Skip to content
#Deployment / engineering
June 17Wednesday
  1. Vapi Blog40

    How Vapi Bootstrapped 15 Homepage Voice Agents in Code

    Vapi built the 15 voice agents on its homepage — 3 use cases across 5 languages — by generating them from a single ROUGH_DRAFT.md file instead of hand-editing each in the dashboard. The four-phase framework (plan, draft, bootstrap, harden) scaffolds a TypeScript project with OpenAI gpt-4.1 at temperature 0.5, ElevenLabs and Deepgram/Soniox voice stacks, and an idempotent upsert loop that stores assistant IDs in .env.local. The repo is public: clone it, add VAPI_PRIVATE_KEY, and run bun run bootstrap.

June 15Monday
  1. Modal Blog34

    Modal Product Updates: VM Sandboxes, Regional Routing, RBAC and More

    Modal shipped a batch of platform updates, including alpha VM Sandboxes that run a real Linux kernel to support Docker containers, eBPF, systemd and cgroups. Functions can now route through US West, EU West or Asia Pacific South instead of the default US East region, and RBAC is available to all Team and Enterprise plans. Sandbox readiness probes are now GA, and the Python SDK 1.5.0 and JS/Go SDK 0.8.0 set a 30-day default snapshot TTL.

June 11Thursday
  1. Modal Blog34

    Modal Makes FlashAttention-4 Faster for LLM Inference

    Modal contributed optimizations to the FlashAttention-4 kernel to speed up decode-heavy LLM inference workloads, where memory bandwidth is the bottleneck. The changes include porting the "split KV" parallelism technique to FA4 and replacing TMA cp.async.bulk loads with cp.async for irregular memory accesses. An FP8 input PR (merged April 17, 2026) delivers up to 1.16x throughput over the bf16 baseline and enables smaller KV caches.

  2. Factory62

    Factory rolls out automated security review in Droid

    Factory is rolling out automated security review in Droid, which runs a STRIDE-based security review alongside standard code review on every non-draft PR and posts findings with severity, a CWE reference, an explanation and a suggested fix as inline comments on the diff. The company says Droid's security review has been run across production codebases and surfaced findings that went through responsible disclosure, including CVE-2026-42876 in external-secrets and workos/workos-node#1578. Droid builds a lightweight threat model of the changed surface, scans for vulnerabilities such as OWASP Top 10 and OWASP LLM Top 10 issues, then validates each candidate finding against the diff to filter false positives before posting one deduplicated summary per PR.

    Why it matters: Factory's Droid now runs a STRIDE-based security review on every non-draft PR, and the post shows real CVEs it surfaced in production codebases.

June 1Monday
  1. Modal Blog46

    Modal: Reinforcement Learning for LLM Post-Training Is an Infrastructure Problem

    Modal says the bottleneck in RL post-training of LLMs is now infrastructure, not algorithms, and has released an open-source library drawn from running RL at scale. It details three pain points — glue code, cluster queueing and GPU under-utilization — and reports RDMA weight sync cutting Qwen3 8B update time from 2.62s to 41ms.

May 27Wednesday
  1. MiniMax Blog72

    MiniMax upgrades Agent as Mavis and launches Agent Teams for long-running tasks

    MiniMax upgraded MiniMax Agent under the new name Mavis and launched Agent Teams, which let multiple role-specific Agents run in parallel on the desktop for long, complex tasks. The system uses Leader, Worker and Verifier roles with a state-machine Team Engine that cycles tasks through producing, verifying and done, and it merges TokenPlan and Agent Plan into one subscription spanning CLI, API and Agent across M2.7, music, video and voice. MiniMax says the Agent will be open-sourced soon, expected alongside the MiniMax M3 model, while the desktop app is already available.

    Why it matters: MiniMax explains the design tradeoffs behind its Leader-Worker-Verifier Agent Team, including handoff, sharing and aggregation costs, offering a concrete reference for building multi-Agent runtimes.

  2. Modal Blog38

    Modal opens Role-Based Access Control to all Team and Enterprise users

    Modal is making Role-Based Access Control (RBAC) available to all users on Team and Enterprise plans, built around Environments as enforceable security boundaries. Restricted Environments make workspace members read-only by default, with only explicitly granted users or agents able to deploy and manage resources, and RBAC ties into Audit Logs for a full record of who did what and when.

May 21Thursday
  1. Vapi Blog20

    Vapi: Bringing Voice AI to ACCESS Chronic Care Panels

    Vapi argues that voice AI can now make voice the economically viable channel for ACCESS chronic disease management, citing Hiya data that 42% of consumers prefer voice for healthcare communication, up from 33% the prior year. The post details three production workflows, including Spring Venture Group's Medicare lead qualification agent, built by four engineers in one week, which lifted transfer-to-close rate by 3% and delivered over $5.8M in combined savings and new revenue.

May 20Wednesday
May 19Tuesday
  1. Modal Blog55

    Modal launches first-class Sandboxes integration with Claude Managed Agents

    Modal announced a first-class integration between Modal Sandboxes and Anthropic's Claude Managed Agents, letting all tool calls run in a self-hosted Modal Sandbox while Anthropic's managed agent loop handles session state. Modal cites fast cold starts on custom images, snapshot and volume persistence, burst pricing with no idle costs, short-lived connect tokens, and upwards of 100,000 concurrent sandboxes per customer. The company also published two reference examples, a CLI agent and a Slack bot, on the same Modal plus Managed Agents backbone.

May 15Friday
  1. Every40

    Every Is Redesigning Its Plus One AI Agents as Shared Team Resources

    Every is changing its Plus One product so its AI agents work as shared team resources with defined jobs, rather than one personal assistant per employee. The company says its first iteration, built on OpenClaw, brought more frustration than efficiency, with agents often failing to follow directions. The next version is meant to be more stable, with skills and integrations still part of the plan.

May 12Tuesday
  1. Modal Blog58

    How Modal achieved truly serverless GPUs

    Modal published an engineering account of how it cut AI inference replica spin-up from roughly 2,000 seconds to about 50 seconds using four components: a buffer of idle healthy GPUs, a lazy content-addressed filesystem called ImageFS, host-side checkpoint/restore via gVisor's runsc, and CUDA checkpoint/restore built on Nvidia driver support. Across over ten thousand cold starts, mean vLLM boot latency fell from 95,679 ms to 13,797 ms and SGLang from 83,713 ms to 17,486 ms for a ~1 GiB Qwen 3 0.6B model in bf16. The post also notes limits, including single-GPU-only snapshots and host-environment sensitivity that requires multiple snapshots per deployment.

May 8Friday
  1. Berkeley AI Research38

    Adaptive Parallel Reasoning: A Survey of Efficient Inference Scaling

    A Berkeley AI Research survey examines adaptive parallel reasoning, in which a reasoning model itself decides when to decompose subtasks, how many concurrent threads to spawn, and how to coordinate them. The post contrasts this with fixed parallelism methods such as self-consistency, Best-of-N, Tree of Thoughts, MCTS, ParaThinker, GroupThink and Hogwild! Inference, which impose the parallel structure externally. Sequential reasoning scales linearly in tokens and latency and risks context-rot, motivating parallel threads that explore independently and concurrently.

May 4Monday
May 1Friday
  1. Vapi Blog34

    Open Stack vs Integrated Solution: Key Considerations for Voice AI Builders

    Vapi Blog interviews Cartesia's Iz Shalom on choosing between integrated and open modular voice AI stacks. Integrated stacks suit narrow use cases and fast proofs of concept, while open stacks fit multiple use cases, multilingual support, and swapping components. The piece urges teams to measure P99 latency in their own environment and build tight evaluations before production.

April 29Wednesday
  1. Modal Blog33

    Building an RL Theorem-Proving Workflow on Modal

    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.

April 23Thursday
  1. Factory55

    Factory launches Automated QA skill that tests apps like a real user and reports in PRs

    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.

April 22Wednesday
  1. Replit Blog22

    Replit Wins 2026 Google Cloud AI Tooling Partner of the Year Award

    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.

April 20Monday
  1. Berkeley AI Research38

    GRASP: Gradient-Based Planning for World Models at Longer Horizons

    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.

April 17Friday
  1. OpenAI Developers Blog60

    OpenAI publishes API deployment checklist for GPT-6 workloads

    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.

April 15Wednesday
  1. Vapi Blog50

    Vapi Launches Vapi Monitoring for Production Voice Agents

    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.

  2. Modal Blog58

    Modal and OpenAI Agents SDK: building a parallel coding agent harness with sandboxes and GPUs

    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.

April 14Tuesday
  1. Vapi Blog27

    Vapi Engineers Share Lessons on Deploying Voice AI at Enterprise Scale

    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.

  2. Modal Blog40

    Modal Autoscaling Autoresearch: Elastic GPUs for AI Research Agents

    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.

April 10Friday
  1. Modal Blog38

    Butter Acquired by Modal, Founder Erik Dunteman Joins Sandbox Team

    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.

April 8Wednesday
  1. Modal Blog40

    Modal powers real-time inference for Physical Intelligence robots

    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.

April 7Tuesday
  1. Modal Blog22

    Modal Product Updates: RTX Pro 6000 Blackwell, Command K, Sandbox FS API

    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.

March 26Thursday
  1. Modal Blog38

    Runway partners with Modal to power real-time inference for Runway Characters

    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.

March 25Wednesday
  1. Modal Blog22

    How Doppel cut ML infrastructure overhead with Modal

    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.

March 20Friday
  1. Vapi Blog38

    Vapi Webinar Answers Top Questions on Composer Voice Agent Builder

    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.

March 4Wednesday
  1. Modal Blog22

    Modal Product Updates: Directory Snapshots, GLM-5 Endpoint and Billing API

    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.

February 25Wednesday
  1. Vapi Blog35

    Vapi Ships Skills and MCP Connector So Coding Agents Can Build Voice Agents

    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.

  2. Modal Blog22

    Modal Blog: How Modal Accelerates AI Research That Accelerates AI Research

    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.

February 24Tuesday
  1. Modal Blog55

    Modal launches Directory Snapshots in public beta for Sandbox project state

    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.

February 19Thursday
  1. Modal Blog58

    How Ramp built Ramp Inspect, a full-context background coding agent on Modal

    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.

February 11Wednesday
  1. Vapi Blog55

    Vapi launches Composer, an in-dashboard AI assistant that builds voice agents

    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.

  2. Modal Blog78

    Modal 上线 GLM-5 免费端点并发布自部署与前端接入指南

    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。

January 28Wednesday
  1. Modal Blog22

    Modal Product Updates: AWS & GCP Marketplace Availability, Sandbox Observability, and Client Updates

    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.

January 26Monday
  1. Charlie O'Neill38

    Continual learning and the post-monolith AI era

    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.

January 20Tuesday
  1. Factory58

    Factory launches Agent Readiness to score how well codebases support AI coding agents

    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.