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#Coding

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Aug 5

Aug 5Wed
  1. Meituan LongCatOfficialAI score34

    LongCat-2.0 is now free on OpenCode for coding

    AIMeituan's LongCat-2.0, a coding-optimized model with 1M context and full open-source availability, is now free to use on OpenCode. The announcement comes from Meituan LongCat's official X account and does not include pricing details beyond the free offer.

  2. Prime Intellect BlogOfficialAI score75

    Prime Agent launches open-source self-improving RLM coding harness

    AIPrime Agent is a new open-source coding harness built on a persistent IPython kernel, a Recursive Language Model design, and Continual Harness state that the agent can create, read, update, and delete. Prime Intellect reports ARC-AGI-3 results of 95.5% RHAE Best@1 with Opus 5 and competitive long-context scores with the open-weights GLM-5.2 model.

    Why it matters: The post explains how the RLM and Continual Harness designs let an agent write code against its own context, sub-agents, and harness state, with benchmark evidence.

Aug 4

Aug 4Tue
  1. Zed BlogOfficialAI score65

    Zed Enables OS-Level Sandboxing by Default for Its Agent Panel

    AIZed's agent panel now sandboxes its terminal and fetch tools by default, starting in release 1.14, and the restrictions are enforced by the operating system rather than by agent instructions. By default the sandbox blocks writes outside project directories, writes to .git, and network requests, and agents can request temporary escalation with a stated reason. The post also notes that sandboxing covers only those tools and does not protect against other tools, external programs, or the regular built-in terminal.

    Why it matters: The post explains how OS-enforced sandboxing limits agent terminal and fetch access, and why fine-grained command rules fall short of it.

  2. Mckay WrigleyXAI score26

    Mckay Wrigley bets on blending multiple AI models into smoother intelligence

    AIMckay Wrigley argues that model routers can match performance at lower cost, and that blending multiple imperfect models could yield far smoother intelligence. He calls this emerging approach "model melding." The post pairs with a Not Diamond Code announcement, which says its router cuts costs 20-65% for coding agents without hurting quality.

Aug 3

Aug 3Mon
  1. JetBrains AI BlogOfficialAI score52

    JetBrains Built a Central CLI to Control Spiraling AI Tool Costs

    AIJetBrains says its AI development expenses rose roughly 10x over six months as developers adopted three to five AI tools each. It built the JetBrains Central CLI, which routes third-party agent traffic through its AI platform so managers can set per-developer and team limits and view consumption reports. The CLI opened to early access on July 8 for anyone with JetBrains AI credits.

Aug 2

Aug 2Sun
  1. OpenRouter BlogOfficialAI score40

    OpenRouter Launches Ori Eval to Find the Best AI Model for Your App

    AIOpenRouter has released Ori Eval, an agent-driven tool that runs your app's prompts against candidate models and returns a comparison table of catch rate, latency, cost per PR, and pass/fail results. The tool asserts on called tools and grades open-ended answers with an LLM judge, pinning the harness and model during each run. Its evals are code files that can run in CI to block regressions and re-run when new models ship.

Aug 1

Aug 1Sat
  1. Andrej KarpathyXAI score66

    Karpathy tests Opus 5 by rendering Lord of the Rings opening in 3D

    AIAndrej Karpathy gave Claude Opus 5 the first paragraph of Lord of the Rings with a 1M token budget and asked for a Three.js render. Opus spent about two hours writing 5500 lines of code that procedurally renders the story, which Karpathy calls janky but fun. He notes the model struggled to audit its work because it cannot efficiently perceive video or play the resulting game, relying on slow screenshots that led to several errors.

    Video from @karpathy's post

Jul 31

Jul 31Fri
  1. DeepSeek API NewsOfficialAI score67

    DeepSeek-V4-Flash API enters public beta with stronger agent benchmarks

    AIDeepSeek has released the DeepSeek-V4-Flash API in public beta, and developers can use the latest version by setting the model name to deepseek-v4-flash. The source reports agent benchmark results far above V4-Pro-Preview, including 82.7 on Terminal Bench 2.1 and 70.3 on Toolathlon verified. V4-Flash natively supports the Responses API format and is adapted for Codex, while V4-Pro and the APP/WEB models are unchanged.

    Why it matters: The release lists agent benchmark results against V4-Pro-Preview and notes Responses API support for Codex, which helps developers gauge the upgrade's practical effect on their workflows.

Jul 30

Jul 30Thu
  1. Thinking MachinesOfficialAI score44

    Thinking Machines' Inkling-Small Gains From Lessons of Larger Inkling

    AIThinking Machines says Inkling-Small began training after its larger counterpart and benefits from the lessons learned. The post cites an improved pre-training data mix, a refined ML recipe, on-policy distillation using Inkling as the teacher, and two additional weeks of agentic coding RL.

Jul 29

Jul 29Wed
  1. Air Street PressBlogAI score75

    Poolside's Laguna S 2.1 is an open agentic coding model that runs on one DGX Spark

    AIPoolside released Laguna S 2.1, an open-weights agentic coding model with 118 billion total parameters and about 8 billion active per token, supporting up to a million tokens of context. Quantized, it fits on one NVIDIA DGX Spark, and Poolside reports 70.2% on Terminal-Bench 2.1 with thinking enabled, with its evaluation trajectories published online. The same week it shipped the Poolside Desktop Assistant for macOS, which runs Laguna locally or alongside Claude Code, Codex, and Gemini agents.

Jul 28

Jul 28Tue
  1. Augment Code BlogOfficialAI score39

    GPT-5.6 Sol Becomes Augment Cosmos's Default Model for Token Efficiency

    AIAugment Code has made GPT-5.6 Sol the default model in Cosmos, choosing it as the most token-efficient model to clear its pass-rate floor for long-horizon software engineering tasks. The company ranks models by cost per task rather than list price per million tokens, since retries on failed steps add token spend. Users can still select any model, and the default will change as more token-efficient models emerge.

  2. JetBrains AI BlogOfficialAI score60

    Ponytail Skill Cuts Claude Code Costs 10% But Not the Advertised 54%

    AIJetBrains tested the ponytail skill for Claude Code across 80 paired tasks and found a median 10.3% cost reduction, with p=0.004. Code written fell about 15% median versus the advertised 54%, reaching 31% on larger builds and little on already-lean tasks. No quality difference was detected, and the skill only self-activated when its ruleset was injected by a plugin hook.

    Why it matters: The benchmark separates advertised savings from measured results and shows the code cut depends on how much the baseline agent over-builds.

Jul 27

Jul 27Mon

Jul 26

Jul 26Sun
  1. Fireworks AI BlogOfficialAI score60

    Fireworks AI adds open-weight Kimi K3 with US-only serverless endpoints

    AIFireworks AI made the open-weight Kimi K3 available for inference and training on its platform, with US-only serverless endpoints and Zero Data Retention. In its own head-to-head with Opus 5, the post reports K3 at 92.7% accuracy and $0.52 per task on SWE (480) against Opus 5's 94.8% and $1.05, with the vendor claiming up to 5x better cost efficiency per task.

    Why it matters: The post compares Kimi K3 with Opus 5 on accuracy and cost per task, giving readers concrete figures to judge the open model against closed alternatives for their own workloads.

  2. Philipp SchmidBlogAI score62

    EvoCode-Bench Tests Coding Agents Across Multi-Turn Iterative Specification Changes

    AIEvoCode-Bench is a multi-turn coding benchmark with 26 tasks spanning 227 sequential rounds, where agents keep a persistent workspace and must pass cumulative tests after each evolving instruction. The results show that agents perform much worse when building on their own prior work than when starting from a clean, human-completed codebase. Regressions, not failure to implement new features, are the main bottleneck, and agents that maintained a persistent requirements document more than doubled their success rates.

Jul 25

Jul 25Sat

Jul 24

Jul 24Fri
  1. Noah ZwebenXAI score44

    Noah Zweben shares a favorite Opus 5 anecdote from his TA days

    AIAnthropic's Noah Zweben says a tornado-physics assignment he once TA'd for, built in Unity, is his favorite Opus 5 example so far. The quoted Atomic Chat post compares Opus 5, Fable 5, Kimi K3, and GPT 5.6 on three HTML physics scenes, with Opus 5 costing $1.40 versus Fable 5's $2.82.

  2. Mike KriegerXAI score22

    Mike Krieger says models now build games from brief, dynamic prompts

    AIMike Krieger, who is associated with Anthropic, says two games were built from prompts of about four sentences that used dynamic /workflows extensively. He contrasts this with earlier in the year, when he relied on a bespoke harness and verification system, noting that current models accomplish much more with far less instruction.

  3. Mike KriegerXAI score46

    Mike Krieger says Claude Opus 5 became his daily driver

    AIAnthropic co-founder Mike Krieger says Claude Opus 5 has become his daily driver at work and on weekends. He reports it can work for hours on complex tasks and consistently gets to the bottom of tricky problems, and he has also built some games with it. Anthropic's announcement describes Opus 5 as close to the frontier intelligence of Fable 5 at half the price.

Jul 23

Jul 23Thu
  1. Matei ZahariaXAI score36

    Berkeley STAR Lab packages AI research optimizers into one GEPA API

    AIBerkeley's STAR Lab packaged multiple LLM-based "autoresearch" algorithms into a single API within the GEPA package, letting users mix and match them. The optimizers can be applied to tasks including prompt writing, agent design, and code optimization. The quoted thread adds that GEPA, AutoResearch, and Meta-Harness each win on different tasks, and that the new optimize_anything omni meta-optimizer beats every standalone optimizer at a matched budget.

  2. One Useful Thing (Ethan Mollick)BlogAI score67

    Ethan Mollick's guide to choosing AI tools for agentic work

    AIEthan Mollick's guide says ChatGPT and Claude are the main choices for real work, since their agent modes can act on a computer. He separates agent modes that run on the company's computers from those that access the user's own computer. He recommends keeping approval settings on for sending, spending, or deleting, because of prompt injection risk. He also notes that Gemini currently lags for agentic work, though its Notebook and video tools are useful.

Jul 22

Jul 22Wed
  1. Cognition Blog (Devin, Windsurf)OfficialAI score41

    Cognition signs MOU with U.S. Department of Energy to join Genesis Mission

    AICognition has signed a memorandum of understanding with the U.S. Department of Energy to join the Genesis Mission, a national AI initiative launched by executive order in November 2025. Cognition will contribute its Devin autonomous AI software engineer in four areas: software and data security, modernizing legacy scientific code, expanding scientific workforce capacity, and cloud modernization. Devin Desktop and CLI are listed as FedRAMP Class D (High) Authorized, and the company has offered in-kind code security scans for national laboratory codebases.

Jul 21

Jul 21Tue
  1. Bryan CatanzaroXAI score57

    Poolside releases open-weight Laguna S 2.1 for agentic coding

    AIPoolside released Laguna S 2.1, an open-weight model with 118B total parameters and 8B active per token. The author says it performs strongly on agentic coding and long-horizon tasks, and it can run on a single NVIDIA DGX Spark. Weights are on Hugging Face under the OpenMDW-1.1 license, with access also available through OpenRouter and Poolside's API.

  2. JetBrains AI BlogOfficialAI score55

    JetBrains Air adds ACP agents, local models, and Java/Kotlin code intelligence

    AIJetBrains Air now connects to ACP-compatible coding agents, including GitHub Copilot CLI, OpenCode, Pi, and Cline, through the Agent Client Protocol. The release also adds Beta Java and Kotlin navigation and diagnostics powered by the IntelliJ IDEA code engine, local model support through Ollama or LM Studio, and Docker-based agent tasks on Windows.

  3. koray kavukcuogluXAI score72

    Google releases Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

    AIGoogle introduces Gemini 3.6 Flash as its workhorse model, with better coding, knowledge work, and multimodal performance while reducing token usage. It also launches Gemini 3.5 Flash-Lite, described as the fastest and most cost-effective 3.5-class model for high-throughput applications, and 3.5 Flash Cyber, a version of 3.5 Flash fine-tuned to find and fix cybersecurity vulnerabilities.

    Why it matters: The post lists three distinct models, each aimed at a different job, so readers can map which one fits coding, high-volume, or security workloads.

    Video from @koraykv's post
  4. JetBrains AI BlogOfficialAI score62

    JetBrains Context adds repository indexing to coding agents in early access

    AIJetBrains has launched JetBrains Context in early access, a repository intelligence layer that builds a semantic index so coding agents can retrieve relevant code without repeated searching. In tests on 205 SWE-bench tasks, 175 production-monorepo tasks, and 1,953 code-localization tasks, it reduced agent turns by up to 68%, latency by up to 59%, and execution cost by up to 48%. It works with Claude Code, Codex CLI, and Junie CLI at no additional cost for JetBrains AI subscribers, and it does not store source code on JetBrains Context servers.

    Why it matters: The source gives benchmark figures for turns, latency, and cost, showing how repository indexing might change agent workflows on large codebases.

Jul 20

Jul 20Mon

Jul 14

Jul 14Tue
  1. Cognition Blog (Devin, Windsurf)OfficialAI score44

    Cognition Marks One Year Since Windsurf Merger With Devin and SWE Model Gains

    AICognition says its one-year-old merger with Windsurf has produced a more capable Devin, which now manages other Devins at a mid-to-senior engineering level, and new SWE-1.7 model, described as its most capable and efficient to date. The company reports growing from 44 to 350 people and revenue run rate from $73M to $500M+ since merging the brands.

Jul 13

Jul 13Mon
  1. Cognition Blog (Devin, Windsurf)OfficialAI score62

    Fable 5 with a sidekick costs less than Opus 4.8 on FrontierCode

    AICognition found that Fable 5 led runs cost less than Opus 4.8 led runs on FrontierCode 1.1 when both used the same sidekick, $1.86 versus $2.04 per run. Fable 5 scored 60.7 against 54.6 for Opus 4.8 in those configurations, and it took fewer lead turns, delegated earlier, and rarely edited code itself. The post attributes the difference to delegation style rather than per-token price, and notes that the approach gives little benefit on short or serial debugging tasks.

    Why it matters: The source compares lead-model delegation habits on a coding benchmark, showing how a pricier model can lower total agent cost through fewer turns and better handoffs.

  2. Cognition Blog (Devin, Windsurf)OfficialAI score39

    Cognition's Devin Reaches FedRAMP High In-Process for Federal Engineering Teams

    AICognition's entire platform, including Devin Cloud, is now FedRAMP Class D (High) In-Process and listed on the FedRAMP Marketplace, extending FedRAMP High authorization beyond Devin Desktop (formerly Windsurf). Devin Desktop and CLI are already FedRAMP High Authorized for workloads with ITAR and DoW IL4, IL5, and IL6 requirements. The company says Devin Security Swarm can find and validate vulnerabilities and open remediation pull requests, and that fleets of Devins can upgrade legacy software 5-40x faster than humans alone.

Jul 12

Jul 12Sun

Jul 10

Jul 10Fri