I’m sorry but…Pattinson walking around like a suave badass, banging hot chicks, beating the piss out of fools, dropping one liners, drinking martini’s, letting his natural British accent fly? With that music behind him? And Villeneuve’s direction??
Who TF doesn’t want this?
Congratulations, Bitcoiners. Six years in, the biggest Bitcoin buyer in the world is sitting at his own cost basis, around $75,500. Saylor promised 30% a year. Gold would have doubled his money. The Bitcoin president just got rejected by the voters. Got gold?
https://t.co/Hq4oTEIara
CANCEL your weekend plans.
The 2027 meta just dropped. You NEED to:
• Build a computer-use agent that parses the DOM, diffs screenshots and maps clicks to coordinates so it can drive legacy software with zero APIs
• Ship generative UI where your LLM returns live React components instead of markdown blobs and watch your product feel 10 years newer
• Wire a System-One router that resolves 95% of requests in milliseconds for fractions of a cent, escalating only the hard 5% to reasoning models
• Kill your `while True` loop and rebuild it as a Temporal state machine that resumes from the exact node after a crash or a 3-day approval
• Write a raw MCP server in pure JSON-RPC so any external agent can call your product with scoped credentials, no SDK required
• Add grammar-constrained decoding so your agent emits 100% valid JSON on the first try, every try, forever
• Build a trajectory grader in CI that blocks the merge the second a tool-call sequence deviates from the golden path
• Ship an inter-agent sanitization proxy that executes prompt injections before they cross a single agent boundary
• Wire a PII unmasking proxy that swaps sensitive data for UUIDs before inference and restores it after with full audit logs
• Add a cost kill-switch that halts any loop projected to exceed $0.50 and degrades frontier → mid-tier → local → cache
• Implement KV-cache prefix sharing at the gateway and cut Time-To-First-Token by 80% on repeated system prompts
• Set up speculative decoding: local 3B drafts, frontier 70B verifies, acceptance rate logged on every single request
• Shadow-route 5% of production traffic to your new model, diff trajectories and cost silently, auto-post the report to Slack
• Automate the DPO flywheel: thumbs-down → preference pairs → nightly LoRA → eval-verified promotion, zero human touch
• Build a voice loop with VAD and sub-1s interruption handling, streaming tokens and tool calls simultaneously
• Ship an API-to-browser fallback that spawns a headless browser the moment a REST endpoint 404s, finishing the job anyway
• Add a WebGPU shim so a 2B model runs in the browser when the cloud dies and your users never see a spinner
• Fuzz your own agent swarm with malformed tool outputs and context overflow until it self-heals without a single pager alert
• Publish one benchmark: your system vs the naive baseline, on cost, latency and task success, fully reproducible
The wrapper era is over. The systems era pays.
You have way too much to do.
Bookmark & Repost.
Companies that offer integrated solutions for local inference will boom in the next few years. I'm not talking about another GPU in a case.
Hardware + OS + an inference stack that makes open models easy to run. A plug-and-play system.
Ease of use is still underrated.