🌳I Know the Paths — But Not Which One to Walk

A tale of overthinking, clarity, and the two sacred ways of deciding — where a living forest becomes the first lesson in Graph Traversal.

Characters: Arjun, Guru Bodhi, Vana Dev (Forest Spirit), Woodland Birds · Arc: Beginner · Pattern: Graphs & Tree Traversal (BFS & DFS)

📜 Sutra of Dawn — The Forest of Too Many Choices

The sun had barely risen when Arjun and Guru Bodhi stepped into the Forest of Decisions. Light poured through the branches like molten gold. Every path split into two more, and those split again, until the forest floor looked like a cracked mirror of trails.

Somewhere between the roots and the mist, hundreds of delicate paths twisted away. They were all walkable, all inviting, all slightly wrong.

Arjun's shoulders sagged. "This is exactly how my head feels, Guruji. So many options, so many 'maybe' paths. I know a lot of things, but I don't know which thing to do next."

The Guru smiled, staff resting lightly on the ground. "Then this forest is the perfect teacher."

📜 Sutra of the Question — Where Trouble Truly Starts

"Guruji," Arjun began, "this isn't just about a forest. My life is like this."

He kicked a pebble off the trail. "At work I have ten different projects I could start. At home there are five different skills I want to learn. I read threads, watch talks, collect advice… and spiral. I know a hundred possible paths, but not which one to walk now."

Rustling leaves answered him. On the overhead branches, the Woodland Birds shifted and chattered like a noisy product meeting.

"Ship the feature that grows numbers fastest!" chirped one bright bird.

"No — invest in deep architecture first!" argued another.

"Explore every idea before you commit!" shouted a third.

Arjun rubbed his temples. "That's exactly my problem. Everyone has a different 'must do now'. I end up wandering in circles."

📜 Sutra of Confusion — The Curse of Overthinking

To prove his point, Arjun started walking. At every fork he stopped, stared, imagined all outcomes, and then picked one at random. A few turns later he doubted himself, backtracked, then dove down a new branch "just to see".

After a long while, the group arrived back at a familiar rock.

This is like choosing a career, a city, or a life partner. The problem isn't lack of options — it's the paralysis of fearing you'll choose wrongly. You circle back to where you started, unchanged, while the paths grew longer.

Vana Dev knelt and drew small circles on the soil, joining them carefully with lines. "The forest is not chaos," they said. "It is a graph."

📜 Sutra of Clarity — The Two Sacred Ways of Deciding

Guru Bodhi tapped two of the drawn circles with his staff. "Call this starting place root. Call the important decision points nodes. Each path between them is an edge."

"There are two sacred ways to explore such a forest," he continued. "Both are correct. They simply answer different questions."

DFS is deep thinking. BFS is broad thinking. Both are correct — but for different questions.

Arjun nodded slowly. "So if I'm choosing the next task to ship soon, I should think like BFS — scan all near-term options and pick the best among them."

"And if I'm exploring a long-term bet — like a new product line or a PhD topic — I should think like DFS: walk one branch deeply enough to understand it before hopping to the next."

🧠 The Forest of Nodes — Algorithm Scroll

We'll model a small corner of the forest as a graph. Each clearing is a node; each trail is an undirected edge. We store this in an adjacency list.

Python: Adjacency List Example

graph = {
    "root":      ["market", "studio"],
    "market":    ["root", "office"],
    "studio":    ["root", "lab"],
    "office":    ["market", "lab"],
    "lab":       ["studio", "office"]
}

Now we can traverse this forest with BFS or DFS.

Python: Breadth-First Search (BFS)

from collections import deque

def bfs(start, graph):
    """Visit nodes in increasing distance from `start`."""
    visited = set([start])
    order   = []
    queue   = deque([start])

    while queue:
        node = queue.popleft()
        order.append(node)

        for nbr in graph[node]:
            if nbr not in visited:
                visited.add(nbr)
                queue.append(nbr)

    return order

Python: Depth-First Search (DFS)

def dfs(start, graph):
    """Explore one path fully before backtracking."""
    visited = set()
    order   = []

    def visit(node):
        visited.add(node)
        order.append(node)

        for nbr in graph[node]:
            if nbr not in visited:
                visit(nbr)

    visit(start)
    return order

Complexity

• Time: O(V + E) — we touch every node and edge once.
• Space (BFS queue / DFS stack): O(V) in the worst case.

Guru: "The algorithms are simple, Arjun. The hard part is choosing which question you're answering: 'What's the nearest good option?' or 'What happens if I follow this direction all the way down?'"

📜 Sutra of Wisdom — How to Choose the Way

As the sun climbed higher, the forest of paths seemed less threatening. The same trails were there, but they now had labels.

• For near-term, "what should I do this week?" decisions — Arjun imagined running a quick BFS across nearby options, comparing only what was one or two steps away.
• For long-term, "what could this become if I commit?" decisions — he imagined a deliberate DFS, following one promising branch deeply before judging it.

Vana Dev watched him thoughtfully. "You were never lost because you lacked paths," they said. "You were lost because you lacked a strategy for moving among them."