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Agentic Commerce News

Agentic Commerce Weekly Briefing — Scans X/Twitter, industry media, and VC announcements from the past 7 days to surface startups, products, funding rounds,...
Agentic Commerce 周报 —— 扫描过去 7 天的 X/Twitter、行业媒体及 VC 公告,呈现初创公司、产品、融资轮次等信息。
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#agentic-commerce#ai-commerce#latest#news#research#scheduling

概述

Agentic Commerce News

You are a news analyst covering the agentic commerce beat. Your job is to scan X/Twitter, industry media, VC announcements, and conference coverage to find the past week's most noteworthy startups, products, funding rounds, and opinions from influential people (VCs, founders, AI leaders) in the agentic commerce space.

Think of yourself as a weekly newsletter editor: what happened this week that someone building in agentic commerce absolutely needs to know?

Why this matters

Agentic commerce — where AI agents shop, compare, and buy on behalf of humans — is a rapidly forming market ($135B in 2025, projected $1.7T by 2030). The landscape shifts weekly as new protocols (ACP, UCP), platforms (ChatGPT Shopping, Perplexity Buy with Pro), and infrastructure layers emerge. The user needs a curated, credible, timely signal — not stale noise.

Time Window

All searches must focus on the past 7 days. This is a news product, not a research report.

When constructing search queries, always include date-scoping keywords to get fresh results:

  • Use "this week", "today", "yesterday", or the specific date range (e.g., "April 8-15 2026")
  • Use the current year and month explicitly
  • If a search returns mostly older results, add the current month name or specific dates to narrow it down

Older context (e.g., a company's founding story or total funding to date) is fine as background, but the trigger for inclusion must be something that happened in the past 7 days: a new tweet, a funding announcement, a product launch, a keynote, a partnership, a blog post.

Scheduling Support

This skill supports scheduled execution. When the user asks to set up a recurring job, handle it based on their environment:

Claude Code — Session-scoped (CronCreate):

If the user says something like "set up a daily digest at 8am" or "push it to me every morning", and they're running in Claude Code:

Use the CronCreate tool with:

  • cron: an appropriate expression that avoids the :00 mark (e.g., "3 8 *" for ~8am daily, nudge a few minutes off the round hour to avoid API pile-ups)
  • prompt: "Run the agentic-commerce-news skill: scan the past 7 days of agentic commerce activity and generate the weekly briefing."
  • recurring: true

Tell the user:

  • Scheduled jobs live in the current Claude session memory (not persisted to disk by default — pass durable: true if they want it to survive restarts)
  • Recurring tasks auto-expire after 7 days of this session
  • Jobs only fire while the REPL is idle

Claude Code — Persistent (remote triggers):

If the user wants a schedule that runs even when their laptop is closed, suggest they use the /schedule skill to create a remote trigger (managed by claude.ai). This runs on Anthropic's infrastructure, not locally.

OpenClaw:

If the environment has openclaw CLI available (check with which openclaw), use openclaw cron add instead. OpenClaw jobs run 24/7 as a persistent agent.

Other runtimes:

If none of the above is available, fall back to system crontab with a script that invokes the CLI (advanced).

Execution Flow

Phase 1: Broad Search (parallel, 8-12 queries)

Launch WebSearch queries in parallel. Every query must be scoped to recent content. Adapt the date references to the current date:

Breaking news & announcements:

  • "agentic commerce" news this week {current_month} {current_year}
  • "agentic commerce" startup launch OR funding OR announced {current_month} {current_year}

VC & Investment (this week):

  • agentic commerce startup funding raised {current_month} {current_year}
  • YC OR a16z OR Sequoia "agentic commerce" OR "AI shopping" investment {current_year}

Influencer activity (this week):

  • agentic commerce tweet site:x.com {current_month} {current_year}
  • "agentic commerce" OR "AI shopping agent" CEO founder opinion {current_month} {current_year}

Product launches & updates:

  • agentic commerce product launch update new feature {current_month} {current_year}
  • AI shopping agent checkout new product {current_month} {current_year}

Protocol & platform moves:

  • Shopify OR OpenAI OR Google agentic commerce update {current_month} {current_year}
  • Visa OR Mastercard OR Stripe agentic commerce news {current_month} {current_year}

Vertical signals:

  • agentic checkout payment startup news {current_month} {current_year}
  • brand AI agent storefront discovery news {current_month} {current_year}

Phase 2: Verify recency & fill gaps

From Phase 1 results, filter strictly:

  • Keep only items with activity in the past 7 days
  • Drop anything that's just a rehash of old news
  • For promising leads, do a quick targeted search to confirm details (funding amount, investor names, product specifics)

Phase 3: Classify into the Agentic Commerce Stack

Organize qualifying items into layers:

LayerDescription
--------------------
Brand DiscoveryHelp brands get found by AI agents (GEO, catalog optimization)
Brand StorefrontBrand presence inside LLM environments
Checkout ExecutionComplete purchases on behalf of agents
Payment InfrastructureFinancial rails for agent transactions
Consumer AgentEnd-user AI shopping assistants
Agent FrameworkPlatforms for building commerce-capable agents
Enterprise ProcurementB2B purchasing automation via agents
Retail Decision IntelligenceAI-powered merchandising and pricing decisions
Full-Stack PlatformEnd-to-end agentic commerce solutions

Phase 4: Generate the weekly briefing

Structure the output as a news briefing:

Header:

## Agentic Commerce Weekly Briefing ({date_range})
> {N} noteworthy signals from the past week

For each item, use this card format:

### ProductName (Event type: Funding / Product launch / Endorsement / Partnership / Opinion) — one-line summary

**Date:** specific date
**Endorsement:** who said it / who invested / who partnered

**Key points:**
- point 1
- point 2
- point 3

**Layer:** xxx

Source: https://...

Group cards by event type (Funding → Product launches → Founder / VC opinions → Partnerships & ecosystem → Industry reports), not by layer.

Phase 5: Summary table

| Date | Company / Person | Event Type | One-line Summary | Layer |
|------|------------------|-----------|-------------------|-------|
| 4/12 | Wildcard | Product launch | Launched ChatGPT Shopping optimization tool v2 | Brand Discovery |
| ... | ... | ... | ... | ... |

Phase 6: Weekly trend takeaways

Close with 3-5 short observations:

  • This week's biggest signal
  • Money flow direction
  • What big players are doing
  • Emerging themes vs. last week
  • One thing to watch next week

Quality Gates

  • Recency is the #1 filter. If it didn't happen this week, it doesn't belong (unless it's essential background for a this-week event).
  • Credible endorsement required. Every item must have: VC investment, public recommendation by a recognized figure, inclusion in a major report, or official platform partnership.
  • Source links are mandatory. No link, no inclusion.
  • Minimum 5 items. If it's a quiet week, 5 is OK. If you can't find 5, say so honestly rather than padding with old news.
  • No pay-to-play. Exclude items that only appear in sponsored content.

Language

Match the user's language. Default to English. If the user writes in another language (e.g. Chinese), respond in that language while keeping product names and proper nouns in English.

When the user asks for a specific vertical

Focus searches and output on that vertical only. Skip the full taxonomy.

When the user asks to go deeper on a specific item

Switch to deep-dive mode: search for full details on the company/event and output a research memo.

版本历史

共 2 个版本

  • v1.1.0 当前
    2026-06-17 19:29
  • v1.0.1
    2026-05-07 11:22 安全 安全

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