Anthropic Opens Claude Interactive Charts and Diagrams Beta
AI Product Management Certification
Today's top 25 insights for PM Builders, ranked by relevance from X, YouTube, LinkedIn, and Blogs.
Anthropic Opens Claude Interactive Charts and Diagrams Beta
#1 š
Claude now builds interactive charts and diagrams directly in-chat, rolling out in beta across all plansāincluding free.
#2 š
Philipp Schmid rolled out experimental spend caps for the Gemini APIālimits take up to 10 minutes to activate (email alerts coming soon)āand asked users to set caps and share feedback.
#3 š
Sundar Pichai launched Ask Maps, an AI-powered chat interface in Google Maps for personalized recommendations and route planning, and unveiled immersive 3D navigation with Street View overlays for real-time guidance.
#4 ā¶ļø
Replit Agent 4 Is Here: Everything You Need to Know
Peter Yang
Building and publishing a full-stack mobile habit-tracker app on Replit using Agent 4 to generate design variants on an infinite canvas, build calendar and habits tabs with parallel AI agents, and deploy with one-click publishing.
- Four design variants (Glass Morphic, RPG Quest, Botanical, surprise) were generated on Replit Agent 4ās infinite canvas in about two minutes.
- Two AI agents built the calendar and habits tabs in parallel, completing coding in roughly five minutes and tracked via a Trello-style taskboard with draft, active, ready, and done columns.
- The full-stack app (frontend, backend, database) was published on Replit with a built-in security scan and deployed in one go.
#5 š
Mustafa Suleyman launches Copilot Health, a secure AI-powered hub that connects usersā EHR records and wearable data to deliver personalized medical insights and proactive health nudges, heralding the dawn of medical superintelligence.
#6 š
AI at Meta launched Canopy Height Maps v2 (CHMv2), an open-source, high-resolution global forest canopy mapping model co-developed with @WorldResources that leverages our DINOv3 Sat-L vision model to deliver major gains in accuracy, detail, and consistency.
#7 š
Google Research expanded its global flood forecasting coverage by launching an AI-driven urban flash flood forecasting system, combining high-resolution precipitation nowcasts with hydrological models to deliver real-time, city-scale flood alerts.
Also covered by: @Google Research
#8 š
Sundar Pichai rolled out an AI floodāforecasting model that predicts urban flash floods up to 24 hours ahead, backed by Groundsourceāa Geminiādriven dataset of 2.
Also covered by: @Google Research
#9 š
Sebastian Raschka launched a āBuild an LLM From Scratchā YouTube series, walking through data prep, transformer architecture implementation, training and fine-tuning to create custom large language models.
#10 š
LlamaIndex š¦ launched āagenticā OCR, a goal-driven, multimodal document parser that uses visual grounding and self-correction loops to adapt to layout changes and trace every field back to its source.
#11 ā¶ļø
7 new open source AI tools you need right nowā¦
Fireship
Demonstrates seven open-source AI toolsāAgency, Prompt Fu, Mirrorish, Impeccable, Open Viking, Heretic, and Nano Chatāto streamline AI agent orchestration, prompt testing, prediction engines, UI design, context management, model de-censoring, and custom LLM training.
- Prompt Fu acts as a unit-testing framework for prompts, benchmarking them across different models and performing automated red-team attacks to expose prompt injection vulnerabilities.
- Impeccable includes 17 front-end design commandsāsuch as
distillto simplify interfaces,colorizeto apply brand palettes, andanimateplusdelightfor custom UI animationsāto rapidly improve app design. - Nano Chat implements the full LLM pipeline (tokenization, pre-training, chat fine-tuning, evaluation, and a web UI) and can train a small language model for about $100 in GPU time.
#12 š
There's An AI For That highlights Modulate.aiās new, cost-effective speech-to-text API, complete with a built-in comparison tool against Deepgram, ElevenLabs, and AssemblyAI.
#13 š
Cursor introduced a novel scoring method for agentic coding tasks, benchmarking its models on intelligence and efficiency. The frameworkās comparative results reveal each modelās performance trade-offs.
#14 š
Tal Raviv looped Claude into a weekend notification-design brainstorm by holding down the dictation button to feed it bottom-line points in real time, and Claudeās targeted questions kept their creative momentum flowing.
#15 in
Marc Baselga recommends quantifying the cost of slow AI adoption (missed markets, lost deals, compliance delays) and enlisting a senior IT- or C-suite sponsor to push for safe approval of broader AI tools beyond just Copilot.
#16 š
Guillermo Rauch launched āAgent-native Flagsā in the Vercel CLIāa new CLI + Skill integration that lets you manage feature flags programmatically and is optimized for AI agents.
#17 š
Santiago keeps each Claude chat in its own terminal tab per project and uses claude --continue to pick up after closing or --resume [session id] to jump to specific sessions, all without plugins.
#18 š
Santiago applauds an SMS-based AI assistant that forgoes inbox access and full upfront data dumps, instead building context incrementally from your actionsāunlike most AI helpers.
#19 in
Wade Foster spotlights Claire Voās no-code āSunday Scariesā agentābuilt in an afternoon with Zapier and a prompt to auto-prep her calendar, meetings, and school drop-offsādriving ChatPRD to 100k+ users with just her and one engineer.
#20 š
Yann LeCun says their planning world models are action-conditioned (hence truly causal), reviving 1950s optimal-control ideasāand that training such models from raw sensory inputs like video demands new techniques.
#21 in
Dharmesh Shah is proposing a simple, standard āFile System Protocolā that lets AI agents navigate and use hierarchical data storesāarguing that, like with CLI tools, coding agents already excel at understanding and searching file-system structures.
#22 š
Aravind Srinivas says Slack will become the enterprise AI interface and Perplexity Computer slots in naturally. He predicts future multi-billion- and trillion-dollar Slack-based companies will delegate more tasks to AI than to humans.
#23 š Simon Willison
Coding After Coders: The End of Computer Programming as We Know It - Clive Thompson's NYT Magazine feature examines AI-assisted development, interviewing many software developers; Simon Willison appears as a source highlighting that programmers can tether AIs to reality by requiring tests. The overall tone captures the industry's changes and leans toward cautious optimism.
#24 š Simon Willison
Grief and the AI Split - Les Orchard argues that AI-assisted coding exposes an existing divide among developers: some will embrace machines to direct work, others will continue hand-crafting code for the craft itself. The post frames this as a visible fork in developer motivations.
#25 š
Guillermo Rauch: Vercel now powers Notionās agent platform via Notion Workers on Vercel Sandbox, merging natural-language specs with data integrations. He believes this positions Notion as one of the big winners in the agent era.