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#Coding

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Sep 16

Sep 16Wed
  1. TinkerOfficialAI score32

    Sundial trains Inkling-Small to fix LaTeX errors in under a second

    AISundial fine-tuned Thinking Machines' Inkling-Small with RLVR on 3,978 verified TeX.StackExchange fixes, using rewards for compilation and PDF match and penalties for removed content. The trained model fixes 83.7% of LaTeX errors in under one second at $0.0013 per fix, according to the post. Sundial says it is rolling out the model in its editor, applying fixes as suggestions and rebuilding the PDF.

  2. Kilo (acq. by Anaconda)OfficialAI score40

    Kilo Mobile lets users run full AI agent loops from their phone

    AIKilo Mobile now lets users spawn Cloud Agents, start sessions on remote machines, and dictate prompts by voice from a phone. Users can also review and comment on pull requests and approve Security Agent remediations without a laptop. On iPhone, Live Activities show session status on the Lock Screen when an agent needs input.

    Image from @kilocode's post
  3. Matei ZahariaXAI score44

    Agent harness choice strongly affects coding cost, not task success rate

    AIMatei Zaharia says agent harnesses make a large difference in cost, even on open-source coding benchmarks, and Melissa Pan's research examines why. Her quoted evaluation of seven models across Claude Code, Codex, and Pi found harness choice had little effect on task success but significantly affected cost. A simple harness can be competitive, and the native harness is not always the best.

  4. Greg BrockmanXAI score22

    Codex voice coming to CarPlay for hands-free road-trip coding

    AIGreg Brockman shared a demo of Codex voice running in CarPlay, letting users build software by speaking while driving. A quoted post from Jonathan Roomer says the setup runs through a third-party iOS app that connects ChatGPT Voice to Codex and his Mac.

Sep 15

Sep 15Tue
  1. Zed BlogOfficialAI score72

    Zed launches Delta public beta to replace pull requests with agent threads

    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.

  2. Claude Apps Release NotesOfficialAI score72

    Claude Cowork moves into every conversation, adding designs, slides, and docs

    AIClaude now makes Cowork capabilities available from any conversation without choosing a mode first, with chats, tasks, projects, connectors, and skills carrying over. Users can also create designs, decks, and docs in any conversation, including Claude Code and the Artifacts tab, and edit them with Claude.

    Why it matters: The release merges Cowork tasks into ordinary chats and adds design, slide, and doc creation, changing how Claude users start larger work.

  3. xAI News (Grok)OfficialAI score43

    Grok Build Adds Memory That Saves Project Notes Between Sessions

    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.

  4. Cognition Blog (Devin, Windsurf)OfficialAI score60

    Cognition and AWS sign multi-year deal to deploy Devin for enterprise modernization

    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.

  5. Kilo (acq. by Anaconda)OfficialAI score22

    Kilo App launches on Product Hunt for iOS and Android

    AIKilo announces that its Kilo App is live on Product Hunt, letting users start coding agents, check sessions, and review pull requests from iOS and Android. The company asks supporters to upvote or comment on its Product Hunt listing.

    Image from @kilocode's post

Sep 14

Sep 14Mon
  1. Factory NewsOfficialAI score40

    Factory raises $200M at $5B valuation to scale self-improving enterprise software development

    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.

Sep 13

Sep 13Sun
  1. Fireworks AI BlogOfficialAI score52

    Fireworks adds DeepSeek-V4.1-Flash, matching GPT-6 Astra coding accuracy at 1/15th the cost

    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.

Sep 11

Sep 11Fri
  1. Augment Code BlogOfficialAI score80

    Augment Code details how its software factory raised output per developer 4.5×

    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.

  2. Baseten BlogOfficialAI score62

    DeepSeek-V4.1-Flash arrives on Baseten with a split prefill architecture

    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.

  3. Andrew NgXAI score22

    AI engineers now shape product direction, not just implement specs

    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.

  4. Cognition Blog (Devin, Windsurf)OfficialAI score51

    Cognition introduces Fusion in Devin Desktop and CLI for lower-cost coding

    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.

  5. InternLM (Shanghai AI Lab) · new models on Hugging FaceOfficialAI score72

    Shanghai AI Lab releases Atria Dawn Preview, an agentic model built on GLM-5.2

    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.

Sep 10

Sep 10Thu
  1. Cognition Blog (Devin, Windsurf)OfficialAI score66

    Cognition releases SWE-2, a coding model trained with cost-penalized RL

    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.

Sep 9

Sep 9Wed
  1. Mistral AIOfficialAI score54

    Mistral details how AI agents migrated 40,000 lines of Fortran to C++

    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.

Sep 8

Sep 8Tue
  1. Google Developers BlogOfficialAI score36

    Google Developers Blog outlines behavioral evals for guarding AI coding agents against regressions

    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.

  2. Xiaomi MiMoOfficialAI score52

    Xiaomi MiMo Desktop enters invite-only beta as a desktop agent

    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.

Sep 7

Sep 7Mon
  1. Ian Johnson 🔬🤖XAI score38

    Ian Johnson: knowing what to ask AI for matters most for value

    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.

Sep 6

Sep 6Sun
  1. OpenBMB (MiniCPM) · new models on Hugging FaceOfficialAI score62

    OpenBMB releases MiniCPM5-2B, a 2B open-source model with open training data

    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.

Sep 5

Sep 5Sat
  1. AI at MetaOfficialAI score38

    AIRA₃ ensemble places 8th with gold-medal results in live competition

    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.

    Image from @AIatMeta's post

Sep 4

Sep 4Fri
  1. Matei ZahariaXAI score46

    Qwen3.8-Flash-Next runs at 68.3 tok/s on a single RTX 5090

    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.

  2. Andrew NgXAI score42

    Andrew Ng maps key skills for using AI coding agents effectively

    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.

Sep 3

Sep 3Thu
  1. TinkerOfficialAI score51

    Bespoke Labs post-trains Inkling on one code repo and reports broader coding gains

    AIBespoke Labs post-trained the Inkling base model on a single GitHub repository using supervised fine-tuning and GRPO reinforcement learning. The post reports a 57-point improvement on the held-out fontTools evaluation over the base model, along with gains on Terminal-Bench 2.1 and SWE-bench Lite. It also says the post-trained model uses about 40% fewer tokens.

    Image from @tinkerapi's post
  2. Mark ChenXAI score80

    Mark Chen announces GPT-6 Astra with computer use and agent oversight

    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.

  3. Thomas DohmkeXAI score38

    Copilot's new search tool understands codebase intent and decision context

    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.

Sep 2

Sep 2Wed
  1. Daniel HanXAI score34

    Stanford's Modern Software Developer course adds AI-native engineering curriculum

    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.

  2. Meituan LongCatOfficialAI score29

    LongCat-2.0 now free to use in Command Code

    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.

  3. Google AI StudioOfficialAI score78

    Google releases Gemini 3.8 Flash and restricted 3.8 Flash Cyber model

    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.

  4. Sundar PichaiXAI score62

    Google introduces Gemini 3.8 Flash, its third Flash release in six weeks

    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.

    Why it matters: The benchmark table compares Gemini 3.8 Flash with Gemini 3.7 Flash and rival models on price, coding, agent, and reasoning tasks, which helps readers judge the tradeoffs.

    Image from @sundarpichai's post
  5. Varun MohanXAI score57

    Gemini 3.8 Flash released with gains in agentic coding and knowledge work

    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.

    Image from @_mohansolo's post