Most engineering teams treat knowledge sharing as an occasional meeting or an afterthought that happens once work is “done.” This is why teams slow down over time. The work gets more complex, the people who understand it become more specialized, and the cost of interruptions increases. When knowledge lives in a few heads, every project requires a pilgrimage to the same experts. Engineers reinforce knowledge silos when asked by stakeholders about creating new functionality or fixing existing features in those specialized areas.

“That has to do with billing so Alice will need to look at that.”

“Bill did that work so send it over to him.”

These knowledge silos feel like a powerhouse when the team is small, the codebase is small, and the speed the features are moving down the delivery conveyor belt is fast. But as your team scales, the size and complexity of your product grows, and your organization begins to have to consider tradeoffs to get access to a singular expert for an area that now has a priority need, the execution pain points intensify exponentially instead of linearly.

Good knowledge sharing fixes this. It turns individual expertise into something the entire team can use. It also protects the team from the risk of single points of failure and makes the codebase less fragile.

Effective knowledge sharing begins before the code is merged, and it continues long after the first version ships. It moves through three phases that each serve a different purpose.

Phase 1: Show and Tell.

The goal is awareness. Give the team a broad overview of what was built, why it exists, and how it fits into the larger system. This is not about deep detail. It is about creating context so nobody is surprised when they touch the code later.

I am a broken record when it comes to mentioning to people that context is king. Context doesn’t lead to analysis paralysis, it creates awareness and unleashes creative problem solving. No matter how you’re working to align your teams, the first step is shared context.

Phase 2: Paired Deepening.

After the overview, shift to a smaller group and pair through the important paths. Walk through specific flows, explain tradeoffs, and let others ask the questions that only appear when you follow the code line by line. This is where the next layer of expertise forms.

Phase 3: Distributed Ownership.

Once a few people have the deeper understanding, invite them to extend the work. Let them fix a bug, add a small feature, or write a test. When someone contributes to a piece of code, they mentally claim part of it. This creates new experts who can support the team in the future.

When knowledge sharing works, the team does not rely on documentation alone. The information spreads through human connection, shared problem solving, and real collaboration. The interruptive cost of onboarding drops, because no one has to dig through days of Slack messages or hunt for context that only one person has.

You know your knowledge sharing system is healthy when multiple people can work in the same area of the code without fear, hesitation, or hours of warm-up. That is what healthy engineering organizations look like. They scale through people, not pressure.

Staff Engineer: Leadership Beyond the Management Track by Will Larson

Why this matters

Key ideas to pay attention to when reading:

This is not a tactical how-to article. It is a mindset reset. If you want teams that move fast without burning out experts, you must design for knowledge flow, not knowledge hoarding.

You do not need a new tool or a big process overhaul to improve knowledge sharing. You need intention and repetition. Here is a concrete way to start this week.

Pick one piece of work that recently shipped or is about to ship. Then run it through these steps.

Step 1: Run a 15 minute show and tell

Have the primary contributor walk through:

Keep it high level. The goal is context, not mastery.

Step 2: Pair with one additional engineer

Choose someone who did not work on the feature. Pair for 30 to 60 minutes and walk a real flow through the code. Let them drive the keyboard where possible. Encourage questions and stop to explain tradeoffs.

This is where understanding starts to stick.

Step 3: Hand off a small follow-up task

Ask the second engineer to:

This converts passive understanding into ownership.

Step 4: Make the ownership explicit

Call out that there are now at least two people who understand this area well enough to support it. Say it out loud. This reinforces the behavior you want repeated.

Ask senior engineers to measure their impact differently for one sprint. Instead of asking what they shipped, ask:

That question alone changes how people approach collaboration.

The goal is not to slow delivery. The goal is to reduce the cost of future work. Knowledge sharing is an investment that compounds quickly when done intentionally.

If the answer is unclear or uncomfortable, that is not a personal failure. It is a signal about how knowledge is currently flowing on your team.

Where does knowledge live today: in systems or in people?

Be honest. Are critical paths documented and shared, or do they depend on a handful of engineers being present in meetings and Slack threads?

When was the last time a handoff actually created a new owner?

Many teams do walkthroughs. Fewer teams follow up with real ownership. Where does your process stop?

Are your best engineers rewarded for making others better?

Or are they implicitly incentivized to hold onto complexity because it makes them indispensable?

What would break first if one senior engineer went on vacation for two weeks?

That answer usually reveals where knowledge sharing needs the most attention.

Are pairing and collaboration treated as productivity drains or productivity multipliers?

The fastest teams are often the ones that invest the most time upfront in shared understanding.

If you onboarded a new engineer tomorrow, how long before they could safely change production code?

That timeline is one of the clearest indicators of how effective your knowledge sharing really is.