Software has spent years making dependencies cheap to add. One install command can save days of work. But every dependency also adds another maintainer, release cycle, security boundary, and possible point of failure that you do not control.
That tradeoff has created a visible countercurrent: packages and runtimes that
treat fewer dependencies as a feature. Chalk,
one of the most widely used packages in the JavaScript ecosystem, highlights
that it has no dependencies. Every module in the
Deno Standard Library is
reviewed by the Deno team and has no third-party dependencies. Meanwhile,
platforms keep absorbing common needs: Node.js made both
fetch and its
test runner stable, allowing many projects
to remove packages they once needed.
A zero-dependency package is not automatically better. Its own code can still be buggy or compromised, and rebuilding a mature library badly is worse than depending on it. The useful idea is that dependency count is a design choice, not an inevitability. Each edge removed from a dependency graph is one fewer external failure that can block the software.
The same idea is even more valuable when the nodes in the graph are people.
The company as a dependency graph
Imagine each employee as a package. A dependency exists whenever that person cannot move a task forward until somebody else supplies information, makes a decision, grants access, or performs the next step.
Those edges are more expensive in a company than in a program. Software interfaces can be specified, tested thousands of times, pinned to a version, and run again under identical conditions. Human interfaces cannot. People have competing priorities, incomplete context, different interpretations, sick days, and meetings. Even a responsible colleague may become a blocker simply because their queue is full.
The problem is not collaboration. The problem is a compulsory handoff: work that must stop at a functional boundary even when the person holding it could reasonably cross that boundary.
A zero-dependency employee can take an important task from question to a verified artifact without waiting for another function. They still seek feedback, respect controls, and use specialists when the stakes demand it. But they ask for input to improve the work, not for permission or labor merely to begin it.
In practice, that kind of employee has several habits:
- They can obtain and validate the information they need.
- They understand the systems adjacent to their formal role.
- They make reversible decisions within clear guardrails.
- They produce a draft, analysis, prototype, or pull request before escalating.
- They hand specialists something concrete to review instead of an open-ended request to do the work for them.
Consider a product manager investigating a drop in activation. A conventional workflow might require a data engineer to write a query, an engineer to explain the event model, and an executive to decide whether the result matters. Each handoff introduces a queue.
A zero-dependency product manager can query the database safely, inspect the relevant schema or code path, connect the result to the business, and recommend an action. If the fix is straightforward and the engineering team is severely backlogged, they can open a focused pull request with tests for the engineering team to review. They do not need to be the best data engineer or software engineer in the company. They need enough SQL, system design, coding, and business judgment to keep the work moving.
The same standard applies to leadership. A zero-dependency COO should be able to preserve operating continuity when the engineering team is severely backlogged: communicate with customers, employees, shareholders, and other stakeholders; understand the product and engineering tradeoffs; make decisions within delegated authority; and step into customer service when that is where the company needs help. The COO does not permanently become every other role. They make sure the company does not freeze when one role is overloaded.
Reducing these dependencies changes more than speed. It reduces translation loss because fewer people reinterpret the problem. It improves resilience to absences and overloaded teams. It gives specialists smaller, better-defined review requests. It also improves escalation: the person asking for help has already gathered evidence, tried the obvious paths, and identified the exact decision they cannot make alone.
Autonomy is a system, not a personality trait
Companies cannot demand zero-dependency behavior while centralizing every permission, tool, and piece of context. An employee cannot query data they cannot access, open a pull request without a development environment, or make a decision when nobody has defined their authority.
Management has to build the conditions for independence:
- Give people direct access to the systems and data appropriate to their risk level.
- Document context and decisions so knowledge does not require a meeting to retrieve.
- Define guardrails that separate reversible actions from changes requiring review.
- Teach adjacent skills and reward people for crossing functions to finish an outcome.
- Keep review available without making another team responsible for producing the first draft.
Zero dependency must not become an excuse for hero culture, access without controls, or knowledge hoarding. High-risk and irreversible actions should retain independent review. Work should be documented so that the versatile employee does not become a new single point of failure. The target is not zero communication. It is near-zero waiting.
Hire for small-company throughput
This model matters most in startups and small organizations. A large company can afford deep specialization and enough staffing to keep every queue moving. A startup cannot. When ten people divide themselves into ten narrow functions, they create the coordination costs of a much larger organization without its redundancy.
Small companies should therefore seek people with depth in one area and useful competence across several others: product managers who can query and code, engineers who can talk to customers, operators who understand product and finance, and executives who can enter the operational details when necessary.
Hiring for this quality means looking beyond titles. Ask candidates about an outcome they delivered across functional boundaries. Give them an ambiguous work sample and see whether they find the data, learn the unfamiliar part, and produce something reviewable. Look for curiosity, tool fluency, business judgment, and a record of closing loops—not just coordinating them.
The best early-stage employees do not eliminate teamwork. They make teamwork more powerful because collaboration becomes a choice made for quality rather than a prerequisite for motion.
A zero-dependency company is not a collection of isolated generalists. It is a company designed so that no ordinary dependency link can bring important work to a halt. Hire people who can cross the links, give them the access and guardrails to do it, and let specialists improve work that is already moving.