In This Article
Introduction
A startup founder configured a three-agent OpenClaw team for competitive intelligence: one agent monitors news and press releases for competitor mentions, one tracks job postings (a leading indicator of product direction), and one monitors app store reviews for competing products. Each morning, a summary report arrives in Telegram: "Competitor X posted 3 senior ML engineer roles this week (suggesting new AI feature development). Competitor Y received 47 new 1-star reviews mentioning their recent price increase. No major press announcements." Building this level of competitive intelligence used to require a dedicated analyst or expensive services. With OpenClaw: $20–30/month. See OpenClaw for startups for more use cases.
Architecture
Three specialized agents, shared memory. Each runs Heartbeat on a different schedule. Results written to COMPETITORS.md. Morning briefing agent aggregates and delivers to Telegram. The key is specialization: each agent has a narrow job. News agent doesn't care about jobs; jobs agent doesn't care about reviews. The briefing agent reads all three outputs and synthesizes. That's the multi-agent pattern.
The Three Agents
- News Agent: RSS, Google News, press release feeds. Keyword: competitor names. Output: mentions, sentiment. Runs every 6 hours. Writes to COMPETITORS.md.
- Jobs Agent: LinkedIn, Indeed, company career pages. Track competitor job postings. Role titles indicate product direction (e.g., "ML engineer" → AI features). Runs daily. Job postings are a leading indicator — companies hire before they ship.
- Reviews Agent: App Store, Play Store APIs. Track review volume, rating changes, common themes. "47 reviews mention price increase" = signal. Runs daily. Review spikes often precede churn.
Output
Daily Telegram message: bullet summary. "Competitor X: 3 ML roles. Competitor Y: review spike, price complaints. No press." User gets strategic intel with morning coffee. No manual monitoring. The format is intentionally terse — you want the signal, not a novel. See tech news digest for a similar pattern applied to industry news.
Cost
~$20–30/month in API fees. Plus setup time. vs $2,000+/month for manual analyst or market intel service. Orders of magnitude cheaper. The agents make a few dozen API calls per day. LLM costs are low for this workload. The value is the automation — you get intel you wouldn't have had time to gather manually.
What You Need
OpenClaw, Telegram integration, API access to job boards and app stores (some are free, some require keys), and a list of competitors to track. Configure the three agents with appropriate tools. Set Heartbeats. Point the briefing agent at COMPETITORS.md. Done. First run will need tuning — adjust keywords, schedules, output format. After a week, it runs itself.
Wrapping Up
Competitive intelligence is a canonical multi-agent use case. See multi-agent and tech news digest for patterns.