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A typical Amazon seller spends 3-4 hours on product research for every new product they consider. Open 8 browser tabs. Cross-reference prices. Copy numbers into a spreadsheet. Read competitor reviews. Check 1688 for sourcing costs. Repeat for 5 candidates. That is 15-20 hours — for information an AI agent can assemble in under 2 minutes.

The 80/20 rule applies here: 80% of product research is data gathering, which is pure repetition. 20% is judgment, which requires your experience. Automate the 80%. Focus on the 20%.

What the Agent Does in 90 Seconds

Give your AI agent a category name. It queries structured e-commerce data and returns:

# One command after installing sorftime-seller-agent:
# /goal Run HPI 5D verified shortlist for kitchen storage on Amazon US.
# stop after 70 turns

Example output: HPI shortlist generated by the agent in 90 seconds — HPI, price, sales, reviews, FBA fee. Example output: HPI shortlist generated by the agent in 90 seconds — HPI, price, sales, reviews, FBA fee.

What You Still Need to Do

The agent gives you a verified shortlist. It does not replace:

The 80/20 Split

Agent Does (80%) You Do (20%)
Pull and rank products Judge which ones fit your brand
Calculate margins Verify with real supplier quotes
Flag review patterns Read the actual reviews
Show price trends Decide if the trend will continue
Identify low-competition signals Decide if low competition means opportunity or dead market

The sellers who figure this out first will spend Friday afternoons reviewing shortlists their agent generated during the week. The sellers who do not will still be opening browser tabs.


Try it yourself: git clone https://github.com/DannylydST/sorftime-seller-agentpython3 scripts/install.py → get your key at open-intl.sorftime.com