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Context Engineering Inside the Harness: 4 Mechanisms That Beat Context Overflow and Goal Loss on Long-Horizon Tasks

Survey of four harness mechanisms—context budgeting, compaction, todo-state, and memory—that keep long-horizon LLM agents on task across 200+ tool calls.

The article details how agent harnesses, not larger context windows, solve context overflow and goal loss on long-horizon tasks, citing Chroma's Context Rot report showing 18 LLMs (GPT-4.1, Claude 4, Gemini 2.5, Qwen3) degrade on long inputs. Concrete implementations include LangChain Deep Agents offloading tool responses over 20,000 tokens to the filesystem and truncating old tool calls at 85% window usage, and Claude Code capping auto memory at 25KB while re-reading the 5 most recently modified files after compaction. OpenAI's Responses API now offers server-side compaction via context_management with a standalone /responses/compact endpoint, which Codex uses for long-running coding tasks. Manus reports a roughly 100:1 input-to-output token ratio per ~50-tool-call task, motivating todo.md state recitation to prevent goal drift.

MarkTechPost · 2d agoAI research1

Agent Harness vs Agent Framework vs MCP: Which Layer Owns the Loop, State, Tools, Permissions, and Recovery

Architecture explainer separates agent harnesses, frameworks, and MCP by which layer owns the loop, state, permissions, and recovery.

The article distinguishes agent harnesses (OpenAI Codex, Claude Agent SDK), which own the execution loop, sandbox, permission model, and recovery; frameworks (LangGraph, OpenAI Agents SDK, Microsoft Agent Framework), which supply composable primitives; and MCP, a stateless JSON-RPC wire protocol governed by the Linux Foundation's Agentic AI Foundation since December 2025. An ownership matrix maps the execution loop, state, tool transport, permissions, recovery, sandboxing, and multi-agent orchestration to each layer. The 2026-07-28 MCP specification made the protocol fully stateless, retiring the initialize handshake and session headers.

MarkTechPost · 1d agoAI research1

Rockwell Automation ControlLogix, CompactLogix, CompactLogix 5480, GuardLogix, Compact GuardLogix

CISA advisory maps CVE-2021-42260 to Rockwell ControlLogix, CompactLogix, and GuardLogix controllers with firmware below per-series patch levels.

CISA published an ICS advisory associating CVE-2021-42260 with multiple Rockwell Automation controller families: ControlLogix 5580, GuardLogix 5580, CompactLogix 5380, CompactLogix 5480, and Compact GuardLogix 5380. Affected firmware versions fall below 34.015, 35.014, 36.013, and 37.011 depending on the series. The vendor provides updated firmware as remediation.

CISA Advisories · 14d agoAdvisoryCVE-2021-42260

Privacy-Aligned Personalized Federated Learning with Compact Adaptation and Variable-Length Gaussian Communication

Paper releases a private client context once and confines adaptation to coefficients, matching full-model differential privacy with 2.67x less uplink on CIFAR-10.

The paper addresses the dimensionality misalignment between record-level differential privacy and low-dimensional client variation in personalized federated learning by releasing a private client context once and restricting repeated adaptation to a fixed coefficient space. A variable-length quantized Gaussian mechanism lets quantization error itself serve as the required privacy perturbation. On MNIST and CIFAR-10, the design matches or outperforms full-model private adaptation across privacy budgets and client heterogeneity while cutting protected uplink 2.67x at epsilon=16 on CIFAR-10.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research1

Building and Evaluating Fixed-Voice Thai TTS from Synthetic Speech

Researchers distill a compact 82M-parameter Thai TTS from synthetic OmniVoice data, enabling on-device fixed-voice synthesis without reference audio.

The paper uses a large voice-cloning model (OmniVoice) as a synthetic data source to train Wayu-Paxa-TTS-Edge, an 82M-parameter fixed-voice Thai TTS student. The model achieves 68.2% Challenge-Set Keyword Accuracy (85.5% of Gemini 3.1), 91.4% pause precision, and CERs of 3.7% on Thai and 1.1% on English. It outperforms its teacher on pause placement and is open-sourced with its evaluation framework.

Hugging Face daily papers · 13d agoAI research

The Evolution of the Agent Harness

Latent Space essay argues late-2025 agent gains came from models and harnesses maturing together, with harness logic absorbed into model weights.

The piece defines the agent harness as everything beyond model weights—tools, context, memory, guardrails—and charts its evolution from ReAct prompting (October 2022) through AutoGPT's premature autonomy, Cursor/Copilot's human-in-the-loop retreat, and Devin's roughly 15% success rate, to o1's capability overhang and Claude Code's February 2025 terminal agent with permission rules. It argues the Christmas 2025 jump cited by Transformer co-inventor Lukasz Kaiser reflected model and harness curves crossing, and that remaining harnesses will serve human attention rather than the model.

Latent Space · 24d agoAI tools & infra

OpenAI Launches the Agents API in Public Beta, Putting the Codex Harness Behind One API Call

OpenAI released its Agents API in public beta, exposing the managed Codex harness with hosted or self-hosted sandboxes, MCP tools, and subagents.

The Agents API is a managed service built on the open-source Codex harness, handling context compaction, tool search, programmatic tool calling, and multi-agent orchestration. Agents run in OpenAI-hosted sandboxes, self-hosted environments, or partner sandboxes from Blaxel, Cloudflare, Daytona, DigitalOcean, E2B, Modal, Oracle, Runloop, and Vercel. Data residency is US-only and Zero Data Retention is unsupported. Examples use model gpt-6-astra; vendor-reported results include SafetyKit cutting case review cost 60% and Ciridae achieving 4x lower subagent latency.

MarkTechPostupdated · 4d agofirst · 5d agoAI tools & infra 4 sources1

Deep Learning-Based Detection of Electrical Faults and Power Quality Disturbances in Aerospace Power Systems

Compact ResNet detects electrical faults in 400 Hz aircraft power systems with 95.87 percent accuracy after deployment on Xilinx Zynq MPSoC.

The study targets multiclass fault and power quality disturbance detection in 400 Hz aerospace networks using a high-fidelity simulation model inspired by the Boeing 787 electrical architecture, covering 21 normal, disturbance, switching, open-circuit, and short-circuit conditions. Two 73,500-sample datasets are built from 1D waveforms and STFT time-frequency representations, augmented with domain randomization and class-specific GANs, and the time-series dataset is released via IEEE DataPort. A compact ResNet with 175,685 parameters achieved 96.94 percent software test accuracy, and 95.87 percent after 8-bit quantization on a Xilinx Zynq UltraScale Plus ZCU102 with 6.90 ms mean accelerator latency per record.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research

[AINews] GPT-6 Astra: OpenAI’s biggest LLM launch of all time

OpenAI launched GPT-6 Astra, its new flagship model, claiming state-of-the-art computer use, software engineering, math, and cybersecurity capabilities.

OpenAI launched GPT-6 Astra as its new flagship model, describing it as its most intelligent and aligned model with state-of-the-art computer use, software engineering, and math/science capabilities. Pricing is $10/$50 per 1M input/output tokens standard ($20/$100 fast tier), rolling out first to limited organizations, then ChatGPT Plus/Pro/Business/Enterprise, the API, and AWS. OpenAI claims 99.9% on ARC-AGI-3, 98% on FrontierMath Tier 4, and 100% on ExploitBench. Artificial Analysis scored Astra 67 on the Coding Agent Index and 61 on the Intelligence Index, behind Claude Fable 5.1, and the system card drew attention for reporting decreased chain-of-thought monitorability despite alignment gains.

Latent Space · 11d agoModel release2

Sparks Fly: NVIDIA Accelerates Local AI at IFA 2026

NVIDIA announces local AI push at IFA 2026 with faster llama.cpp/vLLM inference, PAIR routing tool, and October RTX Spark PCs.

At IFA 2026, NVIDIA announced simplified local AI support for agents in Hermes Agent, OpenClaw, and Perplexity Portable Computer, plus new llama.cpp and vLLM optimizations delivering up to 1.9x faster local inference. NVIDIA also unveiled PAIR, a Personal AI Router for distributing inference across a local network's PCs, and compact RTX Spark Windows PCs from Lenovo and Acer arriving in October. The post recaps recent local-capable model releases including Nemotron 3.5 Lightning (30B), Qwen3.8-Flash-Next and Qwen3.8-27B, DeepSeek v4 Flash (284B MoE, 13B active), Meta Muse Glimmer (30B), Z.ai GLM-5.3-Flash, LTX 2.5, and MiniMax-H3 with the FastH3 distilled variant.

NVIDIA Blog · 12d agoAI industry

XHToken/Spark-X2.5-4B-GGUF — new model trending #30 on Hugging Face

XHToken released GGUF weights of Spark-X2.5-4B, a compact model with 1M-token context and 200+ language support, under Apache 2.0.

The Hugging Face repository provides BF16 GGUF conversions of Spark-X2.5-4B, a compact general-purpose language model for conversation, writing, translation, reasoning, coding, tool use, and agentic workflows. The model uses a hybrid attention architecture, supports a native context length up to 1M tokens, and covers more than 200 languages. Local inference is supported through Ollama and LM Studio via an XHToken llama.cpp fork, with a --think=false flag to disable thinking mode for faster responses. Released under Apache License 2.0; it was trending #30 on Hugging Face at publication.

Hugging Face trending models · 18d agoModel release

IoT Under Siege: The Anatomy of the Latest Mirai Campaign Leveraging Multiple IoT Exploits

Unit 42 tracks a Mirai botnet campaign exploiting over 20 IoT vulnerabilities in routers, cameras and DVRs to build DDoS botnets since March 2023.

Since March 2023, Unit 42 has tracked threat actors exploiting more than 20 IoT vulnerabilities to spread a Mirai botnet variant, first seen downloading payloads from zvub.us on March 14, 2023. Exploited flaws span CVE-2023-1389 (TP-Link Archer), CVE-2022-30525 (Zyxel), CVE-2022-31499 (Nortek) and many router, camera and DVR bugs. The variant decrypts configuration strings with an XOR key derived from 0xDEADBEEF and lacks built-in credential brute forcing, so spreading relies on manual operator exploitation. Two campaigns observed since October 2022 share infrastructure and near-identical samples.

Palo Alto Unit 42 · 29d agoMalware in the wildCVE-2019-12725CVE-2019-17621CVE-2019-20500+13 CVEs

Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction

Grouped Value Attention stores grouped values and reconstructs content keys via a learned linear map, cutting KV-cache size about 45-47% versus GQA.

GVA stores only grouped values and reconstructs content keys with a learned linear map absorbed into the query at decode time, while a small shared decoupled RoPE channel preserves positional information via a separately cached positional key. At 350M parameters trained on 30B FineWeb-Edu tokens, the 16-dimensional positional variant scores 44.18 average accuracy across five tasks versus 44.36 for GQA and 43.88 for MLA. Custom decoding kernels are in development with an open-source release planned.

Hugging Face daily papers · 8d agoAI research

OpenClaw Power, MacBook Simplicity: Five Days With Grok Bot

Hands-on review finds Grok Bot simplifies agent setup via browser logins and bot abstraction, contrasting with the user-owned OpenClaw platform.

After five days with Grok Bot, the reviewer highlights browser-based sign-in as the key differentiator: connecting X, Freshdesk, and Google Calendar required only logins, no MCP configs or API keys. The piece contrasts Grok Bot's managed 'agent computer' with OpenClaw 2.0's user-owned Gateway, which now supports reusing Claude Code or Codex logins and ships a native Codex runtime. Grok Bot introduces 'Bots' as composable units arranged in 'group chats', exemplified by an Agentic Engineer Bot routing tasks across Claude Code, Codex, and Grok Build CLI. The reviewer used Grok Bot with a Cursor Pro+ account.

Latent Space · 10d agoAI industry1

[AINews] Hot Chips: OpenAI’s Jalapeño, Cerebras CS-5, Groq 3 LPX, Apple M6

OpenAI unveiled Jalapeno custom inference chip claiming 1.5-1.9x better perf-per-watt than NVIDIA GB200/GB300, deploying in-house by year-end.

At the 37th Hot Chips conference, OpenAI published first benchmark details for its custom Jalapeno inference chip, claiming 1.5-1.9x more work per watt, 1.7-3.6x lower end-to-end latency, and 2.1-4.1x higher interactive-workload performance versus NVIDIA GB200/GB300, with the 700W-rated part staying at or below 550W in tests. Deployment into OpenAI's own infrastructure begins by year-end, with Gen 2 deep in development and Gen 3 underway. OpenAI also said GPT-Astra and Codex helped write low-level kernels, reportedly 1.5-1.8x faster than human-expert code for selected attention and MoE blocks. Cerebras CS-5, Groq 3 LPX and Apple M6 were also featured at the conference.

Latent Space · 19d agoAI industry