ACP is the HTML of agentic commerce

Hacker News

Instead of waiting for OpenAI to scrape the whole web so your products get listed and people can buy through it, we’ve enabled our own ACP abstraction layer over Shopify to make your store agent ready right now. Merchants get a one-click setup: connect your store and agents can query structured product data (inventory, pricing, availability) and initiate purchases through ACP-compatible flows. Everything is structured and permissioned; no scraping, no prompt-hacking storefront HTML. Full agentic payments via Stripe are on the roadmap, solving the hardest part: safely handing off agent intent while preserving authorization, fraud controls, and auditability. For developers, ACP provides SDK-style endpoints that make "AI can shop this store" as simple as calling an API, not building custom glue code per merchant. We're running a limited beta while we learn where this breaks in real usage—currently free for smaller stores as we focus on stability and feedback. Early interest has been strongest from merchants selling technical or niche products, where agent-driven discovery actually makes sense. We're live at https://actory.ai and looking for blunt feedback from anyone running Shopify stores, building agents, or thinking about what happens when almost all commerce flows through agents in the next few years.

Visit product View on Hacker NewsDec 24, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, agentic · Missing: mac, macos, cursor

93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: compatible · Missing: supports, reddit linkedin, podcasting

87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: shopify · Missing: arr, mrr, revenue

25%25% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

17%17% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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