content-machine

An autonomous, single-operator content studio: ideation → production (blog + video) → repurposing → scheduled auto-publish, across 3 niches and 7 platforms, at 200+ published pieces per month.

Personal system, not a packaged product. It runs my content operation end-to-end; published here to share the architecture. Expect hard-coded paths, opinionated conventions, and no install script.

What it does

Ideate ──────► Generate ──────► Render ──────► Schedule ──────► Learn
idea scorer     Claude CLI       V2 video       APScheduler      analytics +
weekly reels    per-task         pipeline:      daemon fires     UTM star
32-file         model routing    storyboard →   pending posts    attribution
virality KB     (4 model tiers)  HyperFrames →  from SQLite      feeds next
90-day          150 Python       FFmpeg,        launchd          week's ideas
no-repeat       scripts          word-synced    automation
tracker                          captions

Architecture highlights

• 150 Python scripts, one orchestration model — all active code in v1/scripts/; entry points: run_blog_pipeline.py (one idempotent run produces every derivative of a blog: platform posts, social images, carousel, deck, reel brief, thumbnail, worksheet), run_video_pipeline.py (raw footage → trim → storyboard → HyperFrames per-beat compositions → FFmpeg composite), run_voiceover_week.py (audio-first lane: VO → B-roll montage long-form + auto portrait Shorts), scheduler.py (APScheduler daemon).
• Per-task LLM model routing — a single routing table (v1/scripts/lib/niche_config.py) assigns the right Claude model per task: top tier only for quality-critical hero content, workhorse tier for generation, small models strictly for mechanical classification. No model IDs hard-coded at call sites.
• Claude CLI as the LLM runtime — pipeline calls run claude -p subprocesses on subscription auth (no API key), with disk caching, timeout budgets per stage, and backoff only on transient failures.
• Virality as configuration — a 32-file knowledge base injects hooks, CTAs, and guardrails into every generator, routed per niche. Editing markdown changes generation behavior; prompts are versioned in code, never copy-pasted.
• Honesty guardrail — build-in-public posts about my open-source tools are generated with an explicit never-overclaim constraint per project.
• Closed loop — UTM-tagged repo links + analytics collection tie published content directly to GitHub star deltas, which feed the next week's idea scoring.

Stack

Python · Claude CLI (model-routed) · HyperFrames · FFmpeg · APScheduler · SQLite · launchd · Meta Graph API · YouTube (4 channels) · Medium · LinkedIn

Related tools

• autopilot-jobhunt — autonomous job-search agent (100+ ⭐, PyPI, MCP)
• inbox-to-action — one-pass agentic inbox triage (PyPI, MCP)

Author

Tarun Gupta — tarunlnmiit.github.io · Case study of this system