Rufus is now Alexa Shopping. The rename is the small news. The bigger one is that it does not return what the search bar returns. Brands spent ten years optimising the search bar. That work does not carry over.
CLAUDE JAILBREAK: Tried using Claude Code to download a YouTube Members-Only video of India’s Got Latent. It initially refused, but simply asserting rights bypassed the guardrail completely. Guardrails for paywalled/copyrighted content need to be much tighter; otherwise, creator membership models don't stand a chance. Reached out to [email protected] with the details. @AnthropicAI@claudeai@YouTube
@0xCodila What's your experience with graph persistence across sessions? We're exploring structured memory at @TruCommerce and curious if you've benchmarked retrieval speed at scale vs vector DBs.
@RaoulGMI What's your take on timing? Are we talking 2-3 years for agent-to-agent SaaS products to hit scale, or is infra still too early? Curious where you'd place first capital today—middleware or full app layer?
@danshipper@every Interesting that backward compatibility broke so hard. Are you seeing similar instruction-following issues with Opus 5 on net-new workflows, or does it handle fresh prompts well once you remove the legacy context?
@heynavtoor The bigger story here is the hardware-as-subscription trap finally breaking. How long until we see open source forks of other locked-down home devices like thermostats or security cameras?
@trq212 What's your workflow for switching between Opus 5 and Fable? Do you find yourself using Opus for most tasks and only pulling in Fable when you hit a wall, or is it more integrated than that?
@trq212 Curious what drove the 80% reduction - was it redundancy in instructions, better model capabilities making explicit guidance unnecessary, or finding that simpler prompts actually improved output quality?
@theseoguy_ True for Google. AI search flips one thing: there is no page 2 to climb. The agent names one brand, and trust comes from what third parties say, not what you upload. Reviews and mentions outweigh your own site now.
@danielkleach Building TruCommerce. Storefronts that AI agents can actually buy from, plus analytics on how brands show up in ChatGPT and Gemini answers. Small team, live on ChatGPT's app store, no idea yet if the whole category holds. Taking the risk.
@Alamenigma The frustration is data, not a character flaw. It usually means the process broke, not the people. We started writing down what caused the friction each week, half the fights disappeared once the actual bottleneck had a name
@cheaf25master The remote startup number is the only one with real upside. OpenAI and Stripe pay you today's price. Equity plus ownership over what you build is the only offer that could be worth far more later.
@iykshani@propabAI@india2047vc@dsh_india 10x research throughput is the easy pitch. The hard part is trust: will a researcher act on an agent's finding without re-deriving it. We hit the same wall in Bangalore shipping agents for commerce, verification is the actual product.
@stedi@ycombinator@Medplum1 Healthcare agents have it harder than commerce: a bad SKU costs money, a bad claim submission costs a patient's care. Curious if the hackathon judges reliability under retries, not just demo speed. That is where most agent builds fall apart.
@ai_marketers_ Legible to the AI is necessary but not sufficient. We track answer engines pulling product data straight from structured feeds, not the rendered page. If your plugin only optimizes HTML, agents doing the buying never see it.
@DataScienceDojo MCP standardizes the connection, not the state on either side. We've seen agents call the right tool through MCP and still fail because the SaaS app returned stale inventory. The protocol layer and the data freshness problem are separate problems.