Anthropic launches Claude Code Review

March 10, 2026
Anthropic

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Today's top 25 insights for PM Builders, ranked by relevance from Blogs, X, LinkedIn, and YouTube.

Anthropic launches Claude Code Review

#1 𝕏

Claude launched Code Review as a research-preview beta for Team and Enterprise, bringing AI-powered code feedback and analysis to development workflows.

#2 𝕏

DeepLearning.AI Google introduced Nano Banana 2 (Gemini 3.1 Flash Image), a faster, lower-cost image generator built on Gemini 3 Flash that produces images in seconds with iterative editing and cuts generation costs by roughly half.

#3 📝 OpenAI News

OpenAI to acquire Promptfoo - OpenAI announced on March 9, 2026 that it will acquire Promptfoo, an AI-powered prompt testing and validation framework designed to help developers ensure prompt reliability and performance.

#4 𝕏

Andrew Ng launched Context Hub, an open CLI tool that gives coding agents up-to-date API docs to prevent outdated calls and hallucinated parameters. It also lets agents annotate and save workarounds, with plans for agents to share these learnings over time.

#5 in

Udi Menkes open-sourced 28 AI-powered PM skills and used Claude Code to prepare and execute a real product launch in one session.

#6 𝕏

Claude reports that after running their AI review tool on most Anthropic PRs, substantive review comments jumped from 16% to 54%, with under 1% false positives. On large PRs (1,000+ lines), it flagged findings in 84% of cases, averaging 7.5 issues each.

#7 𝕏

Boris Cherny launched Claude Code’s new Code Review feature, where AI agents deep-review every PR, boosting Anthropic engineers’ code output by 200% this year and catching bugs he’d otherwise miss.

#8 𝕏

Andrej Karpathy ran a two-day autoresearch tuning on a depth-12 nanochat model, uncovering ~20 additive changes that, when applied to depth-24, cut “Time to GPT-2” from 2.02 h to 1.80 h (~11% faster) for a new leaderboard record.

#9 𝕏

Cognition launched Devin Review, a free no-signup PR review tool with autofix, smart diff organization, copy/move detection, and codebase-aware chat—just swap “github” with “devinreview” on any PR to try it.

#10 𝕏

Philipp Schmid shows how the Gemini Interactions API can process minutes to hours of YouTube video content in seconds with a single API call, highlighting a major leap in video understanding.

#11 𝕏

LlamaIndex 🦙 launched Surreal Slides, a tool that uses LlamaParse to convert slide decks into structured data stored in SurrealDB, letting you query your entire presentation library in natural language without manual scanning.

#12 in

Greg Isenberg discovered a GitHub repo that spins up a 43-agent AI agency—spanning engineering, design, marketing, product, PM, testing, and support—to coordinate end-to-end idea shipping, and it racked up 10k+ stars in under 7 days.

#13 ▶️

My OpenClaw is the only marketer I need

Greg Isenberg

How to configure an OpenClaw agent named Larry with the Larry marketing skill to autonomously produce, post, and iteratively optimize TikTok slideshow videos to generate hundreds of dollars in monthly recurring revenue for mobile apps.

  • Uses the free Larry marketing skill on OpenClaw to automate TikTok slideshow content and iterate hooks and CTAs via TikTok analytics, generating $300–$400 in monthly recurring revenue for the Snuggly app and nearly $1,000 total across live apps.
  • Larry generates slideshow images using DALL·E 3 and a secondary image model, posts drafts via the TikTok API for Oliver to add sound and publish, and scaled content up to 400,000 views per video.
  • Oliver Henry subscribes to Anthropic Claude’s Banks plan at ÂŁ90/month, favoring it over OpenAI’s ÂŁ200/month tier for cost-effective AI agent tasks.

#14 📝 Doug Turnbull

Ugly hack to force BM25 to 0-1 - Describes a practical technique to normalize BM25 lexical scores into a 0–1 range. Addresses the problem that BM25 scores are inconsistent and proposes an ad-hoc workaround to make them comparable.

#15 📝 Simon Willison

Perhaps not Boring Technology after all - Reflection on the concern that LLMs might bias technology choices toward well-represented tools in their training data, making it harder for new tools to gain traction. The piece explores the implications of that effect for tooling and innovation.

#16 𝕏

Peter Yang distills five takeaways from Pencil CEO Tom Krcha on how humanized AI agents—armed with context, personality, and iterative creativity—will revolutionize design without sacrificing craft and delight.

#17 𝕏

claire vo đź–¤ @jameygannon spent thousands of hours in Midjourney using Pinterest mood boards and a custom personalization code to generate consistent AI-driven brand imagery without complex prompts.

Also covered by: @Claire Vo

#18 𝕏

Shreyas Doshi urges PM Builders to carefully read AI’s initial output, evaluate its logic against their specific context, and then craft precise follow-up prompts to drive more critical, accurate reasoning.

#19 𝕏

Santiago argues that most ideas aren’t worth implementing and he uses AI to optimize and accelerate his existing work rather than shipping new features.

#20 ▶️

5 steps to generate consistent brand images with Midjourney

How I AI Podcast

Jamey Gannon runs a 30-minute MidJourney workflow combining Pinterest/Cosmos mood boards, drag-and-drop SRF style and image references, a “late 2025 aesthetic” personalization code, camera cheat codes, and Nano Banana refinement and upscaling to produce consistent brand assets.

  • Executes the initial “create” phase in 10–15 minutes using MidJourney with mood board SRF style references and brief prompts like “astronaut” and “ethereal female model.”
  • Applies a custom MidJourney personalization profile named “late 2025 aesthetic,” built via flop-matrix voting, to enforce crisp skin rendering, deep blacks, and high-contrast color grading.
  • Uses Nano Banana to upscale outputs from 800Ă—800 to 4,000Ă—4,000 pixels and replace an on-screen laptop by instructing “replace the computer she’s typing on on a 2026 Midnight Black MacBook Pro,” maintaining exact position and scale.

Also covered by: @Claire Vo

#21 𝕏

Guillermo Rauch spotlights OpenBlock’s AI coding agents with built-in Vercel CLI integration—demonstrating in a video how these “real agents” can auto-generate, deploy, and manage production code seamlessly.

#22 𝕏

Josh Woodward unveils NotebookLM’s new ePub upload feature, letting students import full e-books directly for AI-driven note-taking, summaries, and Q&A.

#23 𝕏

Andrej Karpathy clarifies that this version of autoresearch lacked time-controlled evaluation, so runs with lower validation loss but longer training times were rejected. Changes are only accepted if they achieve better-or-equal loss and better-or-equal training time.

#24 𝕏

Cognition launched a Datadog integration in the MCP Marketplace, letting your AI agent Devin pull monitoring data via the MCP Server. They’ve published full step-by-step setup instructions.

#25 𝕏

Boris Cherny shows that ramping up “test-time compute” by feeding more tokens into a coding prompt—and using multiple uncorrelated context windows—yields significantly better code results.

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