coding

Poolside releases Laguna S 2.1, a 118B total parameter Mixture-of-Experts model with 8B activated parameters per token and up to 1M token context, achieving competitive scores on long-horizon coding benchmarks and touted as the most capable agentic coding model in its weight class.

Google DeepMind released Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber, focusing on efficiency, coding, and cybersecurity, but the anticipated Gemini 3.5 Pro was not included due to internal delays.

Google's Gemini 3.6 Flash model is now generally available in GitHub Copilot, designed for web and app development, coding, and agentic tasks, with higher task-completion rates and better token efficiency than its predecessor.

Google introduces Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber models, offering improved token efficiency, lower latency, and better performance for agentic workflows, with 3.6 Flash reducing output token usage by 17% and showing gains in coding and knowledge tasks.

A 15-page paper introduces cohesion-aware task partitioning to improve scaling in multi-agent coding, outlining a new meta process from prompt to graph.

A user shares their experience spending over $100/day on AI tokens via OpenRouter, primarily for coding tasks, and asks for cost reduction advice.

LM Studio launches Bionic, an AI agent for open models that supports coding, document work, and offline voice transcription, with flexible model execution and zero data retention.

Kimi K3 coding benchmarks article discussing performance of the Kimi K3 model on coding tasks.

Kimi K3, a new AI model with 2.8 trillion parameters and 1 million context length, has been released on web and app, featuring leading capabilities in coding, agentic tasks, reasoning, vision, and agent swarms.

A user tests various small AI models for coding tasks, finding Qwen3.6-27B-NVFP4 to be the best balance of speed and accuracy, and notes poor Java performance in these models.

Thinking Machines releases Inkling, an MoE model with 975B total / 41B active parameters, supporting native text, image, and audio reasoning, up to 1M-token context, and full weights availability.

Thinking Machines Lab, founded by ex-OpenAI executives, releases its first open-weight AI model, Inkling, a 975-billion-parameter model capable of reasoning, coding, and processing audio, video, and text.

A tweet expressing fear over a perceived major disruption to software engineering caused by an AI advancement.

Kimi K3, the latest open-weight model from Moonshot, launches with a new architecture, agent swarm capabilities, and focus on long-horizon agent workflows, positioning it as a major contender against other top models.

Matt Pocock clarifies the intended workflow for /wayfinder, emphasizing the flow from /wayfinder to /to-spec to /to-tickets to /implement for coding projects, and notes that v1.2 is in development.

Argues that despite AI coding agents, humans still benefit from writing code for better understanding, ownership, and maintaining software quality.

This paper introduces a compete-then-collaborate framework where multiple frontier AI teachers (Claude, Codex-GPT, Grok, Gemini) are ranked by execution-based tests and then collaborate to build a verifiable curriculum. It finds that imitation (SFT) on teacher solutions degrades a competent coder student, while using the same curriculum for reinforcement learning with verifiable rewards (RLVR) improves performance, particularly on competition problems.

OpenAI launched GPT-5.6, a family of three models (Sol, Terra, Luna) with improved efficiency, cybersecurity capabilities, and competitive pricing, aimed at enterprise and coding tasks.

Muse Spark 1.1, a new agentic and coding model from Meta, achieves +5% improvement on HealthBench-Pro, outperforming all competitors except Fable and Mythos.

Matt Pocock released v1.1 of his skills tool, featuring new commands for planning, specification, implementation, and code review. The poster switched from superpowers to this tool.