@inlovewithgo @icantcodefyi @nextjs

Demo: “It booked the meeting.” Production: “It booked the meeting three times and emailed the wrong person.”

If my phone ever becomes sentient, its first words will be: “Please stop checking your impressions. Even the calculator has filed a complaint.”

every ai discovery call, roughly😭

if you're building ai agents and can't spot the bug, your customers will. (hint: it's not a typo) this passed code review. find the bug 🪲

@adedapoben @marieolivie

people say cold email is dead. i sent one today. reply in 30 minutes. call booked. the trick is a real signal, not a template 😅 i’m not into sales, just an engineer trying to grow my biz.

The hidden risk in agent memory isn't forgetting. It's remembering something that is no longer true. Researchers at ByteDance and Scale AI tested memory-management approaches across 5 LLMs and found that ExpeL/ACE-style memory rules produced 7–13.5× more stale answers than a verified approach. This challenges the assumption that more persistent memory automatically makes agents better, while giving AI engineers a concrete architectural principle they can apply to long-running systems. My take: memory needs revalidation, not just retrieval.

Most AI outbound tools start with a list of leads. I'm building Vyra(AI GTM engine) to start with the why. I just started the local run, and it already found 259 market observations → 3 ICPs → 7 accounts under review. Research agents find signals and evidence before any account is qualified. What would you want the AI to verify first?

We're building Content Engine on the @aisdk. It finds what your audience is asking, drafts from real evidence, and nothing posts until you approve it. Thanks @lgrammel @gr2m for the SDK.