Product Manager
Monitoring 100 Competitor Pages for Changes β Weekly Diff Report
Key Takeaway
An AI agent scrapes 100 competitor pages every week, diffs them against the previous snapshot, and flags every change β new features, pricing shifts, team hires, blog posts β in a single consolidated report delivered to Telegram.
The Problem
We compete in the AI agent infrastructure space. That means we compete with LangChain, CrewAI, AutoGen, Composio, and a dozen others. Each of them has a website with pricing pages, feature lists, team pages, blog archives, careers sections, and documentation.
These pages change. Pricing tiers get restructured. Features get added. Key engineers get hired. Blog posts signal new strategic directions. Partnership announcements reveal where the market is moving.
If you're not tracking these changes, you're reacting instead of anticipating. By the time someone mentions a competitor's new feature in a sales call, they've had it for three weeks and you look uninformed.
The manual approach? Open 100 URLs in a browser, eyeball each one, try to remember what changed since last week. Nobody does this. It's humanly impossible at scale.
Competitive intelligence tools exist β Crayon, Klue, Kompyte. They cost $15,000 to $50,000 per year. For a startup, that's absurd.
The Solution
Scrapling for data collection + a simple diff engine built by the agent. Scrape 100 pages weekly, store snapshots, compare current to previous, flag changes, and deliver a consolidated report.
Total infrastructure cost: the compute time to run 100 scrapes once a week. About 30 minutes of server time.
The Process
The system works in three phases:
Phase 1: Page inventory
yamlShow code
# competitors.yaml β what we track
competitors:
- name: LangChain
pages:
- url: https://langchain.com/pricing
category: pricing
- url: https://langchain.com/features
category: features
- url: https://langchain.com/about
category: team
- url: https://blog.langchain.dev
category: blog
- url: https://langchain.com/careers
category: careers
- name: CrewAI
pages:
- url: https://crewai.com/pricing
category: pricing
# ... 20 pages per competitor
# ... 5 competitors Γ 20 pages = 100 pages
Phase 2: Weekly scrape + snapshot
bashShow code
# Cron: every Monday at 6:00 AM UTC
0 6 * * 1 mrchief cron run --task "Run weekly competitive monitoring.
Scrape all pages in competitors.yaml using scrapling (stealth mode for
protected sites). Save snapshots to competitor-data/YYYY-MM-DD/.
Diff against previous week. Report changes to Telegram."
The agent uses the right Scrapling mode per page:
View details
Static pages (blog, about) β simple mode (~200ms each)
Protected pages (pricing, features) β stealth mode (~3s each)
JS-heavy pages (interactive demos) β dynamic mode (~10s each)
Total scrape time for 100 pages: ~25-35 minutes
Phase 3: Diff + report
The agent compares each page's current content against the previous week's snapshot:
pythonShow code
# The agent generates and runs diff logic like this:
# For each page:
# 1. Load previous snapshot (text content, extracted elements)
# 2. Load current scrape
# 3. Compute structural diff (added/removed/changed sections)
# 4. Classify change significance: major / minor / cosmetic
# 5. Generate human-readable summary
A real weekly report looks like this:
View details
π Weekly Competitive Intelligence Report
March 10β16, 2026 β 100 pages across 5 competitors
π΄ MAJOR CHANGES (3)
ββββββββββββββββββββ
1. LangChain /features
ADDED: "Enterprise SSO" β new section under Security
β οΈ We don't have this feature yet
2. CrewAI /pricing
CHANGED: Pro tier $49β$79/month (+61%)
ADDED: New "Team" tier at $149/month
3. AutoGen /careers
ADDED: 4 new positions β 2 ML Engineers, 1 DevRel, 1 Sales
Signal: expanding engineering + go-to-market
π‘ MINOR CHANGES (7)
ββββββββββββββββββββ
4. Composio /blog β 3 new posts (RAG tutorial, partnership, changelog)
5. LangChain /about β new VP Engineering headshot/bio added
6. CrewAI /features β reworded "Autonomous Agents" β "Agentic Workflows"
...
βͺ NO CHANGES (90 pages)
π 30-Day Trends:
- Most active: CrewAI (14 changes across all pages)
- Fastest moving: Pricing pages (5 changes in 4 weeks)
- Hiring signal: AutoGen ramping aggressively (8 new roles in 30 days)
The Results
100
Pages monitored
5
Competitors tracked
~30 minutes
Scrape time (weekly)
8-15
Changes detected (avg/week)
2-4
Major changes (avg/week)
~1/week
False positives (cosmetic flagged as major)
Monday 7:00 AM to Telegram
Report delivery
5-10 minutes
Human review time
Cost comparison:
| Approach | Annual Cost | Pages | Update Frequency |
|---|---|---|---|
| Crayon/Klue | $15,000β$50,000 | Varies | Daily |
| Manual monitoring | $0 (but impossible) | 10-20 max | Weekly if lucky |
| Scrapling + agent | $0 | 100+ | Weekly (configurable) |
The LangChain SSO feature detection was real value. We saw it within 48 hours of it appearing on their site. That gave us two weeks to discuss whether to prioritize SSO β before our sales team heard about it from prospects.
Try It Yourself
bashShow code
# Install scrapling
# Install via Mr.Chief dashboard after signing up at mrchief.ai/setup
# clawhub install scrapling
# Create your competitor page inventory
# (The agent can help you build this from competitor URLs)
mrchief run --task "I want to monitor these 5 competitors:
[competitor1.com, competitor2.com, ...]. Find their pricing, features,
about, blog, and careers pages. Save as competitors.yaml."
# Run the first baseline scrape
mrchief run --task "Scrape all pages in competitors.yaml using scrapling.
Save snapshots to competitor-data/$(date +%Y-%m-%d)/"
# Set up weekly cron
mrchief cron add --schedule "0 6 * * 1" \
--task "Run weekly competitive monitoring from competitors.yaml.
Diff against previous week. Report to Telegram." \
--channel telegram
First week is baseline. Second week you start getting diffs. By week four, you'll wonder how you ever competed without this.
100 pages. 5 competitors. 30 minutes of compute. Every change, caught.
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