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AI Working Style18 min read

How to Explain AI to Executives (And Business Needs to Engineers)

The rarest AI skill is not building the system, it is translation. Explain an agent architecture to a director without jargon, and a business constraint to an engineer without hand waving, with a real drill built in.

Every skill in this series so far has been about doing real AI work well. This one is about something rarer and, in many organizations, more career defining: explaining that work to two audiences who speak almost entirely different languages, a director who wants to know cost and risk in one paragraph, and an engineer who wants exact behavior and edge cases, not a vague summary of business value.

Most people are genuinely fluent in one of these two languages and only passably functional in the other. The people who become genuinely fluent in both, who can walk into a room with executives and a room with engineers on the same day and be immediately useful in each, tend to become the person both sides trust to represent the other, which is a real, valuable, and specifically rare position to occupy.

This skill also tends to compound in a way that is easy to underestimate early on. A person who consistently translates well between two groups becomes, over time, the person each group asks to check their own communication before it goes to the other side, a real, informal position of trust that often precedes any formal title change but frequently predicts one.

By the end of this guide, you will understand exactly what changes between explaining AI work to an executive versus an engineer, not just in tone but in the actual content that matters to each.

You will have a real, worked example of the same update written two different ways, and a genuine drill, built into this guide, for practicing this translation skill on your own real work.

Why translation is a specifically screened for skill

A technically brilliant AI solution that nobody in the room can actually understand well enough to approve, fund, or trust does not ship, regardless of how good the underlying work is. This happens more often than it should: an engineer explains a genuinely strong solution using terms only other engineers follow, an executive loses the thread within the first minute, and a good idea dies in a meeting not because it was wrong, but because it was never actually communicated in a form the decision maker could act on.

Employers specifically value candidates who can bridge this gap because most organizations have a real shortage of people who can. Most people default to one native language, business or technical, and speak the other only haltingly when forced to. A candidate who can move fluently between both, in the same day, without dumbing anything down or hiding necessary detail, becomes a genuinely load bearing person in an organization far faster than their formal seniority alone would suggest.

Two audiences, two different questions: an executive asks what does this cost and what is the risk, an engineer asks what exactly should this system do.
An executive asks what this costs and risks. An engineer asks exactly what the system should do.

What actually changes between the two audiences

The content that matters, not just the vocabulary, genuinely differs between these two audiences, and understanding that difference is the actual skill, not just simplifying versus not simplifying.

An executive needs, in roughly this order: what this actually does in plain business terms, what it costs and what it saves or earns, what the real risk is and how that risk is being managed. Technical architecture details are almost always the wrong thing to lead with here, not because executives cannot understand them, but because they are not the information a funding or approval decision actually depends on.

An engineer needs, in roughly this order: exactly what the system should do, specific inputs and expected outputs, the real constraints and edge cases, and why this matters to a real person downstream, since that context genuinely improves engineering decisions even though it is business framing. Vague urgency, "this is important for the business," is almost always the wrong thing to lead with here, since it gives no actual technical direction.

Explaining an agent to a director, three sentences: what it does in plain terms, what it costs and saves, what could go wrong and how that is handled.
What it does, what it costs and saves, what could go wrong and how that's handled.
Explaining a business constraint to an engineer: not vague urgency, the specific rule, the specific exception, the specific reason it matters to a real person downstream.
The specific rule, the specific exception, the specific reason it matters downstream.

A worked example: the same update, two audiences

Here is the same real update about a spend categorization agent, written honestly two different ways for two different rooms.

"The spend categorization agent is live and handling about 80 percent of our monthly invoice volume automatically, saving roughly three analyst hours a week. The remaining 20 percent, the ambiguous cases, route to a human reviewer rather than being auto approved, so the financial risk is limited to that reviewed subset. Cost to run is modest and well under the manual labor cost it replaced."

Notice what stayed the same and what changed. The underlying facts, an 80 percent automation rate, a 90 percent confidence threshold, roughly three hours saved weekly, are identical in both versions, nothing was hidden or invented for either audience. What changed was which facts led, and how much technical or business framing surrounded them. The director version leads with value and risk. The engineer version leads with the specific mechanism and the actual next opportunity for improvement.

The two audience pitch drill: write the same update twice, once for a director, cost and risk first, once for an engineer, exact behavior first, compare what changed.
Write the same update twice, then compare what genuinely needed to change.

The real exercise: your own two audience pitch drill

This is the actual exercise promised for this guide. Pick one real piece of AI assisted work you have done, and write two short paragraphs describing it: one for a director, one for an engineer, using the ordering principles from this guide. Then compare them side by side and notice specifically what you changed, not just in wording but in which facts led.

A few real jargon translations

Use these as a starting point for your own translations.

Technical termPlain translation for an executive
Context windowHow much information it can consider at once before some of it gets left out.
HallucinationA confident sounding answer that turns out to be wrong.
Fine tuningTeaching the tool your specific style or format through examples, rather than general instructions.
Confidence thresholdThe cutoff point where the system decides to check with a human instead of proceeding on its own.
OrchestrationCoordinating several specialized tools together on one larger task.
Jargon translation examples: context window becomes how much it can read at once, hallucination becomes a confident wrong guess, fine tuning becomes teaching it your specific style.
The concept stays exact. Only the vocabulary changes.
Why this skill is rare: most people are fluent in one language, business or technical, genuine translators who are fluent in both are the ones who become the bridge.
Most people are fluent in one language. The real bridge is fluent in both.

How Marcus became the person both rooms trusted

Marcus, whose responsible AI habits appeared earlier in this series, had always been comfortable presenting his own work to other analysts, but visibly struggled the first time he had to present a project update directly to a director, defaulting to the same technical framing he would have used with a peer and watching the director's attention drift within the first minute.

After deliberately practicing the two audience drill on several of his own past updates, he built a real habit: before any presentation, he would ask himself which room he was actually in, and lead with cost and risk for one, exact mechanism for the other, using the same underlying facts either way. Within a few months, he noticed something he had not expected: engineers on his team started asking him to help translate their own updates before director meetings, and the director's team started looping him into technical conversations specifically because he could accurately represent what engineering was actually saying.

In a later interview, when asked to describe a time he had to communicate across a real technical and business divide, he had a specific, well practiced example ready, including both versions of the same real update. The interviewer's note afterward specifically flagged "strong cross functional communication," a rarer compliment in his experience than any purely technical praise he had received before.

Marcus later said the strangest part of the whole experience was how mechanical the actual skill turned out to be once he had practiced it. It had felt, at first, like a kind of social talent some people simply had. In practice it was closer to a checklist, decide which room you are in, lead with what that room actually needs first, keep the underlying facts identical either way. Nothing about it required being naturally charismatic or persuasive, just consistent.

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The rest of this guide, including the worked example, the career action plan, and the interview ready summary, is for subscribers. Any paid plan unlocks every post like this one, and Foundation adds the full course catalogue.

Practice these interview questions

Translation skill between technical and business audiences is hard to describe in the abstract and easy to test live. The questions below are the ways interviewers actually check for it. Work through your own answer first, then compare with the sample.

Why they're asking: They're checking whether you translate the limitation into business terms, risk, cost, timeline, rather than giving a watered-down technical explanation.

Hit these points:

  • Connect the limitation directly to the decision the executive is actually making
  • Use a concrete framing, like the share of outputs that need a human check before they're trustworthy
  • Name the actual tradeoff you hand them: accept the review cost now, or delay to improve accuracy first

Sample answer:

  • The move: "I connect the limitation directly to what it means for their actual decision."
  • The framing: "Something like, the current accuracy means about one in ten outputs needs a human check before we trust it for a customer-facing use, so shipping now means accepting that review cost or delaying to improve accuracy first."
  • The reasoning: "That gives them a real tradeoff to weigh, not a technical explanation of why the accuracy is where it is."

Remember it as: Give them the tradeoff, not the mechanism.

9 of 12 answers are locked. Any paid plan unlocks every question like these, and Foundation adds the full course catalogue.