An AI content system built with no-code tools (Airtable, n8n) designed to achieve virality. The workflow involves automated agents that scrape social media platforms (TikTok, Instagram, etc.) for trending topics, sounds, and formats. This data is fed into an Airtable 'content brain' which then informs an AI (GPT/Claude) to generate platform-specific content designed to match current trends.
Trends on TikTok, Instagram and other platforms rise and fade within days. Social media managers try to keep up by scrolling for hours, saving examples in phone folders and pitching ideas in team chats, but by the time a concept is approved and produced, the moment has often passed. Smaller brands and agencies without a dedicated trend researcher either chase every trend with off-brand content or miss the relevant ones entirely.
Social media trend monitoring AI turns trend spotting into a repeatable workflow. Automated collectors gather signals about rising topics, sounds and formats from sources you are allowed to use, store them in an Airtable content brain alongside your brand guidelines and past performance, and prompt an LLM to draft platform-specific ideas that fit both the trend and your product. The content team still chooses, scripts and produces. The system's role is to shorten the gap between a trend emerging and a relevant idea reaching the team, without pretending any piece of content can be engineered to go viral.
n8n or Make.com collects trend signals from official sources such as platform APIs, trend dashboards and permitted social listening tools, avoiding scraping that breaches platform terms.
Each trend is logged in Airtable with the format, sound or hashtag, example links, growth indicators, and notes on whether the audio is cleared for commercial use.
An automation filters trends against brand rules, excluding sensitive topics, competitors and anything clashing with your values.
For qualifying trends, an LLM such as ChatGPT or Claude writes several content ideas and short scripts that connect the trend to your product, tagged by platform.
Ideas appear in Airtable for the content team to approve, produce or discard, and published results are fed back so future suggestions improve.
An n8n workflow identifies a new trending audio clip on TikTok. It adds the trend data to an Airtable base. Another automation triggers, using GPT to write five different video ideas that incorporate the trend and the company's product. The scripts are then populated in Airtable for the content team to produce.
Airtable, n8n/Make.com, Web Scraping Tools, OpenAI/Claude API, Social Media APIs
Scraping social platforms usually breaches their terms of service and may involve collecting personal information, which brings Privacy Act obligations; use official APIs, platform trend tools or licensed listening services instead. Trending sounds are often licensed for personal use only, and business accounts may be limited to a commercial music library, so check before using audio to avoid Copyright Act 1968 issues. Influencer-style content and ads must be clearly identifiable as advertising, and the ACCC has published guidance for influencers and brands on disclosure. Avoid trends involving real people's likeness or other brands' trade marks without permission.
This solution requires careful evaluation of cost-benefit ratio. Consider implementation only after thorough analysis and risk assessment.
Scraping generally breaches these platforms' terms and can lead to blocked accounts or legal complaints. Safer options include official APIs where available, the platforms' own trend and creative tools, and paid social listening services with proper data agreements. The workflow is designed to plug into these permitted sources instead.
Nothing can promise that. What the system can do is surface relevant trends sooner and give your team a steady flow of on-brand ideas to test. Results depend on production quality, timing, audience fit and platform algorithms, which change frequently and are outside anyone's control.
Choosing and connecting trend sources, designing the Airtable structure, writing brand filters and idea prompts, and tuning suggestions with the content team takes time. Most of the later weeks go into reviewing idea quality and adjusting filters so the team trusts what lands in Airtable.
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