Google looks like it’s prepping a credit-based usage system inside the main Gemini app, plus a new images section that hints at stronger built-in image tools. - Credit pool instead of fixed caps, easier to plan heavy usage - Monthly allowance across models and features, option to top up when you run out - Brings Gemini closer to the consumption style we already see from OpenAI and Anthropic - Makes it simpler for Google to add premium features without forcing a huge plan jump - Matters for agentic workflows, Deep Research, Deep Think, and long multimodal sessions that chew through compute - New dedicated Images section in the web UI, could mean improved image generation or even an in-app editor - Fits Google’s bigger move to unify billing across Gemini, AI Studio, Flow, and other tools, which is great if you are automating across multiple surfaces Read the full article here: https://www.testingcatalog.com/google-prepares-credit-system-for-gemini-and-new-image-tools-2/

DeepSeek just released their V4 models, bringing massive 1M context lengths and powerful agentic capabilities to the table for us to build with, all at a fraction of the cost. Here is why this matters for your workflows: - 1M context length default for all official services - DeepSeek-V4-Pro for top tier reasoning vs V4-Flash for fast and efficient tasks - Seamless integration with OpenAI and Anthropic API formats - Pricing comparison: DeepSeek V4 at $1.74 input and $3.48 output per million tokens versus Claude Opus 4.7 ($5/$25) and GPT 5.5 ($5/$30) Read more: https://api-docs.deepseek.com/news/news260424

I canceled my Gamma subscription today haha Anthropic just launched Claude Design, a research preview tool where you collaborate with Claude to create polished visual assets like prototypes, slides, and one-pagers, then refine everything through chat. - Powered by Claude Opus 4.7 vision model, so it can actually “see” and work with visual layout - Starts from prompts, uploads (DOCX, PPTX, XLSX), images, or even your codebase, more paths from idea to output - Builds or applies your design system during onboarding by reading code and design files, consistent branding without manual cleanup - Inline comments, direct edits, and adjustment sliders, tighter feedback loops and less back and forth - Turns static mockups into interactive prototypes without code review/PRs, faster validation before engineering time - Exports to Canva, PDF, PPTX, HTML, easier handoff to the rest of the stack - One-step handoff bundle to Claude Code, hinting at a real design to build automation pipeline - Organization-scoped sharing and group collaboration, teams can iterate live in the same doc Read the full article here: https://www.anthropic.com/news/claude-design-anthropic-labs

Recently worked on an AI system for a music industry website redesign. There were two parts to it: 1. A public-facing AI chat widget for general queries + lead capture 2. A private, full-screen AI assistant inside the client portal. The second one was more interesting. The client didn’t just want “AI support” — they were concerned about users overusing it and burning unnecessary tokens. So instead of a typical chatbot, I designed a session-based interaction system: - Each user gets a 5-minute active window - At minute 4 → a warning is triggered (“1 minute left”) - At minute 5 → session ends + redirects to an external GPT - Then a 5-minute cooldown kicks in - After cooldown → user can start again It basically runs in a loop. What’s interesting is how this changes behavior: Users become more intentional with their questions instead of treating it like an endless chat. Also ended up optimizing one of their internal workflows in the process: A task that used to take ~6 hours manually is now done in under 10 minutes. No fancy theory here—just structuring AI usage in a way that actually makes sense operationally. Still experimenting with how far this “controlled AI interaction” approach can go.

Anthropic just dropped Claude Opus 4.7 and it is a massive win for anyone into automation. This new update is a major leap forward that focuses on turning Claude into a reliable agent that can handle complex projects from start to finish with way less babysitting. - Hand off the hardest coding tasks with total confidence because it now double checks its own work before reporting back. - Vision capabilities have tripled to support high resolution images up to 2576 pixels for reading dense screenshots or diagrams. - New adaptive thinking lets the model spend more time on hard problems while staying fast on the easy stuff. - Professional taste is built in to help you create higher quality slide decks and user interfaces that actually look good. - Advanced memory helps it remember important notes across long sessions so you don't have to repeat yourself. - The xhigh effort level gives us finer control over the tradeoff between deep reasoning and response speed. - $5/million base input tokens and $25/million output tokens Read more: https://www.anthropic.com/news/claude-opus-4-7