I'm going back to writing code by hand

Here is k10s: https://github.com/shvbsle/k10s/tree/archive/go-v0.4.0 234 commits. ~30 weekends. Built entirely on vibe-coded sessions with Claude, whenever my tokens lasted long enough to ship something. I'm archiving my TUI tool and rewriting it from scratch. k10s started as a GPU-aware Kubernetes dashboard (and my first foray into building something serious with AI). Think k9s but built for the people running NVIDIA clusters, people who actually care about GPU utilization, DCGM metrics, and which nodes are sitting idle burning $32/hr. I built it in Go with Bubble Tea [1] and it worked. I learned over these 7 months is worth more than the 1690 lines of model.go I'm throwing away. And I think anyone doing serious vibe-coding can benefit from this, because this part doesn't surface much (I feel it gets buried under the demo reels and the velocity wins). tl;dr: AI writes features, not architecture. The longer you let it drive without constraints, the worse the wreckage gets. The velocity makes you think you're winning right up until the moment everything collapses simultaneously. I started k10s in late September 2025. The first few weeks were magic. I'd prompt Claude with "add a pods view with live updates" and boom, it worked. Resource list views, namespace filtering, log streaming, describe panels, keyboard navigation. Each feature landed clean because the project was small enough that the AI could hold the whole thing in context. The basic k9s clone took maybe 3 weekends. Resource views for pods, nodes, deployments, services. A command palette. Watch-based live updates. Vim keybindings. All working, all vibe-coded in single sessions. I was building at maybe 10x my normal speed and it felt incredible. The whole reason k10s exists is the GPU fleet view. A dedicated screen that shows you every node's GPU allocation, utilization from DCGM, temperature, power draw, memory. Not buried in kubectl describe node output, but right there in a purpose-built table with color-coded status. Idle nodes in yellow. Busy in green. Saturated in red. And Claude one-shot it. I prompted for the fleet view, it generated the FleetView struct, the tab filtering (GPU/CPU/All), the custom rendering with allocation bars. It looked beautiful. I was riding the high. Then I typed :rs pods to switch back to the pods view. Nothing rendered. The table was empty. Live updates had stopped. I switched to nodes, it showed stale data from the fleet view's filter. I went back to fleet, the tab counts were wrong. This is the title of the blog post. This is where I intervened for the first time. For 7 months I'd been prompting and shipping without ever sitting down and actually reading the code Claude wrote. I'd look at the diff, verify it compiled, test the happy path, move on. But now something was fundamentally broken and I couldn't just prompt my way out of it. So I sat down and read model.go. All 1690 lines. I was horrified. Here's what it looked like. One struct to rule them all: type Model struct { // 3rd party UI components table table.Model paginator paginator.Model commandInput textinput.Model help help.Model // cluster info and state k8sClient *k8s.Client currentGVR schema.GroupVersionResource resourceWatcher watch.Interface resources []k8s.OrderedResourceFields listOptions metav1.ListOptions clusterInfo *k8s.ClusterInfo logLines []k8s.LogLine describeContent string currentNamespace string navigationHistory *NavigationHistory logView *LogViewState describeView *DescribeViewState viewMode ViewMode viewWidth int viewHeight int err error pluginRegistry *plugins.Registry helpModal *HelpModal describeViewport *DescribeViewport logViewport *LogViewport logStreamCancel func() logLinesChan <-chan k8s.LogLine horizontalOffset int mouse *MouseHandler fleetView *FleetView creationTimes []time.Time allResources []k8s.OrderedResourceFields // fleet s unfiltered set allCreationTimes []time.Time // fleet s timestamps rawObjects []unstructured.Unstructured ageColumnIndex int // ... } UI widgets. K8s client. Per-view state for logs, describe, fleet. Navigation history. Caching. Mouse handling. All in one struct. And the Update() method was a 500-line function dispatching on msg.(type) with 110 switch/case branches. This is the moment I stopped vibe-coding and started thinking. Here's what I extracted from 7 months of watching AI generate a codebase that slowly ate itself. Each of these is something I did wrong, why it happens with AI-assisted coding, and what you should actually put in your CLAUDE.md or agents.md to prevent it. Tenet 1: AI builds features, not architecture. Every time I prompted Claude for a feature, it delivered. Perfectly. The fleet view worked on the first try. Log streaming worked. Mouse support worked. The problem is that each feature was implemented in the context of "make this work right now" without any awareness of the 49 other features sharing the same state. Here's what the resourcesLoadedMsg handler looks

I'm going back to writing code by hand

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