I've spent the last few months testing coding agents on real software, and one thing kept bothering me: They're way too good at declaring themselves done. So I built Cycle. It freezes the candidate, runs real verification, sends it to two blind reviewers, and lets an independent arbiter decide if it can ship. No self-approval. No “tests pass” without evidence. Cycle finally has a home: runcycle.dev

If @antigravity 2.0 ships native computer use, I’m wiping out 80% of my AI subscription stack overnight. Zero need for five different point solutions when the agent runtime can actually touch the OS. My entire setup would collapse into just two players: Google as the primary execution engine and daily driver Anthropic reserved strictly for high-tier escalation Ball’s in your court @demishassabis @OfficialLoganK @JeffDean @sundarpichai @GoogleDeepMind. Give us the keys to the desktop and take our money.

As a user and advocate of the @Google ecosystem, one thing is clear: OpenAI’s speed of execution is setting a new standard. Google has unmatched scale and proprietary infrastructure, but @OpenAI is capturing actual work habits by turning ChatGPT into a full-fledged workspace. The challenge for Mountain View isn’t compute, it’s product agility. Can Google’s sheer distribution overpower OpenAI’s enterprise traction, or is the lead already too wide?

Today is going to be a rough day for the people running nearly 70% of the web. PHP has announced two critical security vulnerabilities (CVSS 9.2/10), with emergency patches scheduled for today. php.net/archive/2026.php#202…

Pretty soon all AI models will be roughly the same. At that point, the only things that’ll matter are distribution and who can drive costs down the furthest. My money is on @Google winning this.

I’ve been testing @GeminiApp 4 Argon in @antigravity non-stop for the past 6 days. It’s an absolute beast, but man... it burns through tokens like a rocket engine. So, I built a lightweight open-source plugin to bring an "Advisor Mode" to Antigravity routing tasks smartly so Argon only steps in when truly needed. Result? ~85-90% token savings. Check it out and let me know what you think: 🔗 github.com/jannotix/advisor-… cc: @OfficialLoganK @GoogleDevs #GoogleAntigravity #Gemini #AI #OpenSource

I’m a die-hard @Google fan. As a CEO, my entire company runs on @GoogleWorkspace , @googlecloud, and @antigravity . Yet for daily coding, I STILL can't leave @AnthropicAI. Here is the brutal truth @sundarpichai @demishassabis @OfficialLoganK need to hear: 1. The Missing Middle & Routing: @GeminiApp 4 Argon is a beast, but it burns way too many thinking tokens for daily coding. Anthropic has a full pyramid (Fable, Opus, Sonnet, Haiku) + the /advisor flow (Sonnet codes, Opus architects). Google can't just give us Flash and a nuclear reactor like Argon with nothing in between. 2. Broken B2B Billing for Antigravity: I already pay for Google Workspace. Why doesn't it unlock Antigravity? Why do I need consumer "AI Ultra" plans that can't be managed as a Team, OR risk a dev burning €5,000/mo on raw Cloud APIs? 3. Zero Limit Transparency: Stop hiding behind vague "weekly caps" on Argon. If I’m buying seats for my engineering team, I need transparent numbers, not a black box. What @GoogleDevs needs tomorrow morning: - A true Antigravity Team/Seats Plan (flat rate per dev, like @claudeai Team & @OpenAI) - Native Argon-as-Advisor + Flash-as-Executor auto-routing - Transparent token/message limits before we swipe the corporate card Devs & CTOs: are you trusting raw APIs for your team, or sticking with Claude seats until Google fixes this? 👇

I tested @GeminiApp 4 Argon. To me, it rivals Astra and Fable, but is just as token-hungry. I still prefer @OpenAI and @AnthropicAI: Sol 6.1 and Sonnet 5.5 make daily use more practical. @Muse Wonder impressed me most. A @Meta desktop app with a real GUI could reset price/performance.

This is exactly the kind of @WordPress update I like to see. WordPress 7.2 Beta 1 lands October 20, with the new Ipsum default theme and design tools expanding across almost every Core block. WordPress keeps evolving from “just a CMS” into a much more capable application and design platform. If you build on WordPress, this developer roundup is worth reading.

Finally. This is what product distribution looks like. Cursor is now part of The X Subscription: → one subscription → one usage pool across Cursor + Grok → Grok Build → Grok API → Grok Bot on higher tiers → 2× coding usage when using Grok models This is exactly what I’ve been waiting to see. A great model alone is not enough. You need to put it everywhere developers already work and make the entire ecosystem feel like one product. X + Grok + Cursor is becoming a distribution machine. Third-party models moving to API pricing also makes the strategy obvious: keep them available, but make Grok economically irresistible inside the ecosystem. This is how you turn an AI model into a platform. Great move by @elonmusk and the @cursor_ai team.

I think the next @Zai_org model could surprise a lot of people. Everyone is watching parameter counts, but the more interesting signal is somewhere else. Z.ai is now openly working toward Recursive Self-Improvement: GLM is already helping build the infrastructure used to create the next generations of GLM. They’re not claiming fully autonomous self-training yet, but the direction is clear. And honestly, GLM is still massively underrated. I use a lot of frontier models in real engineering work, and for me GLM is one of the very few model families that consistently feels close to Claude and ChatGPT while remaining dramatically more aggressive on cost and openness. If Z.ai gets the next jump right, a lot of people may suddenly realize they weren’t watching closely enough. The next GLM could be the release that changes the perception of Chinese frontier AI.

We’re entering the golden age of startups and developers. AI is collapsing the cost of building software. The scarce resource won’t be code anymore, it will be ideas, judgment, distribution and execution.

Tublat is now part of the @claudeai Startups program by @AnthropicAI. We already use Claude heavily across engineering and AI. Now we build faster. Thanks to the Anthropic team for having us. 🚀

Sometimes the messages that mean the most as a founder aren’t from customers, investors or metrics. They come from the people building the company with you. I asked one of our DevOps engineers what he genuinely thought about what we’re building at @tublatglobal and about the philosophy behind it. This was his answer. What makes me proud isn’t the compliment. It’s seeing the culture understood from the inside. Zero assumptions. Empirical proof. Performance measured, not claimed. Reliability engineered, not marketed. We’re still building. We still have a lot to improve. But this is exactly the kind of company I want Tublat to become. A company where infrastructure is treated as engineering, not a commodity. And where the people building it actually believe in what they’re building.

People think @OpenAI and @Anthropic are fighting the same war. They aren’t. ​OpenAI is going straight for @Google’s throat: consumer discovery, agentic search, the ultimate front-end. @AnthropicAI is quietly securing the enterprise backbone: deterministic reasoning, deep infrastructure, mission-critical B2B. ​One replaces the browser. The other runs the Fortune 500. ​This is exactly why Google is happily backing Anthropic and rolling @claudeai straight into @antigravity. Anthropic doesn’t threaten Google’s search ad monopoly, they just monetize Google’s cloud and dev ecosystem. ​The enemy of your enemy is your best platform integration.

The real win here isn't just "putting AI into WordPress" it's turning @WordPress into a native backend for AI agents via a standard protocol. Fewer webhook hacks, zero custom wrappers, maximum interoperability. Finally, the legacy ecosystem meets the modern stack the right way. Congrats @automattic 🚀

Just fed @tublatglobal product roadmap into an LLM for an honest estimate. ​The AI: "You're looking at a 5-year build." The team: "Cool, so we ship before April?" ​Compressing decades into quarters. LFG. 🚀

I’ve been saying for months that @GoogleDeepMind had all the pieces to eventually take the AI lead. Gemini 4 Argon just made that prediction look a lot less crazy. 77.9% on DeepSWE v1.1 #1 on AutomationBench 1M output token limit $2/M input $10/M output during the introductory period And Google is doing this while owning the entire stack: models, TPUs, Cloud, infrastructure and global distribution. I wouldn’t call the AI race over, independent evaluations still matter, but Argon looks like one of the strongest frontier releases we’ve seen. Huge congratulations to @sundarpichai, @GoogleDeepMind and the entire team. Google arrived later than many people wanted. But I’ve always said it: when @Google finally arrives, it tends to arrive with the whole stack behind it. Now I really want to get Argon into production workloads.

Credit where it’s due: @sama @OpenAI, usage on the Business plans has improved a lot lately. I’ve been pushing the models hard for real engineering work, and the difference is noticeable. I can’t speak for the personal plans yet, but on Business the experience feels much more usable and predictable than it did a few months ago. Great models are only useful if developers can actually keep them working. Please keep moving in this direction.