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Engineering Record · Waryl Systems

We run our business on the systems we build.

Why not build this in-house? We asked the same question, then built these systems for ourselves. This page is the engineering record of what operates Waryl today: research pipelines, an editorial engine, trend detection, security audits. Read the decisions first. They are the part a build budget does not include.

The architecture: what the diagram shows

Read the stack top to bottom: a company, not a script.

This diagram shows the system that operates Waryl today.

  • 01 · Sensing. Five sources feed the intelligence layer: Trends MCP, YouTube API, YouTube Suggest, GitHub, Hacker News. API keys rotate across free-tier accounts so nothing rate-limits.
  • 02 · Strategy. Five engines plan the weekly cycle: Trend, Evergreen, Strategic, Personal, Derivative. An orchestrator applies priority rules and decides what runs when. Agents never self-select.
  • 03 · Execution. Build operations run ten to twelve agents per operation: copy, animations, navigation, trends, research.
  • 04 · Governance. A gate scores every output. Below 4.0 rejects: The Forge at 2.1/5, Heartbeat Monitor at 4.3/5, copy validation 11 accepted, 7 modified, 1 rejected. No output skips this gate.
  • 05 · Memory. Every run writes to one source of truth: index.json for the editorial engine, an internal wiki of ~107 linked documents. The index is the truth; code is a derivative of the docs.
  • 06 · Security. Eight leaf agents audited the stack in parallel and closed 17 vulnerabilities to 0, across three protection layers.
  • 07 · Leadership. The final delivery is approved by a human, in person. Documented principle: the premium user decides, the system suggests.

Data packets travel the rail; the gate is the node no packet passes without a verdict. The same pattern closed 17 vulnerabilities to 0, with 8 leaf agents auditing in parallel.

Three decisions, with trade-offs

1. Orchestrator with priority rules, not free choreography

Decision

The editorial engine runs 5 recommenders (Trend, Evergreen, Strategic, Personal, Derivative). An orchestrator applies priority rules across a weekly 6-phase cycle. Agents never self-select.

Trade-off

Choreography is flexible; rules are predictable. We gave up "agents figure it out" for "we can state what runs next Tuesday." Adding a source means editing rules, not adding an agent.

What we learned

With free choreography you can only describe what happened; with rules you can specify what will happen. For weekly operations, predictability is worth the rigidity.

2. Deterministic first; LLM only where judgment is required

Decision

The site is static Astro with zero unnecessary JavaScript. The hero demo is a deterministic SVG blueprint, no LLM involved. Supabase only receives leads. LLMs are reserved for synthesis and validation.

Trade-off

Deterministic paths are cheap, fast, verifiable. LLM paths are probabilistic and slow. Removing the LLM from the demo costs spectacle; putting it where a rule suffices costs trust.

What we learned

A demo that behaves identically on every visit builds more credibility than a clever one. The LLM's value is judgment, not rendering.

3. Failure is an input, not an accident

Decision

Hypotheses scoring below 4.0 are rejected. The Forge animation was rejected at 2.1/5; Heartbeat Monitor shipped at 4.3/5. Copy validation: 11 accepted, 7 modified, 1 rejected. The trend pipeline rotates 5 to 10 free-tier API keys across 5 sources (Trends MCP, YouTube API, YouTube Suggest, GitHub, Hacker News). Every deliverable passes an accept/modify/reject gate. Postmortems are kept, including "7 fatal failures of the Devil's Advocate."

Trade-off

Gates and scoring add latency and cost; rotation adds operational overhead. Without them, a silent pass ships confidently wrong and one rate limit kills the week.

What we learned

A rejection with a score is more useful than an approval without one. Design for the failure mode: record it, score it, feed it back. The same audit removed 473 AI-typical em-dashes from our visible copy; we run that check on everything, including this page.

Stack

Astro 7, Tailwind CSS, GSAP, Lenis, Supabase (leads only). Agent operations run on LLM providers: OpenAI, Anthropic, and open-weight models. Plain names, no badges: the architecture is the product, not the libraries.

Bring your architecture. We will contrast it against this one, point by point, and tell you where in-house makes sense. Sometimes it does; we will say so.

Free architecture review · 15 minutes

No pitch. Point-by-point contrast. Sometimes the answer is in-house; we will say so.

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