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The diagrams

Every idea in the books is drawn before it is described. This is the drawings, one a day, each with the paragraphs that explain it. RSS feed.

Figure 1.1: The terminology fog. The same word lands five different ways, nobody flags the mismatch, and the meeting "agrees" on five different things.

AI

The terminology fog

2026-08-27

Figure 2.1: The family map. AI contains machine learning, which contains deep learning, which contains generative AI, where the LLMs live. The famous names on the right are products wrapped around those models. Later chapters point back to this figure, so dog-ear this page. Confusingly, vendors reuse the same name for the model family and the app: the left box means the models, the right column the apps.

AI

The family map

2026-08-27

Figure 1.1: The demo-to-production gap. The five rows of change are drawn from the Google Developers retrospective on refactoring a monolithic prototype (21 April 2026).

AI Agents

The demo-to-production gap

2026-08-27

Figure 2.1: The agent loop, the anchor schema of this book. A goal enters. Context is assembled, the model decides, your code runs a tool, the observation goes back into context, and the stop condition is checked before the next turn begins. There are exactly two ways out: the model returns an answer with no tool call, or a ceiling is hit. Later chapters zoom into one box each.

AI Agents

The agent loop, the anchor schema of this book

2026-08-27

Figure 1.1: The chat workflow routes every step through you. The agent workflow moves the read-edit-run-check loop inside the tool, and moves you to the review gate.

Claude Code

The chat workflow routes every step through you

2026-08-27

Figure 1.2: Every surface is a different doorway into the same engine. Configuration you write once (CLAUDE.md, settings, MCP servers) applies everywhere.

Claude Code

Every surface is a different doorway into the same engine

2026-08-27

Figure 1.1: The problem Docker solves. Left: the app plus an install guide meets three machines and produces three outcomes. Right: one image, packed with everything the app needs, behaves the same on all three.

Docker

The problem Docker solves

2026-08-27

Figure 2.1: The anchor diagram of this book. On the left, a hypervisor virtualizes the hardware and every VM repeats a full guest operating system, kernel included. On the right, one host kernel is shared by every container, and each container box holds only an app and its libraries, because a container is a process, not a machine. Note where the isolation boundary sits on each side: virtual hardware for VMs, the shared kernel for containers.

Docker

The anchor diagram of this book

2026-08-27

Figure 1.1: Where ElevenLabs sits in your stack. Scripts, app code, and phone calls go in on the left; listeners, users, and callers come out on the right. In between, four product doors open onto the same shared voice models and one credit pool.

ElevenLabs

Where ElevenLabs sits in your stack

2026-08-27

Figure 2.1: The two-stage neural TTS pipeline. Text is cleaned and analyzed, then the acoustic model writes a mel spectrogram and the vocoder converts it into a waveform.

ElevenLabs

The two-stage neural TTS pipeline

2026-08-27

Figure 2.1: Snapshots vs diffs. Other systems store the change per version and replay the chain to rebuild a file; Git stores a full snapshot per commit and lets unchanged files reference the identical previous copy.

Git

Snapshots vs diffs

2026-08-27

Figure 2.2: Centralized vs distributed. A central server hands out thin checkouts and mediates every commit; in Git each clone is a complete repository, so work happens locally and syncing is a separate, explicit step.

Git

Centralized vs distributed

2026-08-27

Figure 3.1. The three trees: work moves forward with add and commit, and back with restore and switch.

Git

The three trees: work moves forward with add and commit, and back with restore and switch

2026-08-27

Figure 1.1: The split. Everything on the left is git and belongs to you. Everything on the right is GitHub and belongs to a service you sign in to. Push and pull are the only bridge.

GitHub

The split

2026-08-27

Figure 1.2: Where is my file right now. Four places, four commands. Every later diagram in this book is a zoom into one part of this one.

GitHub

Where is my file right now

2026-08-27

Figure 2.1: The same question ("help me with my server") lands very differently across the three. Only the autonomous agent keeps state between sessions and can act on its own.

Hermes Agent

The same question ("help me with my server") lands very differently across the three

2026-08-27

Figure 3.1: The learning loop. Run a task, observe success, curate memory or write a skill in the self-improvement review, then reuse on the next run. Every session is also logged losslessly to SQLite (FTS5) and can be pulled back in via session_search.

Hermes Agent

The learning loop

2026-08-27

Figure 4.1: Install to first session, left to right. Steps 1 to 5 take you from a bare machine to a running chat; the startup gate rejects any model under 64,000 tokens of context, and hermes doctor catches problems at any step.

Hermes Agent

Install to first session, left to right

2026-08-27

Figure 1.1: The Kimi Code stack. Open-weight models at the bottom, one membership and dual-protocol API in the middle, and many surfaces on top. You pick the surface; the subscription and models stay the same.

Kimi Code

The Kimi Code stack

2026-08-27

Figure 2.1: The map of the machine. One session sits at the center, drawing a model from the engine bay on the left and acting on your repo through the guards on the right. Results loop back into the context, sub-agent satellites work in contexts of their own, and every request spends from the quota gauges below. Later chapters zoom into one region at a time.

Kimi Code

The map of the machine

2026-08-27

Figure 1.1: The loop. You describe, the agent edits a real codebase, you check the preview, and you publish when ready. Credits meter the agent's work, Git sync keeps an off-platform copy, and the backend is generated alongside the app. This is the book's master schema.

Lovable

The loop

2026-08-27

Figure 1.2: The promise and the practice. The left panel is what one prompt genuinely delivers on day one. The right panel is what this book adds before other people depend on the result. Neither panel cancels the other.

Lovable

The promise and the practice

2026-08-27

Figure 1.1: Where n8n sits. Prices and build estimates are the figures published on n8n.io/pricing and by NodeSparks, both read 2026-08-21. Agent frameworks sit off the diagonal on purpose: they raise your effort without handing you more control over what happens.

n8n

Where n8n sits

2026-08-27

Figure 2.1: The items pipeline, the anchor schema of this book. A trigger emits an array of three items. Every connection carries that array, never a bare record. Each node runs its configured operation once per item and outputs new items. The highlighted item 2 keeps its identity the whole way and links back, step by step, to the item that produced it.

n8n

The items pipeline, the anchor schema of this book

2026-08-27

Figure 1.1: Four years of that membership, one dot per month. On the left, the months I paid: all of them. On the right, the months I set foot inside even once: a handful, and they clustered after the New Year. Reconstructed from memory, so read the shape rather than the exact count.

The +1 Method

Four years of that membership, one dot per month

2026-08-27

Figure 2.1: The same six months, two ways. Motivation (dashed) spikes far above anything the +1 line asks for, then falls to the floor and stays there through the grey months. The +1 line (thick) never has a hard day and never has a day off, and by day 180 it is doing more than the spike ever did.

The +1 Method

The same six months, two ways

2026-08-27

Figure 1.1: Filtering vs verification. The 2015 funnel chooses from a pile of real CVs. The 2026 funnel faces a partly synthetic pile, so every stage carries a verification gate before taste matters again.

Tech Hiring

Filtering vs verification

2026-08-27

Figure 2.1: The Full Stack Hiring Funnel (the author's framework). Ten stages read clockwise around the ring, in three zones: TOFU (attraction), MOFU (your process), BOFU (keep and grow). The dashed arrows are what makes it a loop: advocacy and content flow from BOFU back into TOFU, and a respectful rejection returns the candidate to Awareness instead of losing them. Chapters 6, 8, 12, and 13 each zoom into a piece of this drawing, so dog-ear this page.

Tech Hiring

The Full Stack Hiring Funnel (the author's framework)

2026-08-27

Figure 1.1: The missed-call problem, drawn as money leaving. The top half is where an unanswered call goes. The bottom half is what the same 250 minutes costs on the three routes a business can actually choose between.

Vapi

The missed-call problem, drawn as money leaving

2026-08-27

Figure 1.2: The three-hop pipeline. Audio becomes text, text becomes a reply, the reply becomes audio, and the loop closes back on the caller. Every architecture diagram in the rest of this book is a zoom into one box on this track.

Vapi

The three-hop pipeline

2026-08-27