标签：#p

The next Model Context Protocol specification, 2026-07-28 , is the largest revision since the protocol launched. The release candidate locked on May 21, 2026, and the final spec publishes on July 28. It contains breaking changes to transport, authorization, and how tool schemas are handled. A server that is correct against 2025-11-25 today is not broken. Nothing here is a present-tense vulnerability. But several of these changes are security properties, not just compatibility ones — request routing integrity, cross-user cache scope, and schema-driven fetch behavior all move under this revision. This checklist walks the changes a server operator needs to handle before July 28, and calls out the security implication wherever there is one. Everything below describes the release candidate. Treat specifics as subject to change until the July 28 final, and validate against the official spec before shipping. Transport: the stateless core This is the headline change. MCP becomes stateless at the protocol layer, and most of the migration work lives here. The handshake and session are gone The initialize / initialized handshake is removed (SEP-2575). Protocol version, client info, and client capabilities no longer get exchanged once at connection time — they travel in _meta on every request. The same SEP adds server/discover as the new discovery anchor: servers must implement it, and clients fetch server capabilities from it when they need them up front. Once the handshake is gone, a server that can't answer server/discover can't be negotiated with. The Mcp-Session-Id header and the protocol-level session it carried are also removed (SEP-2567). Any request can now land on any server instance. The sticky routing and shared session stores that horizontal deployments relied on are no longer required at the protocol layer. If a server needs state across calls, mint an explicit handle from a tool — a basket_id , a browser_id — and have the model pass it back as an ordinary argumen

"Intelligence isn't about searching everywhere—it's about knowing where not to search." Artificial Intelligence is often associated with neural networks, large language models, and autonomous systems. But long before modern generative AI, computer scientists were solving a much deeper question: How do intelligent systems make decisions efficiently? Whether you're building search algorithms, recommendation systems, autonomous robots, or distributed systems, the architecture of intelligence teaches timeless lessons about solving problems under uncertainty. Let's explore five powerful ideas that shaped AI—and why they matter far beyond computer science. ✈️ 1. The Pilot's Dilemma: Why Blind Search Fails Imagine you're a pilot. Suddenly, one of your engines fails. In the next few seconds, there are hundreds of switches, buttons, and controls available. If you treated every control equally, you'd spend precious time trying random combinations. That is exactly how uninformed search works. Algorithms like: Breadth-First Search (BFS) Depth-First Search (DFS) have no knowledge of where the solution might be. They simply explore. Start ├── Option A ├── Option B ├── Option C └── ... The larger the search space becomes, the less practical this strategy is. A pilot doesn't blindly flip switches. They use additional knowledge : Engine pressure Fuel flow Hydraulic readings Warning systems Those clues dramatically reduce the number of possibilities. This is exactly what AI calls Informed Search . Instead of exploring everything, intelligent systems use knowledge to eliminate impossible paths before searching them. 🧠 2. Heuristics: The Cheat Code of Intelligence The secret behind informed search is something called a heuristic . A heuristic is simply an educated estimate. Mathematically, h(n) represents the estimated cost from the current state to the goal. One important rule always holds: h(goal) = 0 Once we've reached the goal, there's no remaining cost. Example: Finding Bucharest

You don’t have a naming problem. You have a 40‑minute decision problem. Here’s a practical, timer-based method to name your SaaS in 2026, without spiraling into a 3‑week Notion rabbit hole. Ground rules for 2026 A few constraints you can’t ignore: .com is crowded. There are around 157 million .com domains registered globally as of 2026, so the obvious one-word .com you want is almost certainly taken or expensive. What is .com domain Domains cost real, recurring money. Typical 2026 guides put standard TLDs at about $10–18/year to register and $14–20/year to renew for .com , and $12–18 / $14–20 for .net/.org . Domain name statistics How much does a domain name cost? Good .coms are often not $10. Clean, short, brandable .com resales routinely land in three to five figures , which is why many early SaaS founders default to modified names or non-.com extensions. How much does a domain name cost? AI-era TLDs are legit now. Investors report 69% positive sentiment toward .ai and 64% toward .io , so those are no longer “hacky” domains; they read like normal startup brands. A look at who invests in domain names .ai is basically a global startup extension. It’s widely described as a “global AI branding extension” and used by SaaS far beyond Anguilla now. .ai TLD explainer The domain space is huge. Roughly 386.9 million domains were registered worldwide by end of 2025, up ~6.2% YoY. Most popular TLDs Your first idea is probably used somewhere. Prices are drifting up, not down. ICANN raised its per-domain fee from $0.18 to $0.20 in mid‑2025, and that cost is now baked into 2026 retail pricing. Domain name market trends So: stop hunting for a perfect single-word .com at $12. Optimize for speed and defensibility , not romance. Set a timer for 40 minutes. Follow this. Minute 0–5: Positioning, not poetry Open a blank doc. In 5 minutes, write three bullets : Who you’re for (ICP in one line). What painful outcome you fix. What “shape” of product you are (API, analytics tool, ops dashb

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Block, Inc. describes migrating ~450 JVM repositories into a monorepo across Cash App and Square engineering to reduce dependency drift and coordination overhead. The system supports ~8,800 weekly builds with ~10 min p90 CI time. The approach improves cross-service changes, build visibility, and developer experience through dependency graph–based builds, selective CI, and custom IDE tooling. By Leela Kumili

Luca Guadagnino's film about OpenAI CEO Sam Altman, Artificial, has reportedly been dropped by Amazon MGM. The film, which stars Andrew Garfield and covers the rollercoaster five days in 2023 spanning Altman's termination and reinstatement as CEO, had been in the works for about a year. The cast also includes A Complete Unknown actress Monica […]

This is Optimizer, a weekly newsletter sent from Verge senior reviewer Victoria Song that dissects and discusses the latest gizmos and potions that swear they're going to change your life. Opt in for Optimizer here. On TikTok, the tanned youths are explaining why they no longer wear sunscreen. In one video, a young man films […]

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A French launch startup is scrapping the name of its rocket, apparently due to a trademark issue.

Internmaxxing Somebody on your timeline this week called intern code "API slop."...

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