Designed a consistent adapter/factory architecture (getAI(), getDatabase(), getCache(), …) applied uniformly across all 31 packages, isolating business logic behind stable interfaces — swapping a managed API for a self-hosted alternative is a config change, not a refactor, eliminating vendor lock-in and de-risking provider price/API churn.

Unified 40+ third-party providers behind those interfaces, including LLMs (OpenAI, Anthropic, Gemini, AWS Bedrock, Hugging Face), databases (PostgreSQL, SQLite/Turso, DuckDB, with vector search), caches (Redis, S3, memory, file), payments (Stripe, BTCPay, USDC/x402), and auth (Keycloak, Cognito, Nostr).

Built as a higher-level alternative to early LangChain.js (then well behind its Python counterpart): one interface for chat, streaming, embeddings, vision, TTS, and function calling that keeps pace with the newest models without framework churn.

Used AI-assisted development to write thin first-party adapters instead of adopting heavyweight frameworks — vendor SDKs are optional peer dependencies, so consumers install only what they use, shrinking the dependency tree, upgrade pain, and supply-chain exposure.

Made the SDK AI-native: every package ships a machine-maintained AGENT.md context file, and an MCP documentation server answers integration questions straight from the package docs.

Ran the project with production-grade engineering practice: pnpm/Turborepo monorepo, ESM-only, ~36k lines of Vitest tests, Biome linting, conventional commits, and automated Changesets releases to public npm — 1,750+ commits.

Designed a single-source-of-truth model layer: a @smrt() decorator on a TypeScript class triggers a build-time AST scan (custom OXC-based scanner → manifest) that generates the class's SQL schema, REST API, CLI, and MCP tool server from one definition — so a domain concept is defined once instead of re-implemented as boilerplate across four surfaces, cutting the code an AI agent writes and a human reviews.

Unified the human and agent surfaces onto one code path: generated MCP tools, REST routes, and CLI commands all resolve to the same ORM collection under a shared sensitive/readonly field policy — letting AI agents operate an application with the same capabilities and guardrails as its users, from a single codebase.

Embedded AI operations in the object model — is() for natural-language boolean checks and do() for instructions on every persistent object, with the object's own methods passed to the model as function-calling tools — so domain logic is directly promptable rather than bolted on.

Built 49 lockstep-released packages of hardened, reusable domain logic — multi-tenant RBAC (a four-level permission cascade), double-entry billing (single-table-inheritance contracts posting balanced journals to a ledger), plus content, messaging, assets, semantic knowledge, and geospatial search — so bespoke SMB and greenfield SaaS builds compose vetted modules instead of re-solving the same concerns per project.

Shipped a typed, themeable, accessibility-tested Svelte 5 component library (~80 components — forms, tables, modals, navigation, calendar) so generated models get a usable UI without rewriting the same components for every app.

Made the framework agent-native and reproducible: per-package AGENTS.md context files and an MCP developer server (code generation + project introspection) for AI coding assistants; run as a pnpm/Turborepo ESM monorepo with 710 test files, Biome, conventional commits, and automated Changesets releases — 1,168 releases shipped.

Launched a network of 10 hyperlocal news sites (e.g., bentleyalberta.com) powered by a multi-tenant SaaS dashboard that orchestrates a suite of specialized AI agents sharing a unified database via Single Table Inheritance (STI).

Autonomous agent monitoring municipal portals (CivicWeb/SharePoint) using PDF parsing and OCR to generate source-linked meeting coverage and automated journalism.

Managed automated media workflows orchestrating performers, characters, and scenes through multi-stage ComfyUI workflows and custom diffusion models.

Developed agents for hyperlocal weather forecasting and sports statistical coverage.

Engineered agents for autonomous social media performance tracking/posting and automated GitHub repository management.

Developed an ad network with weighted distribution, impression tracking, and automated site/zone registration.

Architected a TypeScript monorepo (6 apps, 2 agent daemons, 6 packages) around a model-driven framework: 59 declarative domain models generate REST APIs, Postgres/SQLite schema migrations, CLIs, and MCP servers from a single source of truth.

Built a local-first capture system with native device adapters — Sony CrSDK (C++ bindings), gphoto2, Insta360 MediaSDK (360°), and hardware turntable control — where sessions record offline to SQLite + disk, then resume-sync to the central library as immutable, checksummed source packages.

Automated field-media offload (drones, cameras) with content-based file classification, sidecar detection, SHA-256 deduplication, and GPS track indexing with geohash spatial queries that link footage moments to real-world places — the substrate for reconstructing whole neighbourhoods from a single street drive.

Designed a lease-based distributed job orchestrator that schedules each pipeline step by placement — edge capture node, central host, or NVIDIA/ROCm GPU worker — so heavy AI workloads run on hardware I own instead of metered frontier APIs.

Shipped 13 production pipeline step types: ComfyUI image editing and text-to-video generation, Whisper transcription, voice-cloning TTS, face embedding and matching (InsightFace), background removal, and an article-to-video news-segment generator that publishes straight to YouTube, Threads, X, Bluesky, and Facebook.

Eliminated cloud warm-storage costs with a multi-store architecture: per-tenant S3/MinIO stores with encrypted credentials, presigned multipart uploads, and node-local NAS replication — the library scales by adding servers, not cloud spend.

Built the multi-tenant consumer surface — capability-scoped API keys, HMAC-signed webhooks, tenant provisioning — and published a typed SDK and embeddable UI components to npm, letting downstream apps use ergot as their asset backend without carrying its weight.

Operated the platform with GitOps: Kubernetes + Flux across dev/staging/production, multi-stage Docker images, environment-gated side effects, and a zero-downtime schema-migration workflow.