I’ve been reflecting on a recurring story in R&D: the “underdog turnaround.” It begins with Project A, which many people—senior leaders and technical leads included—doubt will be useful or even feasible. Yet despite the skepticism and resistance, the project begins to succeed. Before long, Project A is on the critical path.

In hindsight, once the success is known, people look back at Project A and say, “Of course—it’s obviously the right thing to do.” But why do we feel the need to express disbelief at the beginning? Often, constraints force us to pick and choose rather than pursue multiple options in parallel, so we need an argument for doing B instead of A. Sometimes, though, the reason is simpler: we have a technical intuition—a hunch—that differs from what is being proposed, so we automatically disagree.

I’ve found that expressing strong disbelief at the beginning of a project usually does more harm than good, unless that disbelief is grounded in analysis, knowledge, and facts. The harm of uninformed early disbelief includes:

  • It hurts our credibility. If we express disbelief assertively and turn out to be wrong, people will trust our judgment less the next time.
  • It discourages the doers. Early dismissal makes it harder for people to take action, learn, and make progress.
  • It gives the team nothing constructive to act on. Disbelief without an alternative is just resistance.

I’ve been reflecting on how to raise concerns and ask hard questions without turning uncertainty into assertive disbelief. I haven’t found a complete formula, but a few subtle distinctions seem useful.

Absence of Evidence ≠ Evidence for Disbelief

A common argument for disbelief goes like this:

I don’t believe this will work because I’ve never seen it work before.

This expresses strong disbelief based on very weak—and often invalid—evidence. In reality, one of two situations is usually true:

  1. I’ve seen a great deal of related work in this domain, and none of it has worked. In this case, the concern is better expressed in terms of uncertainty and risk: “Given the outcomes of previous efforts A, B, C, and D, I believe this project has a low probability of success.”
  2. I haven’t seen much related work. Perhaps prior work does not exist, or perhaps I simply don’t know the domain well enough. In that case, it is better not to form a strong opinion—to remain neutral and open to learning.

Knowing What Is Wrong ≠ Knowing What Is Right

There is a subtle form of “informed” disbelief that is based on past failure. On the surface, it sounds compelling:

We failed in the past with Project A. We conducted a comprehensive retrospective and concluded that B is the right approach. Therefore, your proposed solution, C, is wrong.

The logical flaw is the assumption that the solution space contains only one correct answer. The reasoning becomes: A was wrong, therefore B must be right, and therefore C must be wrong.

But proving that A is wrong does not prove that B is right. A’s failure disproves A; it says nothing about the validity of B or C unless C is meaningfully similar to A. A more accurate statement would be:

We know A doesn’t work. We don’t yet know what will work. Our current preferred option is B, and we don’t have an informed opinion on C.

Not Feasible Today ≠ Not Valuable

This distinction is another subtle one. Something that has not been built cannot yet realize its value, so it is easy to infer that something infeasible has no value. The argument often looks like this:

I don’t believe we can build it within the next X months; therefore, it has no value.

This can be correct when the value depends on catching a one-time train: if we miss it, the opportunity is gone forever. That is very real in startups. Miss a critical delivery, a customer need, or the next funding round, and the company may cease to exist.

But this one-time-train assumption is rarely true for cutting-edge innovation funded by long-term investment. The danger of this kind of disbelief is that we keep delaying investment in anything that cannot be completed today. We lose the opportunity to learn and iterate, so the needle of feasibility never moves. Something valuable remains unbuilt until another team—one with firmer belief and the patience to execute—finally builds it and proves us wrong.

The goal is not to eliminate skepticism. It is to detach concern from conviction: be precise about the evidence, distinguish what has failed from what might work, and separate short-term feasibility from long-term value. We can question an idea rigorously without pretending to know more than we do.