What Search Doesn’t Tell You

Search and AI return answers instantly. But the debates and iterations behind them have vanished. Through a thought experiment borrowing from GitHub, we explore the value of dialogue.

── Answers Have Become Too Fast

Enter a question into a search engine and an answer — or something resembling one — appears in under a second. Ask AI and a polished response generates instantly. We live in the most answer-accessible era in human history.

But what happened on the journey to those answers? Who considered which perspectives, what debates occurred, what was adopted and what was discarded? This process remains hidden behind optimized results.

If the dialogue leading to an answer holds more value than the answer itself, we may be surrendering that value in exchange for efficiency.

What does this dialogue actually look like? Consider one question as an example.

── Why Is the Sky Blue?

“Why is the sky blue?”

A physics graduate student answers first: 
“It’s due to Rayleigh scattering. When sunlight scatters through atmospheric molecules, shorter wavelength blue light scatters more strongly.”

A high school student asks more: 
“So is a red sunset the same principle? Where does the blue light go?”

An earth science teacher adds explanation: 
“Same principle, but at sunset, sunlight travels a longer distance through the atmosphere. Blue light scatters too much along the way to reach us. Only red light remains visible.”

A linguistics student adds context: 
“The expression ‘blue’ itself is cultural. Japanese ‘ao’ once included green, and we still say ‘ao signal’ for green traffic lights. Russian treats light blue and blue as distinct basic colors. Research suggests language influences color perception.”

What began as a physics explanation evolved into multifaceted understanding spanning education, culture, and language.

The final answer isn’t what matters here. Who spoke when, which perspectives expanded the discussion — the dialogue itself holds value distinct from the answer.

── Borrowing from GitHub

Let’s conduct a thought experiment.

In software development, GitHub serves as a platform where developers worldwide collaborate on code. What’s compelling is that it preserves not just current code, but who proposed what when, which debates occurred, what was adopted and what was rejected. The trial and error remains visible alongside the final product.

What if we applied this mechanism not to code, but to answers? Imagine a site where entering a question in the search box creates a discussion space — an Issue — around that question.

Physicists provide scientific explanations, linguists offer cultural perspectives. Discussion deepens through threaded conversations, with reactions like 👍 or 💡 sharing moments of resonance and discovery.

Eventually someone proposes an answer — a Pull Request — drawing from the discussion. “This phrasing is too technical,” “This analogy is easier to understand” — feedback accumulates through reviews, refining the answer. Finally, trusted community maintainers integrate it through Merge, completing one answer.

But what matters most comes after. 
Rejected proposals and divergent discussions all remain. The possibility that other answers could have existed stays accessible.

── Why Process Remains Hidden

Q&A sites have “best answers.” Social media has likes. Search engines have rankings. All mechanisms designed to efficiently deliver the best answer.

While these designs excel, they simultaneously discard something. Unselected answers, divergent discussions, minority perspectives — they become buried as things unchosen, rendered invisible.

What makes GitHub compelling is that discussions and closed Pull Requests all remain as history. Rejected options stay accessible. This transparency supports not just code quality, but developer learning.

This thought experiment asks whether the same approach could apply to knowledge itself.

Discussion (Issue) → Proposal (Pull Request) → Review → Integration (Merge)

If this process became fully visible and version-controlled, 
answers wouldn’t remain fixed but would update with new insights. 
Past versions and rejected proposals would all persist as history.

Just as Wikipedia evolves encyclopedic knowledge and GitHub improves code, answers would continuously improve and grow. 
What matters is that every discussion, every change history, remains transparently preserved.

── The Choice Not to Rush

We face countless questions daily. Search engines and AI provide instant answers to most. This is remarkable.

Not every question requires time. Tomorrow’s weather, the nearest station, tonight’s recipe — countless situations demand efficient answers.

What GitHub-like mechanisms teach us is that answers and the process of reaching them are distinct. The latter holds value different from the former.

For questions that truly matter to you, perhaps a different approach exists. Talk with someone before searching for answers. Don’t rush to conclusions — savor the thinking process itself.

Dialogue holds richness distinct from answers themselves. When people from different positions engage the same question, unexpected scientific insights intersect with cultural perspectives, and expert knowledge reacts with simple curiosity. Witnessing this process teaches us not just answers, but ways of thinking.

Engaging with this richness may offer wisdom for those of us living in an age when answers come too fast.