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.
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.
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.
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.
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.
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.
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.
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.
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.
Modal argues that the same developer-experience principles that help humans—tight feedback loops, programmatic access via CLI/SDK/API, actionable error messages, and consistent code-adjacent examples—also make coding agents faster. Because agents iterate by generating, running, and observing code, vague errors or UI-only config stall them, so designing for agents means applying the same principles rather than reinventing them.
Vapi now supports structured outputs for all voice AI assistants, ensuring every call returns data that matches a developer-defined JSON schema. Schemas are enforced at runtime using provider-native capabilities from OpenAI, Anthropic, Gemini and others, and can be reused across multiple assistants. Extracted data arrives in call completion webhooks and the REST API.
Replit launched Fast Mode, a faster way to direct its Agent to make small, precise changes. It runs on an efficient agentic model that is significantly more affordable than Build mode and optimized to finish requests in the fewest steps, aimed at quick fixes, visual iterations and small features. Fast Mode is available to all Replit users starting today and is activated via the lightning bolt icon.
Modal built Modal Vibe, an open-source demo vibe coding platform on Modal Sandboxes that scales from 0 to 1,000 AI-coded apps in about five minutes. A load test creating 1,000 apps, each in its own Sandbox, took roughly 300 seconds, with the AI API as the rate-limiting step. Modal says the Team Plan can run 1,000 concurrent Sandboxes, enough for over one million sessions per month.
Modal shipped product updates including Modal Notebooks for cloud-based Python experimentation with up to 8 B200 GPUs, plus an optional idle_timeout parameter for modal.Sandbox.create(). The client also added a startup_timeout parameter to @app.function() and @app.cls() decorators and a new API pattern for imperative management of Modal resource types. Modal Notebooks have since been shut down, though existing notebooks can still be downloaded as .ipynb files.
Modal Notebooks is now generally available to all Modal customers after a limited beta last month. The collaborative notebook environment runs on a GPU-enabled Python kernel that reaches a ready state in under 5 seconds on arbitrary container images and hardware up to 256 vCPUs and 8 H100/B200 GPUs, with auto-idle shutdown, shared Volumes and Secrets, and real-time multi-cursor editing. Modal says over 5,000 accounts ran 200,000 code cells during the August beta, and upcoming features include memory snapshots, one-click export to Modal Apps, and scheduled runs.
An AI code sandbox is an isolated environment that executes LLM-generated code at runtime, containing the blast radius of errors or injected vulnerabilities. Modern implementations run on VMs or containers, often using secure runtimes like gVisor to intercept syscalls and shield the host. Most companies choose managed sandbox services over building their own with Kubernetes, since cold starts and scaling to millions of concurrent sessions are costly to handle.
Lovable used Modal Sandboxes to run LLM-generated code during a June 2025 promotional weekend with Anthropic, OpenAI, and Google, enabling users to build an estimated 250,000 applications in 48 hours. Modal ran over 1 million sandboxes with up to 20,000 concurrent at peak as Lovable's concurrent sessions surged 2.5-3x, and its platform team was not paged once. Lovable cut its sandbox orchestration code from 15,000 lines to 700 lines after switching to Modal.
Quora uses Modal Sandboxes to securely execute LLM-generated code in Poe, its AI chatbot platform, shipping the feature months earlier than an in-house build would have allowed. The team stress-tested Sandbox creation throughput to 1000 sandboxes per second and reports saving 2 engineers' worth of ongoing infrastructure maintenance time.
Vapi now lets users launch outbound call campaigns by uploading a CSV of phone numbers and custom variables, then assigning an assistant or workflow to run. Vapi handles queuing, execution and logging, with call status visible in the dashboard. Campaigns require a verified phone number, as Vapi numbers cannot be used.
A guide outlines five ways real estate agents can use AI, including voice agents built on Vapi that answer calls, qualify leads, and book showings around the clock. It also covers automating content with ChatGPT and Canva, plus AI pricing tools such as HouseCanary and CoreLogic that produce valuations with confidence scores.
Vapi compares GPT-4.1 and Claude 3.7 Sonnet as the LLM behind voice agents, weighing conversation quality, context handling, reasoning transparency, platform integration and cost. GPT-4.1 offers a 1,000,000-token context window and 32,768-token outputs with 75% caching discounts, while Claude 3.7 provides a 200,000-token context and 128,000-token outputs. Both models are selectable on Vapi's voice agent platform.
Vapi outlines three voice AI use cases in logistics: ShipEX uses voice intelligence across 350 trucks to route maintenance alerts and accident reports, the Idaho State Liquor Division's voice picking system lifted pick rates 35%, and maintenance technicians log issues by voice to auto-create CMMS work orders. The article also details API integration with TMS, CRM, and WMS systems and deployment considerations.
Vapi outlines how to pick among four Gemini models for voice agents: Gemini 1.0 Pro for predictable, compliance-friendly flows at $0.50 input and $2.00 output per million tokens, Gemini 1.5 Flash for high-volume work with a 1M token context window, Gemini 1.5 Pro for deep reasoning with a 2M token window and 99.7% long-context retrieval accuracy, and Gemini 2.0 Flash for native tool calling.
A Vapi blog roundup lists five Character AI alternatives for voice integration: Vapi, AnimaAI, JasperAI, Novel AI and AI Dungeon. Vapi is pitched as an API-native Voice AI platform supporting 100+ languages, connecting to 40+ applications, with Sesame-powered voice agents and automated test suites for catching hallucinations.
Vapi's guide explains how to configure environment variables for its Voice AI integration, covering temporary vs. permanent and user-level vs. system-level variables. It details setup on Windows, macOS and Linux with Vapi-specific examples like VAPI_API_KEY and VAPI_MULTILINGUAL_SUPPORT, plus naming and security best practices such as never hardcoding API keys.
Modal launched Modal Batch, a batch-processing interface backed by a rebuilt durable queue that can queue 1 million inputs at once, up from 2,000, and guarantees execution up to 7 days after a job is launched, up from 1 day. A new native handler, .spawn_map, spawns thousands of containers over a set of inputs without users managing async logic, and Harvey reports a 10x speed-up in its document-processing pipeline after fanning inputs across 1,000 containers. Suno uses it to run GPU-accelerated preprocessing on thousands of GPUs, and Achira relies on its retry mechanism for quantum mechanical datasets.
Vapi has rolled out direct integration with GoHighLevel Calendars, embedding its voice agents into the GHL scheduling flow. Agents can now check real-time availability on connected GHL calendars, create contacts from caller details, and book appointments tied to the correct contact. Setup mirrors connecting Google Calendar in Vapi, with four new tools: Create Event, Check Availability, Create Contact, and Contact Get.