# Archevyn
> Order. Stability. Execution. Spec-Driven Tech Lead Architecture for autonomous multi-agent engineering.

Archevyn is an engineering framework designed to coordinate autonomous AI agents through rigorous specifications, isolated execution waves, 4-point evidence gatekeepers, and circuit-breaker rollbacks. It replaces informal "prompt-and-pray" workflows with deterministic engineering discipline.

## Conceptual Methodology
1. Formal Specification & Scope Boundaries: Target outcomes, business rules, edge cases, and explicit file boundaries ([CREATE], [MODIFY], [FORBIDDEN]) are locked before writing code.
2. Isolated Execution Waves: Autonomous agents execute scoped slices in clean workspaces or isolated worktrees, preventing cross-task token bloat and context contamination.
3. 4-Point Evidence Gatekeeper: Every change must provide automated proof (Status, Proof Test Command & Exit Code, Autonomous Decisions, Blast Radius) before integration.
4. 2-Retry Circuit Breaker & Clean Rollback: Failing implementations are reverted immediately after two unsuccessful attempts, preventing cascading bugs and context rot.

## Featured Projects
- [Bield](https://archevyn.dev/projects/bield): Free, fully offline, ad-free and tracking-free Android sanctuary app featuring binaural beat synthesis, layered soundscapes, and SOS Panic Relief with guided 4-7-8 breathing (Inhale 4 s → Hold 7 s → Exhale 8 s, repeating), an animated expanding/contracting circle, voice cues (inhale / hold / exhale), and organic haptic pulses synced to the breath. Live on Google Play.
- [Job Finder](https://archevyn.dev/projects/job-finder): Autonomous market intelligence engine designed to scrape multi-channel tech jobs, evaluate candidate alignment using Google Gemini, and extract actionable skill gaps. Live at https://job-finder.archevyn.dev.

## Blog Articles & Deep Dives
- [Why I Deleted 254 MB of Agent Infra for 3 Markdown Files](https://archevyn.dev/blog/why-i-deleted-254mb-agent-infra-for-3-markdown-files) (Nov 2026)
  Description: Most multi-agent setups fail because the orchestration layer consumes more tokens than the actual engineering work. Here is how deleting 17,200 redundant files and shrinking state down to three focused Markdown documents cut baseline prompt overhead by 85%.
  Markdown Source: https://archevyn.dev/blog/why-i-deleted-254mb-agent-infra-for-3-markdown-files/md
- [Building an Autonomous Market Intelligence Engine: How I Replaced My Job Search with AI Agents](https://archevyn.dev/blog/autonomous-market-intelligence-engine-ai-agents-job-search) (Oct 2026)
  Description: Manual job searching is a brute-force loop with terrible returns. So I stopped searching and built a system that does it instead: autonomous scrapers feeding an LLM that scores every posting against my profile and tells me what skills I'm missing. The output isn't a job list. It's a map of the market.
  Markdown Source: https://archevyn.dev/blog/autonomous-market-intelligence-engine-ai-agents-job-search/md
- [Why Your Agentic AI System Forgets Itself: A Coordinator's Guide to Context Rot](https://archevyn.dev/blog/why-your-agentic-ai-system-forgets-itself-context-rot) (Jul 2026)
  Description: The moment your agentic AI system starts repeating mistakes or forgetting decisions isn't a model failure — it's an architecture failure. Here's what context rot and token bloat actually are, why they compound as you scale, and how a non-technical Coordinator can design against them from day one.
  Markdown Source: https://archevyn.dev/blog/why-your-agentic-ai-system-forgets-itself-context-rot/md
- [Building Bield: How an AI Orchestration System Shipped a Native Android App Without Me Writing a Single Line of Kotlin](https://archevyn.dev/blog/building-bield-ai-orchestration-native-android) (Jun 2026)
  Description: Bield is a free, fully offline Android app for mental wellness through sound therapy. This is how an AI orchestration system — not a single chat session — shipped it in native Kotlin without me writing a line of implementation code.
  Markdown Source: https://archevyn.dev/blog/building-bield-ai-orchestration-native-android/md
- [I Don't Write Code. I Architect Systems That Do.](https://archevyn.dev/blog/i-dont-write-code-i-architect-systems-that-do) (Jun 2026)
  Description: Why giving up the 'learn to code' path and focusing on AI orchestration architecture is a more sustainable long-term strategy for builders with ideas but without a traditional CS background.
  Markdown Source: https://archevyn.dev/blog/i-dont-write-code-i-architect-systems-that-do/md

## Machine-Readable Resources
- Complete LLM Documentation: https://archevyn.dev/llms-full.txt
- RSS 2.0 Syndication Feed: https://archevyn.dev/feed.xml
- XML Sitemap: https://archevyn.dev/sitemap.xml