Fast move on the workhorse tier. Matters if you build anything agentic 👇 The news: 3.7 Flash launched just three weeks after 3.6, at half the token cost — $0.75/M input, $3.75/M output, locked through Dec 31. The gains are real: → DeepSWE coding: 49% → 65.3% → Reportedly beats Claude Sonnet 5 and GPT-5.6 on coding → 1M context, better multi-step planning and tool calls The bigger move: Gemini Spark — Google's 24/7 personal agent for Pro/Ultra — now runs on 3.7 Flash. The agent working between your sessions just got a real bump, especially for Workspace tasks. My take: Google isn't chasing the frontier crown right now — their flagship 3.5 Pro is still delayed. They're dominating the workhorse tier instead: the cheap, fast, good-enough model you actually run at scale. Smart. Most agentic workflows don't need the smartest model — they need a reliable one cheap enough to run thousands of times. For builders: The intro pricing is a defined window to test cost-per-task before rates double in January. Use it. And this is the price war I keep flagging, now three-way — Claude doubled Cowork limits, OpenAI gamified resets, Google halved Flash pricing. Every lab's fighting for the builder. You win. Stay model-agnostic and ride whoever's cheapest for the job. Caveat: still no EU availability. Check your region first. Running Gemini Flash in any workflows yet, or all-in on Claude/OpenAI? 👇

Sometimes we stay in the "learning phase" for way too long. We keep saying: "I'm doing an AI course." "I'm building projects." "I'm watching tutorials." "I'm preparing." And it feels like progress. But deep down, we know we're spending months learning and building things that may not actually matter. I call this cheap dopamine. If we wanted to learn swimming, we wouldn't spend months watching swimming tutorials. We would jump into the pool, learn the basics, struggle, make mistakes, and slowly get better by actually swimming. I think the same applies to business and freelancing. Instead of spending months learning AI before talking to businesses, we should start talking to people. Understand their problems. - Ask what is costing them time or money. - Ask what happens if they don't solve that problem. - Then figure out what we can offer. Sell the service before building the product. That's probably the hardest part for beginners, breaking the ice and actually talking to people. - You can learn the technology along the way. - The path can be shown to you, but ultimately you have to walk it yourself. Would love to hear how you people are approaching this and what has actually worked for you?

I'm currently building an AI-powered Medical Transportation Management System that includes an Admin Web, multiple Customer/Company portals, driver management, AI scheduling and dispatching, live GPS tracking, route optimization, billing, reporting, and driver mobile/PWA access. I'm also looking to work with startups and businesses that need custom software, web applications, or AI integrations. If you have an idea and need someone to turn it into a working product, feel free to Dm me We can book a meeting.

Hi! I'm a Senior Full Stack and AI Engineer specializing in AI agents, AI automation, Voice AI, LLMs, and CRM automation. I build scalable web applications, integrate third-party APIs, AWS, and Web3, and can take your project from concept to production. If you're looking for someone who can deliver modern, production-ready AI solutions, feel free to send me a DM. I'd be happy to discuss your project. You can find my contact information in my profile

Anthropic has introduced a hidden watermark in text generated by Claude. It’s invisible to readers but can help identify AI-generated content. https://support.claude.com/en/articles/16266773-how-claude-marks-ai-generated-content My take Interesting development. I’m not quite sure what to make of it. Part of me feels it’s solving a problem that may not exist for long. We’re moving toward a world where AI will be involved in almost every piece of content. As the article points out, even if you write something yourself and only use AI to proofread or refine it, the watermark could still be applied. If AI becomes part of everyone’s writing process, what purpose does the watermark really serve? It feels like another regulation that’s trying to keep up with technology.