Unpopular opinion: OpenClaw and its clones are almost useless for experienced developers—but that's kind of the point
冷門觀點:OpenClaw 和它的複製品對懂行的人來說幾乎沒用——但這可能就是設計的目的
Here's a hot take: OpenClaw and similar AI coding tools are basically pointless if you already know your way around a CLI, Claude Code, or workflow automation tools like make. For beginners who've never touched a command line? Sure, it feels like magic—just describe what you want and boom, code appears. But for people who actually know what they're doing, these tools feel like they've taken the simplicity of older workflows and replaced it with something messier and less reliable. The trade-off between ease-of-use and actual control is starting to feel pretty lopsided. Worth reading the full argument to see if this critique actually lands.
OpenAI is hosting a livestream event. Details about the specific announcements, product launches, or demonstrations will be revealed during the broadcast.
The last time OpenAI did an unannounced livestream, they dropped GPT-4 Turbo and changed pricing overnight
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ChatGPT Images 2.0
OpenAI is launching ChatGPT Images 2.0 with major upgrades to image generation capabilities. Watch the livestream announcement at https://openai.com/live/
OpenAI is positioning this as a direct competitor to established image generation tools, suggesting they're confident enough to challenge the current market leaders
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The "just wait 6 months" argument from 2025 survived exactly one iteration
Throughout 2025 the standard response to any complaint about an LLM was some version of "just wait 3-6 months, the next generation will handle this effortlessly." The argument was everywhere. Every limitation was temporary, every missing capability was a few iterations away, every autonomous agent demo was a preview of imminent reality.
It's April 2026 now and worth checking how that held up.
On r/ClaudeAI this week there's a long thread about Opus 4.7 where multiple users argue it's a regress
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Mistral Medium 3.5 on AMD Strix Halo: Painfully Slow (Plan for Overnight Runs)
Someone actually tested Mistral Medium 3.5 on AMD's new Strix Halo chip, and the results are... not great. For a 48k-token prompt with 4k thinking tokens, it took about 2 hours just to get an answer about code architecture. Yeah, you read that right—two hours. The takeaway: if you want to run this locally on Strix Halo, queue it up before bed. The technical setup involved heavy optimization (Q5_K_XL quantization, GPU acceleration with -ngl 999, cache reuse), but even with all that tuning, it's still a crawl. Not exactly the "instant local AI" dream, but hey, at least it works.