
Lucy Chen
253 posts

Lucy Chen
@el09xc
OSS AI Investor | Public OSS Investment Scorecard V1.2 🧪 | Singapore Top VC EIR | Helping builders evaluate open source AI & VCs find the next 10x | Taipei | g





With the fast codex, I feel like now I'm just waiting for tool calls to happen, especially Playwright MCP feels particularly obnoxious with completely insane output lengths which kill the context. Anything better to do here? Just not use it?



AI has become the justification for every layoff. It's the perfect excuse card, but there is a lot of spin involved. Every layoff is some combo of the following five very different AI stories. 1. Nothing changed, we just realized we have too many people. We are going to blame AI, but we are bullshitting. This is the AI as an excuse; it was really sloppy hiring, and we are just blaming AI. (See Block) 2. Growth has gone away so now we have too many people. This may be because of AI if you are a SaaS company. All the customer love is now going to AI. But it's less AI as a productivity lift, and more about you just building a less ambitious growth company. (See Salesforce and most every SaaS company) 3. We spent our money on capex to build AI so now we can’t afford as many people. Management may say it’s about AI making us productive (4 below) but my gut is a lot of it is about Nvidia getting our money so now there is none for you. (See Meta and Oracle) 4 We are really using AI the way god intended us to. We don't need as many people. This is the ONLY version of the story that is actually about a productivity increase. It's real, it's happening, but I wonder if it is even the majority of the layoffs. (See some software engineering departments right now) @jasonlk raised a fifth reason that doesn't get talked about enough: we just have the wrong people. Maybe we don't need 20 engineers who all know C++, but rather eight who have strong AI skills. This I think should be happening everywhere. Every time a layoff announcement comes out, I try and mentally categorize per the above.








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For $20/month and zero setup, you can now run parallel AI agents that deliver finished work while you sleep. Perplexity shipped Computer. Back on Ramp's fastest-growing B2B software list. 19+ AI models. 400+ connectors. The reason isn't search anymore. Every take I've seen focuses on the "AI assistant" framing. They're all underselling it. Computer doesn't give you suggestions. It delivers the finished thing. Research reports with source citations. Deployed dashboards with shareable links. Cleaned datasets with charts. Launch kits with positioning docs and email drafts. Three things make it different from everything else out there. Cloud execution, so your laptop can be closed. Parallel agents, so five tasks run simultaneously. And persistent memory, so you stop re-explaining yourself every session. I pointed it at Notion's product pages. 28 pages scored across 5 criteria, competitive benchmarks against Coda and Slite, with specific recommendations per page. That's a $15K messaging audit. Took about 20 minutes. But credits disappear fast if you don't know how to prompt it. I burned hundreds learning this. Built a five-rule Prompt Spec that cuts cost by 60%+. I spent weeks testing it. Today's guide has the six PM use cases, exact prompts, the credit-saving system, and an honest comparison against Claude Code, Cowork, and OpenClaw. Full guide: news.aakashg.com/p/perplexity-c…
















