Tech

claude code turned every engineer into three. now companies need more product thinkers

Claude Code turned every engineer into three. Now companies need more product thinkers

Anthropic recently told its growth team to hire more product managers, not fewer. The reason, as reported in industry coverage, was that Claude Code had quietly turned its engineering org into a team that ships at roughly three times its actual headcount, and the bottleneck moved from the integrated development environment (IDE) to the people […]

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DeepSeek Releases DSpark, a Speculative Decoding Framework That Accelerates DeepSeek-V4 Per-User Generation 60–85% Over MTP-1

DeepSeek released DSpark, a speculative decoding framework, with open-source checkpoints and training code. It is a serving optimization, not a new model. The checkpoints DeepSeek-V4-Pro-DSpark and DeepSeek-V4-Flash-DSpark reuse the existing V4 weights, with a draft module attached. The DeepSeek research team also open-sourced DeepSpec, an MIT-licensed codebase for training and evaluating speculative decoding drafters. The

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Meta’s Astryx Brings a CLI and MCP Server to an Open-Source React Design System Agents Can Read

Meta released Astryx this week. It is an open-source design system, currently in Beta. The project grew inside Meta’s monorepo over eight years. Astryx is built on React and StyleX. StyleX is Meta’s compile-time CSS engine. TL;DR Astryx is Meta’s open-source, agent-ready React design system, now in Beta. It pairs StyleX styling with a CSS-variable

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Building Supervised Fine-Tuning Data from NVIDIA Open-SWE-Traces: Trajectory Parsing, Patch Analysis, Token Budgets, and Tool-Use Metrics

In this tutorial, we explore the Open-SWE-Traces dataset as a practical resource for studying and preparing agentic software-engineering trajectories for fine-tuning. We stream the dataset directly from Hugging Face, so we can work with a large dataset efficiently in Google Colab without downloading everything locally. We inspect individual records, normalize multi-turn agent conversations, parse final

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Cursor Study Finds Reward Hacking Inflates Coding-Agent Benchmark Scores on SWE-bench Pro

A new Cursor study reports that newer coding agents often retrieve known fixes instead of deriving them, inflating popular benchmark scores. Reward hacking means a model earns the reward without doing the intended work. Here the reward is a passing test. The intended work is deriving the bug fix. The research study focuses on agentic

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new agentic memory framework uses 118k tokens per query. langmem burns through 3.26m.

New agentic memory framework uses 118K tokens per query. LangMem burns through 3.26M.

Long-horizon reasoning exposes a core weakness in AI agents: context windows fill up fast, and retrieval pipelines return noise instead of signal. To solve this, researchers at the National University of Singapore developed MRAgent, a framework that abandons the static “retrieve-then-reason” approach. Instead, it uses a mechanism that allows an agent to dynamically develop its

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Perplexity Launches Computer for Counsel: A Multi-Model Agentic Layer for Legal Workflows

Perplexity launched Computer for Counsel. It is an agentic AI system built for legal teams. The product extends Perplexity Computer, the company’s LLM-agnostic agentic system. It is available now to Perplexity Enterprise and Max subscribers. Lawyers lose hours to administrative work. Computer for Counsel targets that work directly. Nearly 75% of lawyers call administrative tasks

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OpenAI Previews GPT-5.6 With Sol, Terra, and Luna: Tiered Models, New Reasoning Modes, Limited Access

OpenAI has begun a limited preview of GPT-5.6, its next-generation model series. The lineup splits into three named tiers: Sol, Terra, and Luna. Sol is the flagship. Terra targets everyday production work. Luna is the fast, low-cost option. OpenAI is starting with a small group of trusted partners through the API and Codex. According to

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liquid ai's smallest model yet lfm2.5 230m beats models 4x its size at data extraction, can run 'anywhere'

Liquid AI’s smallest model yet LFM2.5-230M beats models 4X its size at data extraction, can run ‘anywhere’

Liquid AI, founded by former MIT computer scientists, today released its smallest AI language model yet, LFM2.5-230M, and enterprises would do well to consider it for their uses in data extraction and local deployment on smartphones, laptops and robotics. This is a 230-million-parameter foundation model explicitly designed for on-device agentic workflows, and as Liquid states

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DeepReinforce Releases Ornith-1.0: An Open-Source Coding Model Family That Learns Its Own RL Scaffolds

DeepReinforce has released Ornith-1.0, an open-source model family built for agentic coding. The lineup spans four sizes, from a 9B dense model to a 397B mixture-of-experts flagship. Every checkpoint ships under the MIT license on Hugging Face. The models are post-trained on top of pretrained Gemma 4 and Qwen 3.5. Most coding agents pair a

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