Enoch AI / Lab

Under the hood.

The technical side: what I build with these days, what I'm writing about, what I'm currently working on. Practitioner notes, not marketing copy.

Sections

  • Stack →

    What I'm building with right now: hosting, app stacks, models, agent runtime, workflow infrastructure.

  • Writing →

    Best practices I run with and clever AI use-cases. Considered pieces, not hot takes.

How I work

A recent personal build went from planning to production using a coordinated multi-LLM workflow: separate tools for design review, implementation, code review, and test authoring, all kept aligned through version-controlled docs instead of shared memory. The human stayed in the loop for decisions and real-world verification. Claims were checked, not trusted.

That discipline is the point. The interesting part is not which model you use; it is the operating system around the tools.

Case study: DocLifts — a multi-LLM development process →

Currently building

A portfolio of small AI-integrated sites and the tooling around them: production API integrations, automated content pipelines with human review, affiliate and scheduling workflows, deployment checks, and agent infrastructure that reduces the operational drag. Some project details are private; happy to talk through the shape of the work on a call.

Elsewhere

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