Google Demos Doodle-to-Code in AI Studio

#1 𝕏

Google AI turned a hand-drawn sketch into a weather-responsive outfit selector app using Google AI Studio and Nano Banana, demonstrating how you can generate working software from a single doodle.

#2 𝕏

Logan Kilpatrick launched Tab Tab Tab, a new prompt autocomplete engine in Google AI Studio’s Vibe coding experience, letting Gemini flesh out your fuzzy ideas on the fly.

#3 𝕏

clem 🤗 OCR’d 27,000 arXiv papers into Markdown using an open 5 B model with 16 parallel HF Jobs on L40S GPUs and a mounted bucket—cost $850, ~29 hrs, 0 crashes—now powering “Chat with your paper” on Hugging Face.

#4 𝕏

Philipp Schmid shares 8 practical tips for crafting and managing agent skills—from identifying essential skill types to knowing exactly when to retire outdated ones.

#5 𝕏

Guillermo Rauch says Workflows makes sloppy, unreliable tasks reliable, serving as his default for long-running executions with up to 13-minute steps, built-in observability and retries, and it’s OSS and backend-agnostic.

#6 📝 Anthropic Engineering

Quantifying infrastructure noise in agentic coding evals - Anthropic examines how infrastructure configuration affects agentic coding benchmarks and shows that environmental variability can change benchmark results by several percentage points. The post highlights that such noise can be larger than the leaderboard differences between top models and argues for careful measurement and control.

#7 📝 Doug Turnbull

What is psuedo-relevance feedback? - Introduces pseudo-relevance feedback: after an initial BM25 or ranked retrieval, the returned results provide implicit information that can be used to refine queries or improve subsequent retrieval. The post outlines how to leverage those initial results as a source of feedback to boost relevance.

#8 𝕏

DeepLearning.AI introduced TTT-E2E, a method that updates language model weights during inference to learn from context. It delivers stable accuracy and constant processing time on long inputs, traded off against more complex, slower training.

#9 𝕏

Google Research introduced Vantage, a GenAI-powered tool that dynamically steers simulated conversations to assess “future-ready” skills like collaboration, and in a New York University study it scored on par with human experts.

#10 𝕏

Santiago introduces a shared memory layer that spans sessions to log prompts, tool calls, decisions and traces in a searchable team database. He argues this infrastructure is critical to prevent agents from forgetting past work.

#11 𝕏

dharmesh proposed tracking developers’ calls to non-existent API endpoints as “votes” to guide and prioritize future API design.

#12 𝕏

Rowan Cheung Microsoft’s GigaTIME AI transforms $10 microscope slides into advanced imaging, using training on 40 million cancer cells and data from 14 000+ patients across 51 hospitals.

#13 𝕏

Boris Cherny shows that while you can configure Claude to block node_modules, in practice allowing it to read your dependencies’ source code often yields more helpful insights.

#14 𝕏

Andrew Ng invites you to the AI Developer Conference (April 28–29, San Francisco) on “The Future of Software Engineering,” arguing that AI-driven coding will shift the main bottleneck to product decision-making (the “Product Management Bottleneck”) and reshape team structures...

#15 𝕏

Tal Raviv calls for “context engineering as a team sport,” giving every team member’s AI assistant a shared knowledge base to speed onboarding and compound improvements.

#16 𝕏

Peter Yang relays Figma CEO Dylan Field’s core insight: design is the new code—your live canvas replaces static mockups and you can pull request straight to production—and mastering both taste and craft is a must.

#17 𝕏

Lenny Rachitsky distills @rabois’s key insights: small autonomous teams outperform big hierarchies, CMOs will drive AI adoption via token-based pricing, and the traditional PM role faces obsolescence in an AI-first world.

#18 ▶️

Hard truths about building in the AI era | Keith Rabois (Khosla Ventures)

Lennys Podcast

#19 𝕏

Peter Yang warns OpenAI is in a mini-crisis if its GPT integration with OpenClaw doesn’t match or beat Opus’s performance, as shown in a recent comparison image.

#20 𝕏

bolt.new released a 10-minute explainer video showcasing key features—Plan mode, Design Systems, User Auth, API calls, Security, MCP Connectors, and Publishing—to onboard new users quickly.

#21 𝕏

Cursor cut dropped frames by 87% when streaming large-file edits, significantly boosting performance. It’s part of ongoing investments to make the editor faster and more reliable.

#22 𝕏

clem 🤗 used Chandra-OCR-2 by @datalabto for document text extraction. They link to @NielsRogge’s Hugging Face blog for a deep dive on OCR papers, benchmarks, and real-world performance.

#23 𝕏

Santiago launched Cards, prebuilt AI workflow templates (like Skills) that let you chain tasks—e.g., search Slack/Gmail, augment with Google, and email you a summary.

#24 𝕏

dharmesh uses a humanoid-robot analogy to explain that today’s AI agents must “behave” like humans to fit into existing human-centric UIs, but over time products with dedicated, optimized agent interfaces (AUX) will win out.

#25 𝕏

Cursor introduced a diff-to-line jump feature that takes you directly to the exact file line in your editor, unlocking full editing powers like manual edits, Tab completion, go-to-definition, and more.