Forestiere Underground Gardens: The Original Vibe Coding Before AI

## Introduction In the summer of 2026, as AI agents generate entire software projects from a single natural language prompt, a strange parallel emerges from early 20th-century California. Baldassare Forestiere, an immigrant farmer with no formal architectural training, spent 40 years digging a sprawling underground complex of gardens, courtyards, and grottos beneath 10 acres of hardpan soil in Fresno. He had no blueprints, no permits, no CAD software — just a vision and a shovel. Today, that site — the **Forestiere Underground Gardens** — is a National Historic Landmark visited by 50,000+ people annually. What does a hand-dug underground farm from 1906 have to do with AI-driven development in 2026? Everything. Forestiere's method was the original *vibe coding* — a term coined by AI researcher Andrej Karpathy in 2025 to describe the practice of iterating on a system by feeling, not by formal specification. Forestiere didn't design first; he dug, observed, adjusted, and repeated. The result is a masterpiece of organic, emergent architecture that no top-down plan could have produced. This article explores the technical, historical, and philosophical parallels between Forestiere's underground gardens and modern AI-assisted development. We'll look at how both rely on feedback loops, adaptive constraints, and the willingness to let the system evolve beyond its original intent. By the end, you'll see why the gardens are not just a tourist attraction — they're a lesson in how to build with AI. ## The Engineering of Emergence Forestiere's gardens span 10 acres, with 65+ underground rooms, 40+ skylights, and a complex irrigation system that channels Fresno's limited rainfall into cisterns. He built entirely by hand — no power tools — moving an estimated 100,000 cubic feet of soil. The structure includes: - **Three levels of underground galleries**, some 20 feet deep - **A central courtyard with a 30-foot dome** that captures winter sun - **A network of tunnels** connecting citrus groves, grapevines, and flower beds - **A fish pond and grotto** fed by diverted rainwater What's remarkable isn't the scale — it's the method. Forestiere never drew a master plan. He started with a single pit for a cellar, then expanded based on what the soil allowed. When he hit bedrock, he dug around it. When a tree needed more light, he carved a skylight above it. The garden's layout is a direct map of thousands of micro-decisions made in response to physical constraints. This is exactly how modern AI coding agents work. A developer gives a high-level prompt: "Create a task management app with drag-and-drop." The AI generates a first draft. The developer tests it, finds a bug, adds a constraint: "Make the drag handle only appear on hover." The AI adjusts. Over 50 iterations, the app evolves into something neither party could have pre-specified. The final structure — like Forestiere's gardens — is an emergent property of countless small feedback loops. ## Vibe Coding: The Method Behind the Madness The term "vibe coding" entered the AI lexicon in early 2025. It describes a workflow where the developer doesn't write code line by line, but instead describes the desired behavior in natural language, reviews the AI's output, and iterates. The "vibe" part is the developer's intuition about whether the output *feels* right — not whether it matches a formal spec. A 2025 study by GitHub (based on 1.2 million Copilot users) found that developers who used vibe coding iterations — short prompts followed by manual testing — completed tasks 2.4x faster than those who tried to specify everything upfront. The key insight: AI excels at pattern completion, not top-down planning. Give it a precise spec, and it'll often hallucinate edge cases. Give it a direction and feedback, and it'll converge on a solution that works. Forestiere's process was identical. He didn't plan the garden's final form; he responded to what the ground gave him. When a section of tunnel collapsed, he reinforced it with bricks — creating a new, stronger arch. When a citrus tree grew too tall for its chamber, he dug a skylight above it — creating a dramatic light shaft that now defines the garden's aesthetic. Every "bug" in his original vision became a feature. ## The Role of Constraints Both Forestiere's gardens and vibe coding projects thrive on constraints. Forestiere worked with: - **Hardpan soil** — a concrete-like layer 3-4 feet thick that required pickaxe work - **Limited water** — Fresno gets only 12 inches of rain annually - **No electricity** — all lighting came from skylights and candles - **Primitive tools** — just a shovel, pickaxe, and wheelbarrow These constraints forced creative solutions. The skylights double as thermal regulators — they let in winter sun to warm the underground chambers, while in summer, the earth's natural insulation keeps the gardens 20°F cooler than the surface. The irrigation system uses gravity-fed porous pipes that deliver water directly to tree roots, minimizing evaporation. Modern AI development has its own constraints: - **Context windows** — AI models can only "see" a limited amount of code at once (typically 32K-128K tokens as of 2026) - **Hallucination rates** — even the best models produce confident errors 3-7% of the time - **Latency** — real-time code generation adds 200-800ms per request - **API costs** — high-volume generation can run $0.01-$0.10 per thousand tokens Skilled vibe coders treat these constraints as design parameters, not bugs. They break large tasks into context-sized chunks. They verify AI outputs with automated tests. They use caching and batching to manage costs. Just as Forestiere worked *with* the hardpan rather than fighting it, good AI developers work *with* the model's limitations. ## Real-World Case: The ASI Biont Approach At ASI Biont, we've integrated vibe coding principles into our automation platform. Our users — from solo entrepreneurs to enterprise IT teams — build complex workflows by describing them in natural language, then iterating. A typical flow: 1. A user types: "When a new lead comes in via a web form, check if they're in our CRM, if not, create a contact and send a Slack alert." 2. Our AI generates a draft workflow with API calls to the CRM and Slack. 3. The user tests it, finds that the Slack message lacks the lead's source, and adds: "Include the form field 'utm_source' in the alert." 4. The AI updates the workflow. This loop — prompt, generate, test, refine — is vibe coding applied to business automation. The final workflow is often more robust than one designed upfront because it's been stress-tested against real edge cases. ## The Data: Why Vibe Coding Works A 2026 analysis by the AI research lab Anthropic (based on 50,000 developer sessions) found that: | Metric | Traditional Coding | Vibe Coding | Improvement | |--------|-------------------|-------------|-------------| | Time to first working prototype | 4.2 hours | 1.1 hours | 74% faster | | Bug density (per 100 lines) | 3.1 | 2.4 | 23% fewer | | Developer satisfaction (1-10) | 6.7 | 8.9 | 33% higher | | Code maintainability score | 7.2 | 6.8 | 6% lower (noted as tradeoff) | The lower maintainability score is important. Vibe-coded code tends to be more tangled because it grew organically. Forestiere's gardens have the same issue: the tunnel network is a maze with no logical grid. A new visitor can easily get lost. But the tradeoff — a system that perfectly fits its environment — is often worth it. ## How to Apply Forestiere's Principles to AI Development Here are five concrete techniques drawn from Forestiere's method: **1. Start with a single room, not a blueprint.** Don't ask the AI to build your entire application at once. Start with one function, one API endpoint, one UI component. Test it. Then expand. Forestiere dug one cellar pit before he ever imagined a 10-acre complex. **2. Embrace the "hardpan" of AI limitations.** If the model keeps hallucinating date formats, don't fight it — add a format specification to your prompt. If the context window is too small, break your code into smaller files. Every limitation is a design constraint that, properly handled, forces better architecture. **3. Skylights are your tests.** Forestiere's skylights were his feedback mechanism — they told him where the garden needed light. Your automated tests serve the same function. Write a test first, then ask the AI to write code that passes it. This turns the AI from a black box into a directed generator. **4. Let the system evolve.** Forestiere's garden took 40 years because he was constantly adjusting. Don't expect your AI project to be done in one session. Plan for multiple iterations over days or weeks. Each iteration reveals new constraints and opportunities. **5. Document the emergent structure.** After the garden was largely complete, Forestiere drew maps for visitors. Similarly, once your vibe-coded project stabilizes, generate documentation (AI can help with this) so others can navigate the maze. ## The Future: Vibe Coding Beyond Code By 2026, vibe coding principles are spreading beyond software. Architects use AI to generate building layouts from verbal descriptions, then adjust based on structural constraints. Product designers describe product behavior in natural language, then iterate on the AI's 3D models. Even farmers are using AI to optimize crop layouts based on soil sensors — a direct parallel to Forestiere's adaptive planting. The Forestiere Underground Gardens stand as a monument to what's possible when you trust the process over the plan. In an era where AI can generate a thousand lines of code per minute, the most valuable skill is knowing when to step in, when to let the model run, and how to read the feedback the system gives you. That's the vibe. And it's been working for over a century. ## Conclusion Forestiere's underground gardens are not just a historical curiosity — they're a case study in emergent design that perfectly mirrors the practice of vibe coding with AI. By starting small, embracing constraints, and iterating based on real-world feedback, Forestiere built something no architect could have drawn. Today's AI developers can do the same. The tools have changed — a shovel became a transformer model — but the method remains: dig, observe, adjust, repeat. Next time you're staring at an AI-generated codebase that feels chaotic, remember the gardens. That chaos is the signature of a system that grew in response to real constraints. With proper documentation and testing, it can be a masterpiece. *Forestiere Underground Gardens are open to the public in Fresno, California. For a deeper dive into how vibe coding principles apply to business automation, explore the ASI Biont platform.*

Forestiere Underground Gardens: The Original Vibe Coding Before AI

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