#Coding

AIZed has launched the public beta of Delta, a multiplayer environment for coding with agents and reviewing their work, which replaces pull requests with shared threads. Delta is built on DeltaDB, which records edits and messages between Git commits, and it is free during the beta, with paid plans for individuals and teams to follow.

Why it matters: The post explains how Delta replaces pull requests with shared agent threads and DeltaDB, showing a concrete alternative to the GitHub review workflow.

AIGrok Build now has memory, which records conventions, decisions, and project facts after each completed turn and reads them in later sessions. Notes are stored per project plus a global set, and the /dream command organizes them into topic files while /memory opens a read-only browser. The feature is available now and applies to new sessions.

AICognition and AWS have entered a multi-year Strategic Collaboration Agreement to help enterprises deploy the Devin autonomous engineer in production. Devin can be purchased through AWS Marketplace, and the companies are exploring deeper engineering integrations within customers' AWS environments. Mercedes-Benz reportedly used Devin to analyze more than 200,000 lines of COBOL, reducing an estimated eight-month modernization project to eight days.

Why it matters: The collaboration shows how an autonomous coding agent is being packaged for enterprise legacy modernization inside existing AWS environments, with concrete customer migration figures.

AIFactory has raised $200M at a $5B valuation from investors including Blackstone, Khosla Ventures, and Sequoia Capital, bringing its total funding to over $400 million. The company says it will use the capital to accelerate research, product, and global go-to-market efforts. Factory says hundreds of thousands of developers use its platform, with customers including Nvidia, Blackstone, and T-Mobile.

AIMicrosoft Research's latest Research Focus issue covers how coding agents behave at scale, evaluations of AI models that find lymphoma lesions in PET/CT scans, and understanding AI chatbot dependence. It also features research on advancing large-scale decision-making systems.

AIFireworks AI reports that DeepSeek-V4.1-Flash scores 74.34% pass@1 on DeepSWE at $0.430 per task, close to GPT-6-Astra's 74.12% at $6.524. On Terminal-Bench 2.1 it scores 86.5% against Astra's 87.5% at about 12x lower cost per task, while on HLE it trails Astra alone at 34.52% versus 50.40%. The post also reports that a combined oracle router reaches 54.80% on HLE, and that serverless and dedicated API access is available with US-hosted endpoints coming soon.

AIAugment Code reports that size-adjusted output per active developer rose from 12.3 to 55.7 between November 2025 and July 2026, while median time to merge fell from 11.2 to 3.1 hours. The post says the company added specialized agents wherever work was piling up, across planning, review, verification, feedback, and incident response, and kept engineers responsible for product decisions, architecture, and production risk.

Why it matters: The post pairs internal productivity and quality metrics with the order in which agents were added, showing how review and verification bottlenecks shaped a software delivery pipeline.

AIDeepSeek released open weights for V4.1-Flash, which Baseten now offers through its Model APIs. The model has 552B total parameters, 8B active for prefill and 16B for decode, a 1M token context window, and text plus image input. Its Causal Encoder-Decoder design runs only the encoder during prefill and reuses a projected KV cache, and the source reports the global KV cache at a quarter of V4-Flash's memory.

Why it matters: The post explains how the CED architecture splits prefill and decode compute and cuts KV cache memory, which matters for coding agent costs.

AIAndrew Ng argues that skilled AI engineers increasingly drive the build loop and make product decisions rather than merely implementing specifications from product managers and designers. He identifies four key skills for shaping the build: driving the build loop, making product decisions, communicating and leading, and high-agency ownership.

AICognition is making Fusion available in Devin Desktop and CLI, a harness where a frontier lead model plans and reviews while a cheaper sidekick executes. Across listed coding benchmarks, Cognition reports Fusion cuts cost per task by about 11% to 46% versus the lead model alone, while the sidekick does the implementation work. The post recommends pairing Fable 5.1 with SWE-2, and argues price per task matters more than price per token.

AIShanghai Artificial Intelligence Laboratory has released Atria Dawn Preview, an agentic model built on the 744B-parameter MoE GLM-5.2 foundation model, with a 256K context window. The release page reports benchmark results across search, coding, tool use, productivity, and cybersecurity, and describes text-only setup for Codex and Claude Code.

Why it matters: The release page gives a full benchmark table against named rivals and setup steps for Codex and Claude Code, useful for anyone evaluating agentic models.

AIClare Liguori published a manifesto with 10 principles for developers who use AI coding tools but feel they are not shipping much faster. Werner Vogels, owner of this account, called it mandatory reading. The principles are drawn from practices she has seen work across Amazon teams.

AICognition introduces SWE-2, a coding model post-trained from Kimi K3 that scores 50.0% on FrontierCode 1.1 Main, within one point of Fable 5.1 while costing 64% less. The post attributes the gains to an RL algorithm that trains all reasoning-effort levels in one run, with cost penalties tuned to the base model's Pareto frontier. SWE-2 is available starting today in Devin Desktop and CLI, with rollout to Devin Web and Fusion.

Why it matters: The post explains how the cost penalty and length-weighted baseline are derived, which helps readers judge the tradeoffs in coding model post-training.

AISherwin Wu, an OpenAI executive, says employees now use Astra to vibe-code custom forms, deploy them on ChatGPT, and share the links instead of Google Forms. The post describes this as an emerging internal use case around ChatGPT sites.

AIMistral AI helped a European energy operator migrate 40,000 lines of Fortran 77 to C++ for a reservoir simulator with no test suite. The post explains a parity harness that checks numerical agreement between the two codebases, and a workflow where agents coder, tester, and reviewer migrate modules under human review. Its authors note the approach covered the self-contained first sprint of 40,000 of 300,000 lines and that dependent systems would bring additional challenges.

AIGoogle Developers Blog argues that teams building AI coding agents should replace end-to-end benchmark scores with behavioral evaluations that test discrete, observable actions. Examples include asking clarifying questions on underspecified prompts, running a local validator before marking a build change complete, and consulting live search for current information. The post recommends fast, deterministic unit-style checks, outcome-based LLM-as-a-judge checks for complex tasks, and batch runs that track aggregate pass rates over time.

AIAmazon is giving students a free full year of Kiro, its spec-driven coding agent, at 132 universities across 18 countries. The program aims to help students move from idea to working application, the same way teams at Delta, Ericsson, Siemens, and Amazon do.

AICognition has raised over $2B at a $48B valuation, led by Andreessen Horowitz and Accel. The company says run-rate revenue grew from $492M to almost $900M since its May round, and Devin now offers Auto-Triage, Security Swarm, and Automations.

AIXiaomi MiMo has launched MiMo Desktop in invite-only beta, a desktop agent that turns Office files, images, video, audio, and zips into finished, editable output. Invitees also get limited access to next-gen MiMo models, and the post lists features including live previews, region-based editing with versioned rollback, automatic model routing, and browser and computer use with record and replay.

AIOrbital is building an operating system that lets non-CS domains like science and mechanical engineering use its team's computer science expertise to build complex apps and research tools. The author argues that clearly specifying what you want from AI is the key lever for getting value, and that robust results are possible without a CS degree if the right pieces are in place. A quoted post on an ETH Zurich study of 100 developers suggests computer science background predicts vibe coding success more strongly than writing skill.

AIOpenBMB has released MiniCPM5-2B, a dense 2B Transformer built for on-device and resource-constrained deployment, with an average score of 53.9 in its comparison set. The release also opens the UltraData datasets behind it, including UltraX, UltraData-Code, UltraData-SFT-Agent-2609 and UltraData-RL-2609, and includes GGUF, MLX, GPTQ and DSpark variants for common runtimes.

Why it matters: The release pairs a 2B model with open training datasets and reports per-benchmark comparisons against named same-size and larger models, letting readers check the claims directly.

AIMeta's AIRA₃ entered the live competition with an ensemble of models, and the 8th-ranked gold-medal entry combined GPT 5.5 (w/ OpenCode) and Claude 4.8 (w/ ClaudeCode). Post-hoc testing found Muse Spark 1.2 (w/ MuseCode) also reached gold-medal level, while Muse Spark 1.1 (w/ OpenCode) and GLM 5.2 (w/ OpenCode) reached silver-medal level, all graded on the same private test set.

AIA Berkeley Sky Lab researcher says stronger open models and new inference systems will make powerful local AI practical. The linked post reports Qwen3.8-Flash-Next running at 68.3 tok/s on a single RTX 5090 using an NVFP4 checkpoint, with 63GB host RAM and a 51GB n-gram table stored on NVMe at about 0.5% throughput cost.

AIAndrew Ng presented an AI Engineering Skills Map for using coding agents such as Claude Code, Codex, Cursor, OpenCode, and Pi. The workflow he describes covers planning, execution, and deployment with monitoring, and he identifies five key skills: directing the workflow, enabling agent autonomy, reviewing the work, customizing the agent and its environment, and coding agent foundations. The source says these skills matter more as the agents evolve quickly.

AIOpenAI researcher Mark Chen announced GPT-6 Astra, which he described as the company's most capable and aligned model yet. He said it can build and test software, work across apps on a computer, and help with open scientific problems. The post also highlights improved computer use compared with Operator and stronger monitoring that can stop potentially unauthorized agent actions.

Why it matters: The post links a named model release to specific capabilities like computer use and aligned agent behavior, giving readers concrete claims to check against the model.

AIMicrosoft and Copilot's Thomas Dohmke announced a search tool that understands a codebase beyond literal phrases, returning results based on intent, semantic reasoning, and the context behind key decisions. The post's quoted Entire context describes Agentic Search, an API across accessible repos that returns the code, session, transcript, and prompt behind a change.

AIThomas Dohmke, owner of Microsoft and Copilot-related accounts, says a team's new tool answers difficult codebase questions using half the tokens and half the steps of the GitHub CLI. The post gives no further technical details, and the tool is available at entire.com.

AIMihail Eric announced the 2026 edition of his Stanford course "The Modern Software Developer," with 85% of the Fall 2025 material replaced by AI-native topics such as agent skills, context engineering, and agentic code review. Students will ship pull requests to real open-source AI repositories, with partners including Browserbase, HeyGen, and CopilotKit offering mentorship.

AIMeituan's LongCat-2.0 is now available free in Command Code, the AI coding tool. The model has 1.6T parameters, 48B activated, and a 1M-token context window. It is available on all Command Code plans to all subscribers.

AIGoogle introduces Gemini 3.8 Flash for coding, agentic tasks, and multi-step reasoning, priced at $0.75 per million input tokens and $3.75 per million output tokens during the introductory period. Gemini 3.8 Flash Cyber targets vulnerability detection and automated patching and is available only to trusted defenders through the new Fairwind Program. The introductory price expires December 31, 2026, after which $1.50 and $7.50 per million tokens apply.

Why it matters: The post separates a general coding and agent model from a restricted cyber variant, showing how one shared core is deployed under different access and safety tiers.

AIwith gains over 3.7 Flash in software engineering, agentic tasks, and multi-step reasoning. Sundar Pichai says it outperforms most larger frontier models on DeepSWE v1.1 at a fraction of the cost. The comparison table lists input at $0.75 and output at $3.75 per 1M tokens, with introductory pricing through December 31, 2026.

AIGoogle's Gemini 3.8 Flash is out, and Varun Mohan says it substantially improves on 3.7 Flash for agentic coding and general knowledge work. It is now available to everyone on Antigravity. The attached benchmark table lists Gemini 3.8 Flash at $0.75 per 1M input tokens and $3.75 per 1M output tokens, with introductory pricing through December 31, 2026.

AIGoogle AI Developers says Gemini 3.8 Flash, built for complex reasoning, generated an interactive 3D visualizer using Three.js in Google AI Studio. The visualizer produces physically proportioned teardowns of hardware devices, automatically splitting each device into layers that users can explode and inspect with a deconstruction slider.

AIGoogle's Gemini 3.8 Flash reached 73.7% on the DeepSWE 1.1 benchmark, according to a post from Logan Kilpatrick. The post gives no further details on methodology, comparisons, or pricing.

AIGoogle's Koray Kavukcuoglu says Gemini 3.8 Flash is a major step up from Gemini 3.7 Flash and outperforms most larger frontier models on complex engineering problems at a fraction of the cost. The attached DeepSWE V1.1 chart, sourced to Datacurve AI, plots average cost per task against score for Gemini 3.8 Flash and other models. A link to Google's blog post with more details is included.

AIGoogle announced Gemini 3.8 Flash, its third updated Flash model in six weeks, citing improvements in agentic and coding capabilities. The benchmark table lists input at $0.75 and output at $3.75 per 1M tokens, with introductory pricing of $1.50 and $7.50 expiring December 31, 2026. Terminal-bench 2.1 shows 89.4% for Gemini 3.8 Flash against 85.8% for Gemini 3.7 Flash.

AIGoogle AI Studio announced Gemini 3.8 Flash, which it calls its most intelligent workhorse model. The company says it brings significant improvements over 3.7 Flash in software engineering, agentic tasks, and multi-step reasoning in specialized domains. It is available at the same introductory price as 3.7 Flash, $0.75 per million input tokens and $3.75 per million output tokens, through the Gemini API and AI Studio.

AIGoogle has released gemini-3.8-flash, described as its most intelligent Flash model, for long-horizon software engineering, autonomous agents, and complex enterprise workflows. The Gemini 3.8 Flash model page and the Latest model guide are linked for getting started.

AIMeituan's LongCat-2.0, a 1.6T open-weights MoE model with a 1M context window, is now free to use in Cline. Cline's post says it scores similarly to Claude Opus 4.7 and Gemini 3.1 Pro. Users can select it under free models via /model after installing Cline with npm i -g cline.

AIAnthropic's team says Claude Fable 5.1 has let them take on projects that previously would have taken months, and invites users to try it in Claude Code, Claude Cowork, and Claude Tag. The post asks what big bets users want to make, and it builds on Anthropic's announcement of Claude Fable 5.1 and Claude Mythos 5.1 as its most advanced models for coding and knowledge work.