Huawei has opened its DevEco Studio for HarmonyOS PCs to public beta, alongside first public betas of the AI tool DevEco Code and the agent toolkit DevEco CLI. The beta requires HarmonyOS 7.0.0.107 or later, at least 16 GB of memory and 100 GB of storage, and runs on several MateBook models and the MatePad Edge. DevEco Code ships with Zhipu AI's GLM-5.3 and GLM-5.1 models and supports third-party model connections.
The University of Michigan's EECS 498 course Applied Agentic Software Engineering teaches a coding agent across three phases, from applying and analyzing agents to building one. Its Elephant-Goldfish Model packages a design-first workflow into five Skills, with human handoffs between each step, and the course materials are public on GitHub.
No video AI model was used to make this video. The entire video is code: > 0% Blender > 0% Afeter effects > 0% Seedance Pure Three.js, took 12 hours with render. Made with Higgsfield Katana in Claude.
Snyk moved its internal support agent, Snyk Assist, into the core Snyk product in September 2026, giving every paying customer access. Built on LangChain and LangGraph with observability in LangSmith, the agent answers questions in plain language and can open support cases or log feature requests. It runs as a single agent behind Slack, web and API surfaces, with tools attached per user permissions.
Tessl argues that an AI-native organization collapses the handoff between people who own outcomes and the work itself, so product managers and designers can execute changes through agents. It says PR count and token spend are insufficient measures, and that merge rate better shows whether the new workflow is working. The article also says the boundary should follow decision authority, with engineers still owning architecture and data models.
The author argues that system use cases, with actors, preconditions, scenarios, and acceptance criteria, work better than user stories as the input for AI code generation in enterprise business applications. He describes a process that skips the plan-and-task phase, reverse-engineers legacy systems into use cases and entity models for modernization, and recommends self-contained system verticals and risk-based review.
The article explains how a software factory combines agents, tools, and engineering practices to take work from intent to verified output. It argues that teams should enforce domain rules, workflow gates, and tool permissions independently, version shared guidance and checks, and review lessons before reuse.
OpenAI's DevDay 2026 session demonstrates Codex shifting from a single-user tool to a team-oriented agent. The session shows a persistent personal agent investigating a 2am outage, from the first Slack message through a reviewed fix, using voice, Appshots, plugins, and meeting notes to keep the team informed.
OpenAI's DevDay 2026 video presents what's new in Codex across the CLI, app, and web. Live demos show moving from delegating individual tasks to having Codex tackle entire problems and goals. The source is a short description only, so no specific features or figures are confirmed.
Stack Overflow's small teams used Codex to build Stack Overflow for Agents and reimagine Stack Internal, according to a DevDay 2026 session. The talk covers lessons for accelerating R&D and bringing new products to market.
Theo, creator of the T3 Stack, open-sourced tsc-rs, a line-by-line Rust port of Microsoft's Go-native TypeScript 7 compiler, type checker, and language server under MIT, pinned to typescript-go commit 673a5f17. The author reports tsc-rs is about 1.61× faster than tsc 7 and about 2.95× faster than bun check on six real-app benchmarks on an Apple M4 Pro. The port passes all 181,711 ported Go tests, and CLI output matches the Go version on 120 open-source repos except for known edge cases such as monorepo rootDir and tsc -b incremental output.
AIWhy it matters: The post reports a benchmarked, test-verified Rust port of the TypeScript 7 compiler, with pinned upstream and stated edge cases useful for judging its compatibility.
At the Apsara Conference, Alibaba's Qwen team outlined a roadmap of Qwen4 followed by Qwen4.5 and Qwen5, aiming for 5T to 10T parameters. The article notes that Qwen3.8 reached 2.4T parameters and that Qwen3.8-Flash activates 6B parameters per inference while cutting training cost to one-ninth. It also describes Qwen3.8-Max running model-driven experiments in chip design and inference optimization, and multimodal updates including a video model slated for November.
A paper introduces HERMES, a harness that pairs each repository component with a resident LLM and uses dependency-aware activation and failure diagnosis. With the same model and effort setting, GPT-5.6 Sol's whole-repository migration score rose from 6.5% to 31.0% when Codex was replaced by HERMES. Across four software engineering benchmarks, HERMES beats matched baseline harnesses by 12.4 points on average, and Qwen3-8B components come within 4.5 points of an all-GPT-5.6 Sol setup while cutting Terminal-Bench 4.0 inference cost by 26.2%.
A Chinese podcast transcript argues that Opus 5.5 makes code generation, game modding, and language migration much faster and cheaper. It cites examples such as game remakes, Photoshop clones, and ESP32 firmware projects, and says legal and open-source barriers are struggling to keep pace.
The weekend after Opus 5.5 launched I had my most productive coding day of the year (so far).
Maybe the website is done, but the launch isn’t. Keep going in the same Replit conversation. Ask for a pitch deck or launch graphics. The brand and direction are already there. Build on them without starting over.
Databricks introduces database branching in Lakebase Postgres, letting each coding agent work in its own isolated database branch created in under a second regardless of size. Branches use copy-on-write storage, consuming extra space only as they diverge, and scale to zero when idle so unused branches incur no compute cost. Schema changes are tracked in code and promoted to the parent branch through migrations rather than merged back, and ephemeral branches are created per pull request for testing.
OpenAI's YouTube livestream presents three demos showing how Codex supports production monitoring. The demos cover tracing a checkout failure in Grafana, investigating a Kubernetes rollout causing out-of-memory restarts, and linking a Codex Security finding about a missing resource limit to service availability.
slop is also being used now to say “just made this, it works, up to u”
NVIDIA developers are pairing frontier AI models, including GPT-6 Astra and Claude Fable 5, with Omniverse libraries to turn simulation ideas into working applications. Examples include a humanoid warehouse simulator, an autonomous-driving testing workflow, and sensor-matching digital twins. The projects are guided through natural-language instructions and reviewed by developers.
Anthropic is launching OSS Scanner, a service that uses its frontier models to periodically scan opted-in open-source projects for vulnerabilities at no cost. Its reports provide a proof-of-concept, an explanation, and a suggested fix.
it's built on top of Claude Managed Agents, doing code generation in the cloud sandbo, using Sonnet 5.5 each run costs ~$0.75 you can try it yourself here: https://github.com/ThariqS/ai-newtab/
Lauren Tan argues that with frontier AI agents, anyone can produce code at machine speed, so PR volume now signals productivity alongside impact. She says the bottleneck is trust in agent output, and that higher token costs are worth it compared with hiring many engineers. She frames the engineer's job as building the software-producing machine rather than writing code directly.
The first chart usually raises the next question. Ask it in the same chat and /visualize answers with a new chart.
Claude Haiku 5.5 (1587 pts) is a +257pt improvement over Haiku 4.5 (1330 pts)! It also significantly improved across all categories. Dive into the Code Arena: WebDev at https://arena.ai/leaderboard/code/webdev
Claude Code v2.1.295 adds onFailure: "block" for command and HTTP hooks, so a hook that cannot start, times out, or exits unexpectedly blocks the action. The release also adds an optional models list for Claude apps gateway upstreams, plus upstream_request_id in the inference audit event, and fixes a range of MCP, plugin, and terminal issues.
Google proposed FlowAgent, a ReAct-style agent that generates and validates fixes for pre-submit test failures and shows them in its code review tools. Two abstention filters, before and after execution, suppress weak suggestions; in a manual review of 195 real failures, 67.18% of fixes were correct. After the Google-wide launch, it suggested fixes on 295,508 changes, with developers previewing 65,069 and applying 28,554.
OpenAI's Codex 0.162.0 release adds tools for creating and listing managed Git worktrees from trusted local projects when the worktrees feature is enabled. The update also lets users pin tasks in the agent Command Center, copy transcript blocks with /copy, and make URLs clickable in approval headers, questions, and warnings, along with several Linux and Windows sandbox fixes.
Tessl argues AI code review is slow because generated code outpaces trust, and proposes executable specs that let agents check preview environments against product intent. Its spec reviewer splits work between a planner agent that extracts requirements and parallel verifier agents that test each one against the code and base branch.
Devs and agents are moving faster than ever. Secret protection needs to keep pace. GitHub’s new context-aware classifier checks candidate secrets in under 2 milliseconds and could more than double the number of secrets push protection prevents before they enter repository history. https://github.blog/ai-and-ml/github-copilot/secret-protection-must-scale-with-software/?utm_source=x-promoting-secret-protection-article&utm_medium=social&utm_campaign=secret-protection-oct-2026
Step 5 Preview is now free in @cline for one week. Our flagship model for agentic and professional work. Fire up Cline and show us what you build!
We added OS level sandoxing in Unsloth with bwrap (Linux), seatbelt (Mac) and Windows MXC in Unsloth! Latency per tool call for all is under 100ms. Our software style sandboxing with regex ast checks is 3ms latency as well. Thanks to Windows for collabing with us on MXC!
OpenClaw v2026.9.9 patch release is out 🦞 🧠 GPT-6.1 Sol in Codex + Claude Haiku 5.5 🔧 Better failed-update recovery 💬 Missing iMessage replies fixed ⏰ Scheduled-job fixes Thanks to all 90 contributors! https://docs.openclaw.ai/releases/2026.9.9
JetBrains has released Mellum2.1, a 12B mixture-of-experts thinking model with 2.5B active parameters, under Apache 2.0 on Hugging Face. Post-training reinforcement learning in real software repositories raised SWE-bench Verified from 2.0 to 47.0, according to JetBrains' self-reported results. Qwen3.5-9B still leads on SWE-bench Pro, GPQA Diamond and AIME, and GGUF builds start at 7.0 GB for local use.
Windows now has sandboxing! Microsoft released an open-source repo, mxc, for sandboxed code execution. We collaborated with Windows to add mxc OS level sandboxing to Unsloth which adds just <100 ms of overhead. GitHub: https://github.com/unslothai/unsloth Guide: https://unsloth.ai/docs/new/studio/sandboxing-in-unsloth
Oracle is using ChatGPT Work and Codex to turn specialist knowledge into fast, repeatable workflows across recruiting, engineering, and operations. The source does not provide figures, timelines, or specific results beyond the headline's claim that days of work can take minutes.
Anthropic released Claude Haiku 5.5, raising its OSWorld 2.1 score from 15.7% to 72.4% and supporting a 1 million token context window. The article notes Haiku 5.5 still scores 39.2% on Terminal-Bench 4.0 against Sonnet 5.5's 70.6%, and that prompts above 100,000 tokens are priced higher, so migration costs need to be measured on real workloads.
Augment Code is selling select assets, including Cosmos, Auggie CLI, and the Code Context Engine, to Harness, and the product team is moving to Harness. The company says Harness's integrated platform delivers these capabilities to customers more effectively than building them independently. Harness describes itself as building the Autonomous SDLC Platform for shipping AI-written code across enterprises.
AIWhy it matters: The announcement shows how a coding AI company is folding its products into a larger software delivery platform, a shift that shapes how enterprise teams will buy these tools.
Tessl's Code Review defines review standards as skills in the repository, called lenses, routed to files by a repo-owned profile file. Because these team-visible standards are portable, lessons from review can feed back into code generation and maintenance, not only the next review.