antidrift/docs/superpowers/specs/2026-05-31-go-focus-os-design.md

AntiDrift Go Reimagining — Design

Date: 2026-05-31

Purpose

AntiDrift is being reimagined from its current Rust implementation (~7,500 lines) into Go, to become the user's focus operating system on the computer: fast, good-looking, and deeply integrated with AI from the start.

This is not a faithful 1:1 port. The existing domain model and the commitment-os-design.md spec remain the north star. The Rust code is a reference, not a thing to replicate line-for-line. The move to Go is an opportunity to shed incidental complexity — most notably the token-heavy event-log replay/revalidation design — while preserving what is genuinely valuable.

Why Go, why now

• Token efficiency for AI-assisted development. The current pain is not runtime cost; it is that any AI edit to the core must load session.rs (3,475 lines, ~80% replay-validation logic and its tests). Go's smaller idioms plus a redesigned, smaller core directly reduce the context any change requires.
• Predictable LLM codegen. Go's rigid syntax produces functional code on the first pass with fewer correction loops.
• Runtime fit. Concurrency and local HTTP serving are first-class, which suits a long-running focus daemon that also talks to AI.

What Carries Over vs. What Changes

Preserved (high value, ports cleanly):

• The domain model: Commitment, PolicySnapshot, RuntimeState, CommitmentState, AllowedContext, EnforcementLevel.
• The pure runtime/commitment state machines (state_machine.rs) — a near 1:1 port.
• The commitment-os-design.md spec as the conceptual foundation, including "no unchosen transitions" and the staged threat model.
• Hash-chained tamper evidence — but relocated to the audit log only.

Reimagined:

• Persistence. Replace replay-everything-and-revalidate-on-startup with an in-memory state-of-truth, a persisted snapshot, and an append-only audit log. This removes roughly 3,000 lines (the bulk of session.rs).
• UI. Replace the ratatui TUI with a local web app (Gin backend + browser). This is the surface that must "look good."
• AI. AI is a first-class participant from the start, not a later add-on.

Deferred for v1:

• The AI reviewer role (session-end reflection). The three live roles ship first.
• Privileged enforcement (guardian, IPC, nftables, delayed admin) — same Stage 2 boundary as the original spec.

Process Model

A single Go binary, antidriftd, runs as a local daemon and owns all state. The browser is its face.

┌─────────────────────────────────────────┐
│  antidriftd (one Go process)             │
│                                          │
│  web (Gin)  ──HTTP + SSE──▶  browser UI  │
│     │                                    │
│  session ── statemachine ── domain       │
│     │                                    │
│  store (snapshot + audit log)            │
│  evidence (xdotool/X11)                  │
│  ai (CLI backend, async workers)         │
└─────────────────────────────────────────┘

• The daemon holds live state in memory as the single source of truth.
• It persists a snapshot on every state change (crash/restart recovery).
• It appends every significant event to an append-only audit log (the tamper-evident, hash-chained trail — for audit and later review, not for state reconstruction).
• The browser is stateless: it renders what the daemon pushes over Server-Sent Events (SSE) and POSTs user actions back. No business logic in the browser.

Why snapshot instead of replay

The original Rust design reconstructs all state by replaying the entire event log on startup and re-validating every transition, with a dedicated test per illegal sequence. That is correct and tamper-aware, but it is the single largest source of code and token weight. A snapshot of current state plus an append-only audit trail gives the same recoverability and keeps tamper evidence on the log, at a fraction of the code. State-machine correctness is still enforced — by the pure transition functions at the point of transition, tested directly — just not re-litigated on every startup.

Architecture: Ports Around a Decision Core

AntiDrift is a focus brain: a decision core surrounded by pluggable interfaces (ports) to the outside world. This is a ports-and-adapters (hexagonal) architecture, and it is the organizing principle the whole system grows along. New capability is almost always "a new port + adapter," not a change to the core.

The core is layered, and the layering is load-bearing:

• Skeleton — deterministic, no I/O (domain + statemachine). The rails. Owns what moves are legal. The original spec's safety property, "no unchosen transitions," lives here: the system can only ever be in a legal state, reached by a legal move.
• Nervous system — the orchestrator (session.Controller). The single hub. Holds the in-memory state-of-truth, routes signals between ports and the skeleton, persists snapshots, appends to the audit log, and broadcasts. Everything connects through here.
• Cortex — the advisor (the LLM, via the ai port). Powerful judgment at the decision points the state machine exposes — sharpen this commitment, is this window drift, nudge me. It informs and proposes; it can never force an illegal transition. The LLM is the most powerful adapter, not the kernel.

"The brain" is all three together. Critically, the state machine — not the LLM — owns transitions; the LLM acts only within the rails the skeleton enforces.

Ports

Each port is a small Go interface with one real adapter (and a fake for tests).

Port	Interface	"Answers"	Adapter(s)	Milestone
Activity	evidence.Source	What am I doing right now?	X11 / xgbutil (was xdotool)	M1
Advisor	ai.Assistant (Coach/JudgeDrift/Nudge)	What's the smart call here?	claude/codex CLI	M2–M3
Tasks	tasks.Provider	What should I be doing?	Amazing Marvin (existing ampy + marvin MCP)	deferred (M5)
Knowledge	knowledge.Source	Who am I; what are my priorities?	PKM / files	deferred (M6)
Enforcement	enforce.Guard	Make drift cost something	window-minimize now (legacy minimize_other); nftables/guardian later	deferred (M7)
UI	web	Show me; take my input	Gin + browser over SSE	M0, ongoing

Persistence (store) is infrastructure shared by the orchestrator, not a port.

The tasks, knowledge, and enforce ports are named now but built later — defining them keeps the architecture coherent without expanding near-term scope. We resist designing their interfaces in detail until the milestone that builds them, to avoid speculative abstraction (YAGNI). M1 ships the first real port end-to-end (evidence.Source + X11 adapter + fake), establishing the pattern every later port copies.

Package Layout

Package	Ports from	Size	Purpose
domain	domain.rs	small	Commitment, PolicySnapshot, runtime/commitment states, AllowedContext, EnforcementLevel, validation
statemachine	state_machine.rs	small	Pure transition functions (1:1 port)
session	reimagined session.rs	medium	In-memory controller; drives transitions, snapshots, audit appends; no replay validation
store	event_log.rs	small	Snapshot file (current state) + append-only hash-chained audit JSONL
evidence	window/* + context.rs	small	Active-window snapshot (xdotool/X11), evidence health, allowed-context matching
ai	new	small	Coach / JudgeDrift / Nudge behind one interface; CLI backend
web	new (replaces TUI)	medium	Gin routes, SSE stream, static browser UI
tasks	new (deferred, M5)	small	Provider port over current to-do items; Amazing Marvin adapter
knowledge	new (deferred, M6)	small	Source port over personal priorities / about-me context
enforce	window/* (minimize)	small	Guard port; make drift cost something (window-minimize → nftables/guardian)

Design constraint: every package stays small and single-purpose so an AI edit loads one focused file, not a monolith. This is the concrete mechanism for the token-efficiency goal.

AI Integration

AI is reached through one narrow interface with a single CLI backend to start:

type Assistant interface {
    // Planning: turn a vague intent into a concrete commitment.
    Coach(ctx context.Context, intent string) (domain.Commitment, error)
    // Live: is the current window on-task for this commitment?
    JudgeDrift(ctx context.Context, c domain.Commitment, w evidence.WindowSnapshot) (Verdict, error)
    // Ambient: periodic check-in based on recent activity.
    Nudge(ctx context.Context, c domain.Commitment, recent []evidence.WindowSnapshot) (string, error)
}

• Backend (v1): shell out to claude/codex with a strict prompt that demands JSON output. Reuses existing CLI auth; no API key plumbing.
• Latency containment (the CLI is slow, ~seconds, and AI is in the live hot path): all AI calls run in background goroutines; the UI never blocks. Drift judgments are debounced (no faster than ~10s) and cached per (commitment, window-class) so the same window is not re-judged. The UI shows a pending state and updates via SSE when a verdict lands.
• Swap path: the interface boundary lets an Anthropic API backend (faster, structured, prompt-cached) drop in later without touching callers. Not built in v1.

The three live roles ship first: planning coach, live drift interceptor, ambient nudge. The reviewer is deferred. The advisor sits at the cortex layer of the decision core (see "Architecture: Ports Around a Decision Core"): it proposes and judges at the decision points the state machine exposes, but never owns a transition.

Roadmap

Each milestone is independently shippable and gets its own spec → plan → build cycle. M0–M4 build the core plus the first two ports (activity, advisor) and the UI; M5–M7 add the remaining ports, each a small interface + adapter following the pattern M1 establishes.

• M0 — Walking skeleton. Daemon + Gin + minimal browser UI; port domain + statemachine; snapshot persistence; manual commitment → timebox → end. Proves the full stack end-to-end. No AI, no window tracking.
• M1 — Evidence & audit. X11 (xgbutil) active-window tracking via the evidence.Source port, evidence health, per-window time stats, append-only hash-chained audit log, live SSE updates. Establishes the port pattern.
• M2 — AI planning coach. ai port + CLI backend; "sharpen this commitment" in the Planning view.
• M3 — Drift interceptor + ambient nudge. Allowed-context matching + live AI drift judgment (debounced/cached) + violation friction UI.
• M4 — Look good. A real design pass on the web UI.
• M5 — Tasks port. tasks.Provider over current to-do items; Amazing Marvin adapter. Pull the day's commitments from real tasks.
• M6 — Knowledge port. knowledge.Source over personal priorities and about-me context, feeding the advisor richer grounding.
• M7 — Enforcement port. enforce.Guard: make drift cost something, starting with window-minimize (porting legacy minimize_other) and later the privileged guardian / nftables path.

The first sub-project to brainstorm and spec in detail is M0.

Repo Strategy

• New Go module at the repository root.
• Move the existing Rust into a legacy/ directory (or a rust branch) so it remains available as reference while the Go code becomes the front door.

Out of Scope (v1)

"v1" here means the first shippable arc, M0–M4 (core + activity/advisor ports + UI). The items below are deferred past it; some are now named ports with their own later milestones (see Roadmap), others remain fully out of scope.

• Tasks, knowledge, and enforcement ports — named in the architecture and slotted as M5–M7, but not built in v1. The enforce.Guard port starts with window-minimize; its privileged adapters (guardian process, root-owned Unix socket IPC, nftables/DNS domain blocking, delayed admin, break-glass) remain out of scope until that milestone and keep the original Stage 2 threat boundary.
• AI reviewer / session-end reflection.
• Wayland compositor adapters beyond the existing degraded reporting.
• Planner/project model and outcome writeback (beyond the M5 tasks port).
• Presence sensing.

These remain governed by commitment-os-design.md and may return as later milestones.