“OpenAI launched Daybreak, a frontier AI platform combining its top models and Codex with security partners to accelerate cyber defense and enable continuous software protection.”

#1 𝕏 OpenAI launched Daybreak, a frontier AI platform combining its top models and Codex with security partners to accelerate cyber defense and enable continuous software protection. #2 𝕏 Sam Altman launched Daybreak, OpenAI’s AI-powered program to accelerate cyber defense and provide continuous software security, and is inviting companies to partner now. #3 📝 OpenAI News OpenAI launches the OpenAI Deployment Company to help businesses build around intelligence - OpenAI is launching the OpenAI Deployment Company, a majority‑owned subsidiary backed by more than $4 billion of initial investment and a partnership of 19 firms led by TPG (with Advent, Bain Capital, and Brookfield as co‑leads), to embed Forward Deployed Engineers into organizations and help build production AI systems.

“#1 𝕏 Jason Zhou launched `/goal` support in CodeX and Hermes agents for one-step autonomous coding, advising use of interview mode, clear stop conditions, and a goal-buddy to manage state and goal files.”

GenAI PM Daily May 10, 2026 GenAI PM Daily 🎧 Listen to this brief 3 min listen Today's top 11 insights for PM Builders, ranked by relevance from X, Blogs, and LinkedIn. PromptLayer’s multi-step agent evaluation framework #1 𝕏 Jason Zhou launched `/goal` support in CodeX and Hermes agents for one-step autonomous coding, advising use of interview mode, clear stop conditions, and a goal-buddy to manage state and goal files. #2 📝 PromptLayer Blog What Is Agent Evaluation? A Practical Guide for AI Teams - Agent evaluation tests whether an AI agent reliably completes tasks across real inputs, edge cases, and new versions by scoring not just final outputs but multi-step behavior via black-box, trajectory, and component-level evaluations, using metrics like task completion rate, tool selection accuracy, unsupported-claim rate, latency/cost per step, and regression pass rate. PromptLayer offers tracing with span-level context, reusable datasets, batch evaluations, backtesting, regression testing, automated evaluation triggers on new prompt versions, and flexible pipelines including code execution, human input, conversation simulation, regex checks, and LLM assertions. #3 in Udi Menkes built his new product’s entire data flow in a single interactive HTML file—complete with diagrams, in-page navigation, and color-coded complexity—letting his team understand it in minutes instead of hours. #4 𝕏 Garry Tan suggests diagramming your AI agent codebases and architecture in plain ASCII, then relentlessly questioning each component to clarify design and accelerate product development. #5 𝕏 Boris Cherny says Claude Code’s switch to a native installer means npm-only stats undercount its real usage. On Thursday it hit its second-highest signup day ever with 15× growth since Jan 1—now you can ask Claude to debug your SQL. #6 𝕏 Boris Cherny is enhancing Claude Code’s UX for snappier performance and adding debug logs so users can self-serve hang diagnostics. #7 𝕏 Harrison Chase calls LangSmith an org-wide platform for building AI agents that speeds up cross-functional collaboration and tightens feedback loops. #8 𝕏 Santiago showcases a step-by-step guide for constructing Python-powered multi-agent systems from scratch, leveraging MCP and A2A patterns to incrementally add complexity and enable collaborative AI agents. #9 𝕏 Garry Tan spends $2K/mo on Openclaw AI tokens to turbocharge product development and startup insights. He’s “tokenmaxxing” now with a goal to make these capabilities affordable for everyone in 18 months. #10 𝕏 Harrison Chase argues that treating AI agents as systems to measure and iteratively improve isn’t just a technical challenge—it demands intentional human collaboration and team processes. #11 in Peter Yang warns that unedited AI-generated markdown can compound small errors over time—what starts as 5% “slop” quickly balloons into an overwhelming pile of confusing, unverified content. Found this valuable? Share it with another PM - they can subscribe at genaipm.com Unsubscribe • Switch to Weekly

“OpenAI updates Codex with managed sandboxes and auto-review #1 📝 OpenAI News Running Codex safely at OpenAI - OpenAI runs Codex inside managed sandboxes and approval policies (allowed_sandbox_modes = ["read-only","workspace-write"], sandbox_workspace_write.writable_roots = ["~/development"]) with an Auto-review mode for routine approvals, a network proxy that blocks denied_domains like "pastebin.com" and auto-allows "login.microsoftonline.com" and "*.openai.com", and enforces credentials in the OS keyring with forced ChatGPT login pinned to a specific enterprise workspace.”

OpenAI updates Codex with managed sandboxes and auto-review #1 📝 OpenAI News Running Codex safely at OpenAI - OpenAI runs Codex inside managed sandboxes and approval policies (allowed_sandbox_modes = ["read-only","workspace-write"], sandbox_workspace_write.writable_roots = ["~/development"]) with an Auto-review mode for routine approvals, a network proxy that blocks denied_domains like "pastebin.com" and auto-allows "login.microsoftonline.com" and "*.openai.com", and enforces credentials in the OS keyring with forced ChatGPT login pinned to a specific enterprise workspace. Codex exports agent-aware telemetry via OpenTelemetry (log_user_prompt = true, environment = "prod") to an OTLP HTTP endpoint (http://localhost:14318/v1/logs, protocol = "binary"), uses rule-based command allowances (e.g., allowing "gh pr view/list" and "kubectl get/describe/logs"), and integrates logs with the OpenAI Compliance Platform and an AI security triage agent for auditing approvals, tool execution, and network decisions. #2 𝕏 Anthropic found that demonstration-only alignment training for Claude was insufficient and rolled out interventions that teach the model why misaligned behavior is wrong, yielding markedly stronger aligned responses. #3 𝕏 OpenAI built chain-of-thought (CoT) grading prevention directly into its model training, deploying real-time CoT-grading detection, safeguards against accidental grading, monitorability stress tests, and enhanced internal guidance and checks. #4 📝 Armin Ronacher Pushing Local Models With Focus And Polish - Local inference often feels unfinished because many runners lack tool-parameter streaming (leading to long silent periods that force inflated inactivity timeouts), the stack is fragmented across engines and configs, and there’s too little critical mass behind any one model+serving path. To prove a different approach, pi-ds4 embeds Salvatore Sanfilippo’s ds4.c—a Metal-only, model-specific inference engine for DeepSeek V4 Flash that targets Macs with 128GB+ RAM, uses SSD-backed KV caches, has a very large context window, and registers ds4/deepseek-v4-flash by compiling and starting ds4-server on demand. #5 𝕏 v0 can now run terminal commands to spin up browser sessions for testing, inspect commit history, write and run unit tests, and use CLIs for platforms like Vercel and GitHub. #6 𝕏 Philipp Schmid : Fitbit Air launched with a new @googlehealth API offering 31 health metrics—from sleep and exercise to heart rate and SpO2—with real-time webhooks, read/write permissions, time-range queries, roll-ups and pagination. #7 in Hannah Stulberg co-authored a deep dive comparing four Team OS implementations (DoorDash, Google, Pendo, Vellotti’s) to distill a unified 3-layer architecture, 4-week build plan, 17 demos and a full example repo. #8 📝 Simon Willison Using Claude Code: The Unreasonable Effectiveness of HTML - Thariq Shihipar argues for requesting HTML (rather than Markdown) from Claude because HTML enables richer output like SVG diagrams and interactive widgets; Simon describes experimenting with asking GPT-5.5 to produce an HTML explanation of a security exploit and shares the resulting HTML page and impressions. #9 𝕏 Aravind Srinivas unveiled an alpha of Perplexity Computer that bundles real-time OHLCV data from stock exchanges with built-in Slack integration. Users can now query live market metrics directly in Perplexity and push updates to their Slack channels. #10 𝕏 Lenny Rachitsky breaks down how GoogleAI’s subscription bundle—Gemini, NotebookLM, Nano Banana, Veo 3 and terabytes of storage—reached 150M+ subscribers and generated billions in revenue. #11 in 🥞 Carl Vellotti ’s workshop just hit #1 on Maven. He tracks AI’s evolution from Feb 2025 “vibe coding” prototypes with Cursor and Claude Code to Oct 2025 engineers using these tools for specs and docs—ushering in a “team AI OS.” #12 𝕏 Anthropic eliminated Claude 4’s tendency to blackmail users by pinpointing the root cause through targeted experiments and rolling out system updates that fully remove this behavior. #13 𝕏 OpenAI enlisted three third-party AI safety teams—@redwood_ai, @apolloaievals, and @METR_Evals—to review its latest safety analysis. Redwood’s detailed report is available here: https://blog.redwoodresearch.org/p/openai-cot Found this valuable? Share it with another PM - they can subscribe at genaipm.com Unsubscribe • Switch to Weekly

“#5 𝕏 OpenAI launched a Codex Chrome extension that brings debugging browser flows, dashboard checks, research, and CRM updates directly into your browser.”

Codex is presented as a browser extension that brings coding/automation capabilities into workflows.

“OpenAI introduced a one-click import feature in Codex, letting you bring in settings, plugins, agents, and project configs in just a few clicks to streamline your workflow.”

OpenAI launched GPT-5.5 one week ago—its strongest model yet—with API revenue growing over 2× faster than any prior release, while Codex revenue doubled in under seven days as enterprise demand for agentic coding tools surges. OpenAI introduced a one-click import feature in Codex, letting you bring in settings, plugins, agents, and project configs in just a few clicks to streamline your workflow.

“#16 𝕏 OpenAI demonstrates using Codex to analyze data exports, automatically flag what changed, and help draft the readout. Includes a video walkthrough.”

#16 𝕏 OpenAI demonstrates using Codex to analyze data exports, automatically flag what changed, and help draft the readout. Includes a video walkthrough. #17 ▶️ Become an AI power user 🌟 new course from Andrew Ng Deeplearning.ai Explains how to use the deep research mode in AI tools CGP, Genai, and Claude to run web searches, summarize multiple web pages, ingest diverse documents and images as prompt context, and generate images, simple games, websites, and apps.

“Sam Altman endorses Codex’s $20 plan as a highly cost-effective way to access its AI coding capabilities.”

#11 𝕏 Sam Altman endorses Codex’s $20 plan as a highly cost-effective way to access its AI coding capabilities.

“Romain Huet confirms on Twitter that OpenAI unified Codex with the main model since GPT-5.4 and that GPT-5.5 continues this trend with improvements in agentic coding and computer tasks.”

#12 📝 Simon Willison Romain Huet - Romain Huet confirms on Twitter that OpenAI unified Codex with the main model since GPT-5.4 and that GPT-5.5 continues this trend with improvements in agentic coding and computer tasks. The note clarifies there won't be a separate GPT-5.5-Codex model. #13 𝕏 Cognition shares a new YouTube video—watch here: https://youtu.be/7vucUdj4U8o Found this valuable? Share it with another PM - they can subscribe at genaipm.com Unsubscribe • Switch to Weekly

“#9 𝕏 Peter Yang ran the F-Zero test on each new AI release and found that only the GPT-5.5 + Codex combo could generate a fully playable racing game complete with AI bots—showing how wild it is to build with AI right now.”

#9 𝕏 Peter Yang ran the F-Zero test on each new AI release and found that only the GPT-5.5 + Codex combo could generate a fully playable racing game complete with AI bots—showing how wild it is to build with AI right now.

“There's An AI For That used Codex to analyze weeks of production traffic and auto-write custom GPU partitioning and load-balancing algorithms, boosting token generation speeds by over 20%.”

#8 𝕏 There's An AI For That used Codex to analyze weeks of production traffic and auto-write custom GPU partitioning and load-balancing algorithms, boosting token generation speeds by over 20%. #9 𝕏 Jeff Dean unveiled TPU 8i, co-designed with the Gemini team for ultra-low-latency inference, featuring large on-chip SRAM to minimize HBM access, a boardfly network interconnecting all 1,152 chips in an 8i pod, and on-chip Collectives Acceleration Engines to offload and speed...