I’m building an iOS fitness app and I didn’t want content marketing to become a second full-time job, so I’ve been building the infrastructure around it myself. The current pipeline looks roughly like: research → content → video render → automated QA → scheduled publishing → Instagram/Facebook → comment automation → tracking The stack is mostly Python, FFmpeg, systemd, Meta Graph API, Cloudflare Workers and Supabase. A few things that turned out to be much harder than I expected: safely publishing to Instagram and Facebook without accidental duplicates handling a laptop being offline when a scheduled post should fire Meta webhook verification and Page permissions Facebook comment → Messenger private replies separating Instagram and Facebook automation so one cannot break the other automated video QA before anything is allowed to publish making the scheduler fail closed when Meta returns an ambiguous result thumbnail selection so Reels don’t appear with a black cover One thing I’m deliberately trying to avoid is “AI generates unlimited junk and posts it everywhere.” The system has a QA gate and publishing state so content has to pass checks before it can go live. It’s now successfully publishing live content, and I’m working on making the generation queue prepare the next posts several hours before their scheduled slots. I’m curious how other people building production automations handle the last 20%: observability, retries, idempotency and failure alerts. If you were hardening this system next, what would you work on? currently the first post is live you can check it here the next 4 are scheduled in the next 48 hours : instagram facebook dauntra   submitted by   /u/Psychological-Row938 [link]   [comments]