As a CEO, you hold the authority. You see the business risk. You hear the client complaints. You notice missed deadlines, production bugs, slow delivery, or technical decisions that seem too complicated from the outside.

What you usually don’t have is the technical context.

And the gap —  between your authority as a CEO and the little technical context —  is where feedback to engineering teams often goes wrong.

You don’t need to be a great tech lead to give useful feedback. You do need to know the difference between a concern and an observation. 

As “Something feels wrong with this feature” is not feedback. But “The payment flow failed twice after the last deployment, and we did not have a rollback plan ready” is.

The first creates anxiety. The other start is a way of starting a discussion.

Keep in mind that the dev team are open minded, and rarely reject feedback because they are defensive. More often, they blow off suggestions because they are vague, unfair, technically uninformed, delivered too late, or delivered publicly when it should have been private. 

So what are the other pitfalls of providing feedback?

Why CEO Feedback Often Fails With Engineering Teams 

The CEOs are trained to think in business outcomes: Revenue. Delivery. Client trust. Risk. Roadmap. Speed.

Engineers think in systems: Architecture. Dependencies. Constraints. Trade-offs. Technical debt. Quality. Edge cases.

Both sides are right. But they speak different languages.

A CEO may say:
“We need this faster.”

An engineer hears:
“You do not understand the complexity.”

A CEO may say:
“This should be simple.”

An engineer hears:
“You do not respect the work.”

A CEO may say:
“Why was this missed?”

An engineer hears:
“You are blaming me before understanding the system.”

This is where feedback starts to break. Not because the CEO is wrong to care about speed, quality, or business impact. But because the feedback jumps too quickly from outcome to judgment.

Good tech feedback needs one extra step: context. Before you comment on the decision, understand the constraint behind it.

1. Was the team working with legacy code?
2. Was the deadline unrealistic?
3. Was there a missing requirement?
4. Was the problem caused by one engineer, or by the process around them?
5. Was the “bad decision” actually the best possible option under pressure?

If you skip this step, your feedback may still be technically correct. But it will not land.

Six Practices When Giving Feedback to Engineers 

1. Separate the code from the coder.

 Do not turn a technical problem into a personal verdict. Say:

“This part of the system is difficult to test.”
“The current implementation creates risk in the checkout flow.” 
“We need a second reviewer for anything touching payments.” 

That changes the entire conversation. Of course, there are moments when behavior needs to be addressed directly: missed communication, repeated lack of ownership, ignoring agreed standards, or pushing unreviewed code into production.

But even then, the feedback should stay specific.
The more specific you are, the less defensive the conversation becomes.

2. Match the channel to the weight of the message.

A one-line PR comment is fine for a naming convention. A recurring pattern of rushed reviews on critical paths deserves a real conversation. Not a comment thread the whole team can see.

The channel is part of the message.

When a CEO gives critical feedback publicly, even with good intentions, it can feel heavier than expected. The tech team knows who the big cheese is.

A short comment from a CEO can feel like a public judgment, even if you meant it as a small note.

3. Ask before you assert. 

It is better to start with "Walk me through why you built it this way" which gets further than "I'd have done this differently."

As there may be a legacy constraint you forgot about. A deprecated dependency. A client deadline you agreed to. A product requirement that changed twice. A security limitation. A shortcut the team took because leadership asked for speed.
Once you understand the context, the feedback becomes sharper. You are no longer reacting to what you imagine happened. You are responding to what actually happened.

4. Point to a shared standard, not a personal preference. 

Engineers respect standards and clear guidelines more than opinions.

"Anything touching payments gets a second reviewer and a rollback plan" is a bar that the whole team already agreed to. “We agreed that production-critical services need test coverage before release” is clear.

“Our engineering standard is that new services must include logging, monitoring, and documentation before handoff” is operational. 

Without shared standards, every feedback conversation becomes personal.

With shared standards, the conversation becomes much simpler:

Did we meet the bar or not? If not, what do we change?

A CEO should not invent standards during the feedback conversation. The best feedback refers to a standard the team already knows.

5. Give Feedback Close to the Event. 

If a deployment issue happened in January, do not bring it up for the first time in April during a performance review.

By then, the details are gone. The engineer may not remember the exact context. The team has moved on. The feedback feels like stored resentment, not leadership. 

Good feedback should be close to the incident. Not emotional and immediate. But close.

Sometimes that means the same day. Sometimes it means the next day after everyone has slept.  Sometimes it means after the incident review, when the facts are clear.

The goal is simple: Do not let important feedback become old news. Engineers respect timely feedback because it is connected to reality.

6. Close the loop.  

Feedback should not end when you finish talking. After a difficult conversation, try to ask:

1. “Was the way I gave that feedback clear?”
2. “Did I miss any context?”
3. “Was there a better way to raise this?”
4. “What should I understand before I comment on something like this next time?”

This is not about checking whether the tech expert liked the feedback. It's about understanding how it came to be. Sometimes the engineer will tell you: 

“You were right about the issue, but you brought it up too publicly.”
Or: “You were missing the deadline pressure we were under.”
Or: “The problem was not the code. The problem was that the requirement changed after implementation.”

That is valuable information. A CEO who gives feedback should also be willing to receive it.

Where AI can Help to a Non-Technical CEO Give Better Feedback

I was skeptical about using AI while providing feedback to engineers. It felt like the one part of leadership a CEO shouldn't hand off.

I still half-believe that. But here's the narrower claim I've come around to, specifically for CEOs who don't write code themselves:  AI closes part of the context gap that causes vague feedback in the first place, and it sharpens your prep before a hard conversation. AI helps to remove judgment from your first draft. 

Before a conversation with an engineer, I write a rough version of what I want to say and run it through an AI check against the Situation Behaviour Impact (SBI) model. Does it separate situation, behavior, and impact, or is it sneaking in a verdict word like "careless" or "sloppy"? It catches at least one landmine most times.

1.  AI Can Help You Understand the Technical Context.

   Before I talk to an engineer about a bug or a design decision, I ask an AI assistant to explain the relevant code, PR, or system in plain language first. That's the difference between "be more careful with payments" and "the null check on the optional field," and engineers feel that difference immediately.

2.  AI Can Help Spot Patterns Across Pull Requests.

   AI-assisted code review tools can surface trends across months of PRs — a recurring test coverage gap, one service quietly accumulating technical debt. No single PR looks alarming on its own, but the pattern does, and it's exactly what a CEO who isn't in the codebase daily will otherwise miss entirely.

3. AI Can Help You Rehearse the Conversation. 

   I've used AI to roleplay how an engineer might respond defensively before a hard conversation, so I don't retreat into vague, softened language the moment it gets uncomfortable.

4. AI Can Help Check Your Own Bias.

   Review of your own feedback history over a quarter can flag if you're consistently harsher with certain engineers, or thinner with remote team members than with whoever sits closest to your office. Uncomfortable. Useful.

Here's the line I don't cross: the moment AI starts writing the actual message instead of refining mine, I've lost the thing that made it land. That it came from me, about their specific work, with enough context to be credible. Use AI to close your context gap and sharpen your draft. Never as the voice.

A Checklist for the Conversations You're Avoiding

1. Do I have a specific situation and behavior, not a vague impression?
2. Have I separated the person from the code?
3. Do I actually understand the technical constraint they were working under — or do I need to ask first?
4. Is this the right channel — a private conversation vs. a PR comment the whole team sees?
5. Am I giving this feedback close to the incident, not months later in a review?
6. Have I made space for them to respond, not just receive?
7. Am I pointing to a shared engineering standard, or just my own opinion?
8. If I used AI to build context or check tone, does the message still sound like me?
9. Will I follow up on how this landed?

If I can't check most of these, I will wait a day. It's better than sending the message I almost sent at midnight.

Feedback Approaches for CEOs and Engineering Teams: A Quick Comparison
Approach

None of these is universally best. A CEO's job isn't to master all of them. It's to close the context gap before choosing one.

If you're a founder or CEO I'd like to hear your experience of giving feedback to your tech team. Let`s chat, maybe we can exchage few funny stories.