OpenAI released a Developers plugin that gives ChatGPT and Codex access to the OpenAI API Platform and API setup guidance, with adaptations for Claude Code and Cursor bundling portable developer skills and the public OpenAI Docs MCP server. It covers API key setup, Agents SDK app building, API migration to the Responses API, and troubleshooting common API failures.
Factory built an open-source benchmark testing 13 models on 50 real pull requests from Sentry, Grafana, Keycloak, Discourse and Cal.com, with each model reviewing every PR at least three times at high reasoning effort and an LLM judge scoring findings against a human-curated golden set. GPT-5.2 led at 60.5% F1 for $1.25 per PR, ahead of Claude Opus 4.6 at 59.8% F1 and $3.11 per PR, while MiniMax M2.7 reached 45.6% F1 at $0.15 per PR and Kimi K2.5 hit 51.9% F1 at $0.41. Factory says cost explains only about 21% of quality variance, and it open-sourced the golden set, evaluation scripts and a Droid Action GitHub Action supporting all 13 models.
AE Studio details how it trained LLMs to prove math theorems with reinforcement learning on Modal, comparing Evolution Strategies against GRPO while keeping the training loop fixed. The setup runs vLLM inference on GPUs, Lean compiler verification in isolated CPU sandboxes, and a lightweight orchestrator, using per-function images, .map() fan-out, and Volumes for base weights.
Factory released an Automated QA skill that drives apps the way a real user would, filling forms, typing into terminals and calling endpoints, then posts a structured report with screenshots, terminal snapshots and API traces as a single comment on each pull request. The skill runs on every push via Droid, can be configured as an optional CI check triggered by a PR label, comment command or manual dispatch, and is also available locally through /qa in any Droid session. Setup uses /install-qa, and the feature is available today in all Factory plans.
Google Cloud named Replit its 2026 AI Tooling Partner of the Year, recognizing the platform now used by more than 50 million people across 85% of the Fortune 500. The award follows the launch of Replit's Agent 4, which the company says is 10x faster than Agent 3 and runs multiple agents in parallel. Replit is available on the Google Cloud Marketplace, integrated with Cloud Run, Kubernetes Engine, and BigQuery.
GRASP is a new gradient-based planner for learned world models that makes long-horizon planning practical by lifting trajectories into virtual states for parallel-in-time optimization, adding stochasticity to state iterates for exploration, and reshaping gradients so actions receive clean signals while avoiding brittle state-input gradients through high-dimensional vision models. The work addresses ill-conditioned computation graphs, non-greedy local minima, and high-dimensional latent failure modes that make long-horizon planning fragile. It was done with Mike Rabbat, Aditi Krishnapriyan, Yann LeCun, and Amir Bar.
OpenAI published an API deployment checklist that walks developers through moving workloads onto the Responses API and the GPT-6 model family, including gpt-6-astra, gpt-6.1-sol, gpt-6 Sol and gpt-6 Luna. The guide covers reasoning.effort levels from low to max, text.verbosity, tool_search with deferred tool loading, Programmatic Tool Calling, Multi-agent, compaction, prompt caching and WebSocket mode, which OpenAI says has shown up to roughly 40% faster end-to-end execution for workflows with 20 or more tool calls. It also details reliability and safety steps such as handling 429 and 503 errors, background=True for long jobs, safety_identifier and misalignment monitoring.
Why it matters: OpenAI's official deployment checklist consolidates model selection, reasoning effort, tool search, compaction and WebSocket mode into one migration guide for GPT-6 workloads.
OpenAI published an overview of new Codex app updates aimed at working across tools, apps, automations and other developer workflows. The material is a short summary only, so specific features, versions and availability details are not described.
Why it matters: OpenAI outlines Codex app updates that extend the coding agent across tools, apps and automations, showing how its scope is widening beyond code generation.
Vapi released Vapi Monitoring, a monitoring product that lets teams create customizable monitors for voice agents and get alerted when thresholds are hit. It covers effectiveness and compliance monitoring for Enterprise subscriptions, plus technical and infrastructure monitoring, and surfaces issues with affected call counts and recommended fixes.
Modal published a walkthrough on building a custom coding agent harness on top of the OpenAI Agents SDK, which OpenAI launched today, using Modal Sandboxes to give agents isolated Linux environments and GPUs. The guide starts from a minimal exec-based agent, then adds sessions for memory, an orchestrator plus subagent pool for parallel async work, GPU quotas, filesystem snapshots to deduplicate setup, and a skills subsystem, ending with a harness that runs OpenAI's Parameter Golf challenge across parallel GPU subagents. Modal cites Ramp's fleet of background coding agents on Modal, which it says now produces more than half of the company's PRs.
Vapi VP of Product Management Nathalie Criou told a HumanX panel with Salesforce, Databricks and TinyFish that AI amplifies rather than replaces fundamentals like domain expertise and judgment. She said Vapi's platform, built on millions of real-world voice interactions, develops institutional memory that a single training run cannot replicate. The panel argued shallow moats such as being first to market are eroding while trust, switching costs and unique interaction data compound faster.
Vapi's Forward-Deployed Engineers say the demo-to-production gap is where most enterprise voice AI initiatives stall, requiring extensive testing, guardrails and intent-based design rather than exact phrase matching. The team warns of "personality drift," where agents adopt callers' speech styles, and notes LLMs are non-deterministic, so deployments need defined error tolerance and continuous iteration. They advise starting with cost optimization but targeting revenue generation, and benchmark a good interaction at under a minute.
Modal demonstrates running autoresearch agents on elastic GPUs: given Modal Skills, Claude Code ran 113 experiments over 238 GPU-hours on OpenAI's Parameter Golf challenge, finishing core training runs 5x faster than a single workstation while using a fraction of a dedicated cluster's resources. Agents provision GPUs via API calls, scaling from one to dozens of H100s and back to zero automatically.
Modal has acquired Butter, with founder Erik Dunteman and researcher Raymond Tana joining Modal's Sandbox team. The Butter team brings agent harness engineering experience, including bVisor, a virtual Linux kernel written from scratch in Zig for lightweight, ephemeral sandboxes. Modal says the hire advances its goal of making Modal Sandboxes a best-in-class product experience.
Physical Intelligence (Pi) runs its Visual-Language-Action robot models on Modal, adding only ~10-15ms of network overhead. Pi worked with Modal to build a QUIC-based portal over UDP with automatic NAT traversal, replacing TCP Tunnels to avoid request-response stalls in the robot control loop. Checkpoints stored in Modal Volumes load in under 30 seconds, and region-pinned deployments keep inference close to robots.
Modal now offers NVIDIA's RTX Pro 6000 Blackwell with 96GB of VRAM and strong fp4/fp8 throughput, available via a single line of code for inference and fine-tuning workloads. The update also adds a dashboard Command Palette (CMD+K), a revamped Sandbox Filesystem API in beta supporting reads up to 5GB and streaming in both directions, and CLI log commands with historical fetching.
Vapi released Enhanced Security Mode, an audio privacy layer it calls the quietest and most secure ever deployed in an enterprise voice AI platform, designed to prevent AI agent speech from being overheard in open spaces. The company says its entire audio pipeline was re-engineered to invert signal-presence optimizations without adding latency artifacts. Early access covered healthcare, benefits administration, and post-acute care organizations, and the feature is available now.
Runway is partnering with Modal to power real-time inference for Runway Characters, a real-time video agent API built on Runway's GWM-1 world model that generates expressive digital personas from a single image with zero fine-tuning. Modal's serverless platform let Runway move from proof of concept to production in under 30 days, using single-line multi-node GPU clusters with RDMA networking across every region. Characters is available now to developers and businesses at dev.runwayml.com and to consumers at runwayml.com.
Doppel migrated a large portion of its ML workflows to Modal, removing the infrastructure friction that slowed training experimentation and inference deployment. Parallel experiments via map() replaced sequential runs, while image layer caching and persistent volumes cut build times by up to 10x, with complex setups reaching sub-minute warm builds.
Vapi hosted a webinar in which Principal Product Manager Nick Robin demoed Composer, its in-product assistant for building voice agents without code, producing a working inbound customer service agent within a 30-minute demo. Composer writes system prompts, provisions phone numbers, sets scheduling and flags its own errors for approval. It is currently in alpha and supports both inbound and outbound assistants, CRM and calendar integrations, and editing of existing agents by assistant ID.
Berkeley AI Research researchers describe SPEX and ProxySPEX, algorithms that identify influential feature, data, and model-component interactions in LLMs at scales far beyond prior methods. SPEX reframes interaction search as sparse recovery using sparsity and low-degreeness, while ProxySPEX exploits hierarchy to match SPEX with about 10x fewer ablations. On sentiment analysis, SPEX matches Faith-Shap and Faith-Banzhaf faithfulness on short inputs and retains it as context scales to thousands of features.
OpenAI updated its Sora 2 prompting guide to cover new API capabilities: reusable character references for objects and animals, 1920×1080 and 1080×1920 exports, a maximum clip length raised from 12s to 20s, video extension that uses the full original clip as context, and a Batch API for asynchronous video jobs. The guide also walks through prompt structure for shot framing, camera motion, lighting and dialogue, and notes that resolution, duration and character IDs must be set as API parameters rather than described in prose. Extensions of up to 20 seconds are supported, and a video can be extended up to 6 times for a total of 120s.
Why it matters: OpenAI's updated Sora 2 prompting guide details new API capabilities such as character references, 20s clips and video extension, plus reusable prompt templates for controlling shots.
Modal added Directory Snapshots for Sandboxes, letting users snapshot a single directory and mount it into a new Sandbox independently of the base image. Modal also released a free public GLM-5 endpoint with Z.ai through the end of April, compatible with OpenCode, Claude Code, OpenClaw and the Vercel AI SDK. The modal billing report CLI and modal.billing.workspace_billing_report API are now generally available for Team and Enterprise workspaces.
Vapi released Vapi Skills, a repo following the Agent Skills standard, plus a Model Context Protocol connector that gives coding agents live access to Vapi's documentation. One install command loads step-by-step instructions with exact API schemas for workflows like create-assistant, create-tool, create-call, and setup-webhook, and the skill pack runs on Claude Code, Cursor, VS Code Copilot, and Gemini CLI.
OpenAI released a Codex prompting guide for developers calling the Codex-tuned gpt-5.3-codex model directly through the API, recommending medium reasoning effort for interactive coding and high or xhigh for the hardest tasks. The guide covers migrating an existing harness to the open-source codex-cli, including the standard Codex-Max prompt, the apply_patch, shell_command and update_plan tools, and first-class compaction via /compact in the Responses API for multi-hour sessions. It also describes the new phase field, supported only on gpt-5.3-codex, which marks assistant items as commentary or final_answer and must be preserved in history to avoid performance degradation.
Why it matters: OpenAI's official guide details how to tune prompts, tools and compaction for gpt-5.3-codex, giving teams a concrete migration path for their own coding agents.
Modal, a cloud infrastructure platform for data- and compute-intensive AI workloads, highlights research from Hazy Research, Scaling Intelligence, and IRIS that used its GPU fleet to speed up AI research. The KernelBench project, led by Scaling Intelligence's Anne Ouyang, Simon Guo, and Will Hu, provides a 250-problem benchmark and research environment for automated GPU kernel generation, using Modal for consistent, scalable benchmarking across hardware from L40s to Blackwell systems.
OpenClaw agents can now make and receive phone calls through Vapi's AgentSkills-compatible skills, installed in about five minutes via the npx skills CLI or by asking the agent directly. The Vapi pipeline targets sub-500ms voice responses and supports mid-call tool calling, with eight skills covering assistants, calls, phone numbers, tools, squads, webhooks and workflows.
Modal launched Directory Snapshots in public beta, letting users snapshot a specific directory inside a running Sandbox and mount it into another Sandbox independently of the base image and the rest of the filesystem. The feature targets coding agents and vibe coding platforms that need to preserve project state across sandbox restarts, and Modal says it enables separating system dependencies from application code, pre-warming sandbox pools, and faster pre-loading of key files. Directory Snapshots persist for 30 days after last use and mount instantly, with contents prioritized for pre-loading on Modal's lazy-loading container filesystem.
Ramp built Ramp Inspect, an internal background coding agent running on Modal Sandboxes, and it now starts roughly half of all merged pull requests across Ramp's frontend and backend repos. Each session boots a full-stack environment with Postgres, Redis, Temporal and RabbitMQ in seconds, because a Modal cron job clones repos and saves filesystem snapshots every 30 minutes. Modal Functions, Dicts and Queues handle snapshot builds, session locks and prompt routing, letting Inspect support multiplayer sessions and hundreds of concurrent sessions without one affecting another.
Opus 4.6 and GPT-5.3-Codex both shipped last week, but the decisive contest is not raw capability. The argument holds that most economically valuable work sits in the specialisation layer, where a sub-80B model fine-tuned on a client's own data outperforms GPT-5.2 on that client's workflow — faster, cheaper, and without sending proprietary data to a third party. Open-source needs only to match the intelligence ceiling, not the frontier, and the labs' capital-dependency clock is the weaker position.
Vapi shipped Composer, an AI assistant inside the Vapi Dashboard that builds voice agents from a description, writing the prompt, configuring settings, provisioning phone numbers, building tools and setting up integrations. Composer can also pull call logs to explain a failed call and apply a fix, and generate custom code tools that run on Vapi's infrastructure for integrations such as HubSpot. It is available now in Alpha with no setup or onboarding flow.
Modal 推出 GLM-5 的免费 OpenAI API 兼容端点，可用至 4 月底，限单个并发请求，同时发布在单节点 8 张 B200 上用 SGLang 部署的可复现代码。
Why it matters: Modal 为 Z.ai 的 GLM-5 提供免费 OpenAI 兼容端点，并给出在 OpenCode、OpenClaw、Claude Code 和 Vercel AI SDK 中接入的具体配置。
OpenAI introduced the Codex app, a dedicated app for its Codex coding agent, in an official developers blog post. The post is an intro walkthrough covering the app and its core workflows, with the full video hosted on YouTube.
Why it matters: OpenAI's official walkthrough shows how the Codex app structures core coding workflows, useful for developers weighing it against existing coding agents.
Modal is now purchasable through AWS and Google Cloud Marketplaces, letting enterprise customers apply existing cloud spend commitments to Modal usage. The platform also shipped Sandbox UI updates with clearer resource and region details plus a new execution timeline, and client 1.3.1 adds Python 3.14 support including experimental free-threaded Python (3.14t) in Modal containers.
Continual learning is inseparable from specialization because the cost of remembering scales with scope: as context grows, the KV cache grows linearly and can exceed all model weights, so information must move from token level into weights. Task specialization is essentially solved via continuous fine-tuning pipelines, while broad-scope, sparse-feedback, one-shot retention remains the hard problem.
Factory launched Agent Readiness, which evaluates how well a codebase supports autonomous development across eight technical pillars and five maturity levels, runnable via /readiness-report in Droid, an organization dashboard, or an API. Each criterion is binary and a level unlocks only when 80% of its criteria and all prior levels pass; grounding each evaluation on the repository's previous report cut score variance from an average of 7% to 0.6% across 9 benchmark repositories over six weeks. Reports can trigger an agent that opens a pull request to fix failing criteria such as missing AGENTS.md, linter configuration, or pre-commit hooks.
Chai Discovery is using Modal to run its machine learning drug discovery pipelines, from protein embeddings and multiple sequence alignments to antibody design. Modal Volumes downloads and indexes datasets reaching hundreds of gigabytes once, then shares them across machines, while elastic GPU scaling spins up hundreds of GPUs in minutes. Chai says the same setup now carries research workflows into production without rewriting infrastructure.
OpenAI released a public Model Context Protocol (MCP) server that gives agents read-only access to developer documentation across developers.openai.com, platform.openai.com, and learn.chatgpt.com. The server is documentation-only and does not call the OpenAI API on the user's behalf. Developers can add it to Codex via the CLI or IDE extension with a single shared configuration, and pair it with the OpenAI Docs Skill for citation-backed answers.
Modal has scaled its multi-cloud GPU worker pool past 20,000 concurrent GPUs and launched over four million cloud instances in the last couple years, and is now sharing the reliability system behind it. The post covers instance type testing and selection, machine image preparation and boot checks, passive and active GPU healthchecking, and observability and support. It reports hyperscaler differences such as Cloud A's 99.6% boot success and Cloud C's H100s running above 90ºC in 2025.
Replit is now available inside ChatGPT, letting users tag @replit in any message to have Replit Agent create, update and deploy Replit Apps directly in the conversation. Build progress and an interactive preview appear in-chat, and each request such as adding dark mode or a payment form updates the app instantly, with apps stored in the user's Replit account for later publishing. The integration requires a ChatGPT account (Free, Plus, Pro or Teams) and a Replit account, works where the ChatGPT App Store is available, and consumes Replit Agent credits.
Why it matters: Replit's ChatGPT integration lets users describe an app in chat and have Replit Agent build, preview and deploy it without leaving the conversation.