Social media posting was done manually, platform by platform. No scheduling, no coordination, no visibility into what was performing. Teams were publishing and hoping, with no structured way to learn what content worked.
Reliability and the analytics feedback loop were the two priorities.
Integrates with social media APIs for platforms that expose them, and uses Selenium for automation on platforms that do not. Posts scheduled through a central interface, queued, and dispatched at configured time.
Social platforms are inconsistent — rate limits, login challenges, layout changes. Built retry logic and failure detection so a failed post triggers an alert rather than disappearing silently. Content creators are told when something did not go out.
class PostScheduler:
def dispatch(self, post: ScheduledPost) -> Result:
# Health check before attempting
if not self.platform_healthy(post.platform):
return Result.DEFERRED
try:
result = self.post(post)
self.log_success(post, result)
return Result.SUCCESS
except RateLimitError:
self.reschedule(post, delay_minutes=15)
return Result.RESCHEDULED
except PostingError as e:
# Never silent — always alert
self.alert_creator(
post=post,
reason=str(e)
)
return Result.FAILEDPulls engagement data — likes, shares, reach — back into the system so teams see what performs across platforms in one view rather than logging into each separately. Closed the loop: publish → measure → learn.
Teams could plan a week of content, schedule it once, and have it go out reliably. Analytics gave actual data to make content decisions.
"Publishing without analytics is guessing. The feedback loop is what turns activity into learning."