure they don’t trip over the same pitfalls you’ve avoided.

Why Delegation Fails Without Understanding

Delegation isn’t dumping tasks onto someone else. It’s transferring ownership while ensuring they have enough clarity to succeed without you standing over them.

If you don’t deeply understand what you’re delegating, here’s what happens:

1. You over-explain irrelevant details (because you’re unsure what’s actually important).

2. You under-explain critical steps (because you didn’t realize they were crucial).

3. You misprioritize the order of actions (because you never thought through dependencies).

In hacking terms, it’s like telling someone to “crack the password” but forgetting to mention they need to gain hash access first. They’ll waste hours brute-forcing the wrong thing.

Teaching AI Is Like Teaching a Child

Training AI agents isn’t magic — it’s a communication skill.

Just like explaining to a kid how to make a peanut butter sandwich, you have to clarify:

• What matters (bread, peanut butter, knife — not “use your imagination”)

• In what order (spread before cutting, not the other way around)

• What success looks like (sandwich intact, not peanut butter smeared on the ceiling)

With AI, the principle is the same:  If you tell it “scan the website for vulnerabilities,” you might get random results. But if you say:

“Use OWASP ZAP to scan , focusing on XSS vulnerabilities. Log all findings in a CSV with columns for URL, payload used, and confidence score. Ignore 404 errors. Limit scan depth to 3.”

Now you’ve defined what matters, in what order, and what success looks like.

Why Clarity is Leadership in a World of Agents and Automation

Automation is everywhere — from AI-based vulnerability scanners to autonomous SOC monitoring tools.

But here’s the catch: these tools are only as effective as the clarity of the person directing them.

In this new reality, your value isn’t just in doing the task — it’s in translating complex goals into executable steps that humans and machines can follow without confusion.

In other words: Clarity has become a leadership skill.

The Hacker’s Framework for Achieving Clarity

Over the years, I’ve developed a mental checklist whenever I explain or delegate a task — whether to a human or AI:

Define the objective

• What is the end goal?

• Why does it matter?

Set the scope

• What’s in and out of bounds?

• What resources are available?

Break it down into ordered steps

• Sequentially, like a playbook.

Define success criteria

• How will we know the task is done correctly?

Identify possible pitfalls

• What could go wrong and how to handle it?

This isn’t just theory. In pentesting, it’s how we prepare our engagement plans. In AI, it’s how we prompt and fine-tune agents.

Example: Bad vs Good Task Instruction

Bad:

“Find open ports on the target.”

Good:

“Using Nmap, scan for open TCP ports 1–1000. Use the flag to detect service versions. Save results in in the directory. Exclude IPs 192.168.1.5 and 192.168.1.10. Stop scan if more than 50 hosts respond as live.”

Notice the difference?  The second version leaves no ambiguity, and an AI agent or teammate can execute without coming back with “What do you mean by…?”

Why This Matters More Than Ever

In the pre-AI era, if you didn’t explain clearly, a human might still figure it out through context or improvisation.

AI doesn’t improvise well unless you train it to.  And poorly trained AI is like an intern who works 24/7 but delivers the wrong thing faster than you can say “data breach.”

In cybersecurity, this could mean:

• Running tests on the wrong system (legal risk)

• Reporting false positives (wasting analyst time)

• Missing real vulnerabilities (actual danger)

That’s why clear, complete communication is a defensive skill.

How Ethical Hackers Can Practice This Skill

Document your own processes

• Next time you do a recon scan, write every step as if you were teaching it to someone with zero prior knowledge.

Explain a tool you use daily

• Pick one tool (Burp Suite, Nmap, Wireshark) and explain it to a non-technical friend in plain English.

Create SOPs (Standard Operating Procedures)

• Turn repeated tasks into clear, reusable instructions for others — or for AI.

Challenge yourself with “one-take explanations”

• Pretend you have 60 seconds to explain something without prep. If you can’t, you probably don’t understand it well enough.

Clarity as a Competitive Advantage

In the coming years, technical skills alone won’t be enough.  With AI agents handling more of the “doing,” the people who can clearly describe the “what” and “why” will rise to the top.

In the ethical hacking world, that means:

• Being the person who can design the pentest plan, not just run it.

• Being trusted to brief C-level executives because you can speak their language without losing technical accuracy.

• Being the one who can train AI to handle grunt work while you focus on higher-level strategy.

That’s leadership.

Final Thought

In hacking, we’re taught to “own the system.”  But in leadership — and now in AI-driven workflows — the first system you need to own is your own understanding.

If you can’t explain it simply, you don’t own it.  If you don’t own it, you can’t delegate it.  And if you can’t delegate it, you’ll always be stuck doing the work yourself.

So, in this new world of agents and automation:  🎯 Clarity is not optional — it’s the new form of power.