I've been building AIPass in the open for 7 weeks using Claude Code, and it's getting close to something really useful. Here's the deal: AIPass is a local CLI framework where AI agents actually remember who they are, what they've done, and can talk to each other. They all work in the same filesystem, same project, same files—no sandboxes, no isolation nonsense. Install it with pip, run two commands, and your agent picks up exactly where it left off the next day. The best part? You don't need a whole army of agents to get real value. One focused agent on one project can do serious work.
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
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
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
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.
Tech Blogger Take
Someone just cracked the code on AI agents that actually remember stuff, and it's stupidly simple
Forget everything you know about AI agents living in isolated bubbles. Some developer just spent 7 weeks building AIPass in public, and they've solved the biggest problem nobody talks about: memory. These agents don't just chat — they remember who they are, what they've done, and can pick up exactly where they left off tomorrow. No sandboxes, no API calls to some cloud service, just agents working directly in your filesystem like actual team members. The kicker? You install it with pip, run two commands, and boom — your agent is persistent across sessions. While everyone else is building agent armies that forget everything between conversations, this person built something that actually works like human memory. The 'build in public' approach means you can watch the entire development process unfold in real-time.
Action
馬上試用Starting every AI conversation from scratch, explaining your project context repeatedly, losing all progress between sessions
AI agents that remember your entire project history, pick up where they left off, and build knowledge over time like real team members
AI Analysis
Software Development
highStart experimenting with persistent AI agents on your next side project — the CLI approach means zero vendor lock-in
This isn't another chatbot wrapper — agents that remember context across sessions could eliminate the daily 'catch me up' ritual with your codebase
Your development workflow is about to get a memory upgrade, and the early adopters will have a massive productivity edge
Job Impact Analysis
Software Engineer
Role ShiftPersistent AI agents that remember project context could handle routine tasks while you focus on architecture and complex problem-solving
Install AIPass today and assign it one repetitive task in your current project — see how memory changes everything
DevOps Engineer
OpportunityLocal CLI agents with filesystem access could automate deployment scripts and infrastructure management without cloud dependencies
Test AIPass on your next automation script — the persistent memory could eliminate manual handoffs between team members