# harness Published articles for harness. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Harness Named a Leader in SecureIQLab's August 2026 Cloud WAAP v5.0 Validation Report DevFeed: [Harness Named a Leader in SecureIQLab's August 2026 Cloud WAAP v5.0 Validation Report]() Original publisher: [Read original article]() Author: Christine Ferrusi Ross Published: 2026-09-11T00:00:00Z Content type: news Language: en Sources: [Harness Blog]() Topics: [Security](), [Cloud](), [API](), [Web](), [Testing]() Tags: [2026](), [ai-security](), [api](), [cloud](), [harness](), [protection](), [report](), [security](), [testing](), [v5](), [validation](), [web]() ### AI overview Harness Web Application & API Protection was named a Leader in SecureIQLab's August 2026 Cloud WAAP v5.0 CyberRisk Validation Comparative Report. The article highlights reported scores for API protection, advanced-threat coverage, deployment and management, false-positive avoidance, and GenAI and LLM operational efficiency. ### Source excerpt In the August 2026 SecureIQLab Cloud WAAP v5.0 CyberRisk Validation Comparative Report, Harness Web Application & API Protection (WAAP) was named a Leader. | Blog ## What to expect at the Zephyr Project Meetup (September 15, 2026) - Amsterdam, Netherlands DevFeed: [What to expect at the Zephyr Project Meetup (September 15, 2026) - Amsterdam, Netherlands]() Original publisher: [Read original article]() Author: Susan Remmert Published: 2026-09-09T05:00:04Z Content type: article Language: en Sources: [Zephyr Project]() Topics: [Zephyr RTOS](), [Embedded Systems](), [Open Source](), [Fuzzing/Fuzz testing](), [simulator](), [developer tooling]() Tags: [2026](), [blog](), [bugs](), [community](), [contributors](), [embedded](), [embedded-systems](), [event](), [events](), [firmware](), [fuzzing](), [harness](), [meetup](), [open-source](), [simulator](), [talk](), [technologies](), [tooling](), [tools](), [zephyr]() ### AI overview The Zephyr Project Meetup in Amsterdam on September 15, 2026, will bring together embedded developers, contributors, students, and engineers to exchange practical knowledge about Zephyr RTOS. The agenda includes talks on JetBrains' work with Zephyr, fuzzing Zephyr applications with AFL and Renode, and making hardware development easier with Schematik. ### Source excerpt What are developers in the Netherlands building with Zephyr? On September 15, the embedded community will meet in Amsterdam to exchange practical knowledge, discuss current work, and learn more about the Zephyr RTOS. The event is open to experienced contributors, first-time users, students, engineers, and anyone curious about open source embedded development. ## What to expect at the Zephyr Project Meetup (September 15, 2026) - Amsterdam, Netherlands DevFeed: [What to expect at the Zephyr Project Meetup (September 15, 2026) - Amsterdam, Netherlands]() Original publisher: [Read original article]() Author: Susan Remmert Published: 2026-09-09T05:00:04Z Content type: news Language: en Sources: [Zephyr Project]() Topics: [Zephyr RTOS](), [Embedded Systems](), [Fuzzing/Fuzz testing](), [Open Source]() Tags: [2026](), [blog](), [c](), [c-plus-plus](), [crashes](), [developer-tooling](), [embedded](), [embedded-systems](), [event](), [events](), [firmware](), [fuzzing](), [harness](), [jetbrains](), [meetup](), [memory-corruption](), [open-source](), [simulator](), [zephyr]() ### AI overview The Zephyr Project Meetup in Amsterdam on September 15, 2026, will bring together embedded developers, contributors, students, and engineers to share practical knowledge about Zephyr RTOS. The agenda includes talks on JetBrains' work with Zephyr, fuzzing Zephyr with AFL and Renode, and making hardware development easier with Schematik. ### Source excerpt What are developers in the Netherlands building with Zephyr? On September 15, the embedded community will meet in Amsterdam to exchange practical knowledge, discuss current work, and learn more about the Zephyr RTOS. The event is open to experienced contributors, first-time users, students, engineers, and anyone curious about open source embedded development. ## Making Operational Readiness Testing Continuous with Harness DevFeed: [Making Operational Readiness Testing Continuous with Harness]() Original publisher: [Read original article]() Author: Uma Mukkara Published: 2026-09-08T17:57:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [Testing](), [Resilience](), [sdlc](), [Deployment](), [configuration]() Tags: [configuration](), [deployment](), [harness](), [resilience](), [sdlc](), [testing]() ### AI overview The article argues that Operational Readiness Testing should be continuous rather than a one-time pre-release checklist. It describes how Harness Resilience Testing can apply ongoing checks to services as dependencies, configuration, deployments, and operating conditions change. ### Source excerpt Harness makes Operational Readiness Testing continuous, applying resilience checks to every SDLC change. | Blog ## How engineering teams can measure AI coding ROI with cost attribution and outcome metrics DevFeed: [How engineering teams can measure AI coding ROI with cost attribution and outcome metrics]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-09-08T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [ai-coding](), [Ground truth / benchmark quality](), [coding](), [Finance]() Tags: [ai](), [ai-coding](), [analysis](), [blog](), [coding](), [cost](), [datadog](), [engineering](), [governance](), [harness](), [incident](), [lifecycle](), [measurement](), [metrics](), [numbers](), [production](), [team](), [tokens](), [tooling](), [workflow]() ### AI overview A Harness panel discussion outlines ways engineering organizations can measure AI coding ROI. The panel recommends attributing costs to specific work, combining throughput metrics with qualitative evidence, and using governance and process changes to interpret results. ### Source excerpt Harness panelists share practical strategies for measuring AI coding ROI, from granular cost attribution and lifecycle metrics to budgeting, governance. | Blog ## An RTOS for Ages Two and Up -- Zephyr Podcast #049 DevFeed: [An RTOS for Ages Two and Up -- Zephyr Podcast #049]() Original publisher: [Read original article]() Author: Benjamin Cabé Published: 2026-09-04T20:01:01Z Content type: article Language: en Sources: [Zephyr Project]() Topics: [Embedded Software Dev](), [Testing](), [Arduino](), [Hardware](), [Maintainers](), [GitHub](), [Robotics](), [Wi-Fi]() Tags: [arduino](), [blog](), [engineering](), [firmware](), [github](), [halow](), [hardware](), [harness](), [maintainers](), [open](), [podcast](), [robotics](), [test](), [zephyr]() ### AI overview Zephyr Podcast episode 049 covers open-firmware hardware that does not yet run Zephyr, hardware-in-the-loop testing with Twister's pytest harness, project growth and contributors, Arduino Core for Zephyr 1.0, maintainer news, new drivers and subsystems, Wi-Fi HaLow support, and Zephyr's robotics community. ### Source excerpt The Dato DUO and the Teenage Engineering catalogue: lovely open-firmware noise machines that do not run Zephyr ...yet! Using the pytest harness in Twister to coordinate a device under test... ## Private Preview: DigitalOcean Managed Agents Runtime Services DevFeed: [Private Preview: DigitalOcean Managed Agents Runtime Services]() Original publisher: [Read original article]() Author: Salman Paracha Published: 2026-08-25T19:01:05Z Content type: release Language: en Sources: [DigitalOcean]() Topics: [Digital Ocean](), [Agent Harness](), [Artificial Intelligence](), [Cloud](), [Claude Code](), [codex](), [Langgraph](), [Command-line interface]() Tags: [agents](), [ai-agents](), [apis](), [claude-code](), [cli](), [cloud](), [codex](), [coding-agents](), [digitalocean](), [gateway](), [harness](), [langgraph](), [preview](), [product-updates](), [services](), [workflows]() ### AI overview DigitalOcean announces Managed Agents Runtime Services (M.A.R.S.) in private preview, combining Harness Runtime and Action Gateway. The managed service provides cloud infrastructure for persistent, scalable agent sessions and governed access to tools, APIs, and SaaS systems. ### Source excerpt AI agents are helping developers, teams, and businesses do more: writing and executing code, conducting research, and running dynamic workflows across systems. But that ability is often bounded by where they run. Close the laptop, and the work stops there. You can't pick it up on another device, hand off to a teammate, or scale it across users. Moving agents to cloud VMs solves part of this problem; developers and companies building agent harness frameworks still have to build a high-fidelity experience that can match a local session, including agent friendly execution environments, session persistence, secure tool access, human-in-the-loop approvals, and observability. Now available in Private Preview, DigitalOcean Managed Agents Runtime Services (M.A.R.S.) provides that infrastructure as a fully managed service. It gives developers, teams, and ISVs a powerful yet lightweight environment for operating coding agents and long-running, multi-tool agentic workflows without building and managing the underlying infrastructure themselves. M.A.R.S. brings together two products: Harness Runtime provides the managed execution environment in which agents run, persist, and scale. Action Gateway gives those same agents governed access to the tools, APIs, and SaaS systems they need to complete real-world work. Rather than requiring you to rebuild your agent around a proprietary framework, M.A.R.S. lets you define an environment template that packages your preferred harness, dependencies, tools, and configuration. Designed to work with Claude Code, Codex CLI, and OpenCode, as well as agents built with LangGraph or CrewAI, giving teams the freedom to choose the agent experience that best fits their needs without being locked into a single harness or framework. Agent sessions that outlive your laptop Harness Runtime helps agent sessions run independently of any local machine. They can start in under a second and resume from a pause in as little as 200 milliseconds while preserving ## Context Engineering for Coding Agents DevFeed: [Context Engineering for Coding Agents]() Original publisher: [Read original article]() Author: Paul Iusztin Published: 2026-08-25T05:01:37Z Content type: tutorial Language: en Sources: [Decoding ML]() Topics: [context window](), [AI-assisted coding](), [coding](), [Claude](), [codex]() Tags: [agents](), [claude](), [codex](), [coding-agents](), [context](), [context-engineering](), [context-window](), [harness]() ### AI overview This tutorial explains context engineering for coding agents, focusing on memory, skills, LSP servers, compaction, and feedback loops. It presents these techniques as ways to keep an agent's context high-signal and improve coding-agent performance. ### Source excerpt The 4 harness components that keep your context window high-signal. ## Automated Incident Response: Nobody Should Be the Scribe DevFeed: [Automated Incident Response: Nobody Should Be the Scribe]() Original publisher: [Read original article]() Author: Ryan Taylor Published: 2026-08-25T00:00:00Z Content type: opinion Language: en Sources: [Harness Blog]() Topics: [incident](), [Incident response](), [Artificial Intelligence](), [Slack](), [Python](), [Shell]() Tags: [agent](), [ai](), [automated-incident-response](), [blog](), [harness](), [incident](), [incident-response](), [jira](), [product](), [python](), [shell-script](), [slack](), [teams]() ### AI overview A Harness product lead argues that incident teams should not rely on a human scribe. The article describes automated runbooks that create communication channels, video bridges, and tickets, while an AI Scribe Agent captures incident events and produces timelines, postmortems, and synchronized action items. ### Source excerpt A Harness product lead on why humans shouldn't be the status-tracking layer during incidents, and how automated summaries and postmortems replace the scribe. | Blog ## Agent Night demo recap: How Mastra turned its issue backlog into a software factory DevFeed: [Agent Night demo recap: How Mastra turned its issue backlog into a software factory]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-08-17T19:04:08Z Content type: news Language: en Sources: [WorkOS Blog]() Topics: [Development](), [Open Source](), [coding](), [Software](), [Command-line interface]() Tags: [agent](), [agentic](), [agentic-development](), [agents](), [coding](), [demo](), [development](), [harness](), [mastra](), [memory](), [open-source](), [open-source-software](), [recap](), [software](), [terminal]() ### AI overview The article recaps Abhi Aiyer's Agent Night demonstration of Mastra's open source software factory. It describes observational memory, Mastra Code, and the AgentController, which supports building interactive agent applications with modes, models, storage, workspaces, approvals, subagents, and channels. ### Source excerpt Abhi Aiyer, co-founder and CTO of Mastra, demoed the company's open source software factory at Agent Night: memory, harness, a rules engine around work. ## Agent Night panel recap: AI spending, open-source models, and the changing agent economy DevFeed: [Agent Night panel recap: AI spending, open-source models, and the changing agent economy]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-08-17T18:34:23Z Content type: article Language: en Sources: [WorkOS Blog]() Topics: [Artificial Intelligence](), [Open Source](), [deepseek](), [OpenAI]() Tags: [ai](), [anthropic](), [deepseek](), [engineering](), [harness](), [open-source](), [openai](), [recap]() ### AI overview A recap of WorkOS's Agent Night panel, where Jaya Gupta, Flo Crivello, and swyx discussed increased spending on AI tooling, progress in open-source models, and changing economics for AI agents. The article presents panelists' claims and observations, including Flo Crivello's view that AGI has arrived and reports of companies moving from OpenAI and Anthropic to open-source models. ### Source excerpt Jaya Gupta, Flo Crivello, and swyx on stage at Agent Night: 5x AI spend, open source getting real, harness engineering, skills, and December predictions. ## Harness Community: Connect, Learn, and Build Together DevFeed: [Harness Community: Connect, Learn, and Build Together]() Original publisher: [Read original article]() Author: Dewan Ahmed Ankit Kumar Published: 2026-08-12T00:00:00Z Content type: release Language: en Sources: [Harness Blog]() Topics: [Software](), [CI/CD]() Tags: [blog](), [community](), [harness](), [software-delivery]() ### AI overview Harness announces the launch of the Harness Community, an open discussion forum where users can connect with practitioners, share expertise, solve delivery challenges, and help shape the platform's future. ### Source excerpt Join the Harness Community to connect with practitioners, solve delivery challenges, share expertise, and shape the future of software delivery. | Blog ## Why Amp Became Sebastian's Default Coding Harness DevFeed: [Why Amp Became Sebastian's Default Coding Harness]() Original publisher: [Read original article]() Author: Freek Van der Herten (freek@spatie.be) Published: 2026-08-11T10:30:28Z Content type: opinion Language: en Sources: [freek.dev - all blogposts]() Topics: [coding](), [User Experience]() Tags: [agents](), [ai](), [coding](), [developer-experience](), [experience](), [harness](), [mcp](), [tools](), [user-experience](), [verification]() ### AI overview Sebastian explains why Amp became his default coding harness, emphasizing user experience over model churn and describing AGENTS.md changes that reduced overzealous verification during everyday coding. ### Source excerpt Sebastian explains why Amp became his default coding harness, and why user experience now matters more to him than model churn. He also shares the AGENTS.md tweaks that reduced overzealous verification during day-to-day coding. Read more ## Linear's Case for Building a Custom Agent Harness Instead of Using Agent Frameworks DevFeed: [Linear's Case for Building a Custom Agent Harness Instead of Using Agent Frameworks]() Original publisher: [Read original article]() Author: Byte-Sized Design Published: 2026-08-10T17:59:45Z Content type: opinion Language: en Sources: [Byte-Sized Design]() Topics: [Frameworks]() Tags: [agent](), [frameworks](), [harness](), [tools]() ### AI overview The article presents a case for building a custom agent harness instead of using agent frameworks, focusing on shallow tools and just-in-time skills. ### Source excerpt Shallow tools, just-in-time skills, and a defensible case for a custom harness ## Terraform Scalability: When IaC Outgrows Your Setup DevFeed: [Terraform Scalability: When IaC Outgrows Your Setup]() Original publisher: [Read original article]() Author: Mrinalini Sugosh Published: 2026-08-10T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [Terraform](), [Infrastructure as code](), [Scalability](), [iac-security]() Tags: [dynamodb](), [harness](), [iac](), [s3](), [scalability](), [security](), [terraform]() ### AI overview This article examines how Terraform scalability challenges emerge as infrastructure code and teams grow. It discusses bottlenecks involving state management, collaboration, governance, large state files, locking, plan times, module sprawl, and version drift, and introduces Harness IaCM as a management solution. ### Source excerpt Terraform scalability issues slow teams down. Learn how to overcome IaC bottlenecks with better management. See how Harness helps. | Blog ## Automate Incident Intake with AI SRE Runbooks DevFeed: [Automate Incident Intake with AI SRE Runbooks]() Original publisher: [Read original article]() Author: Ryan Taylor Published: 2026-08-10T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [SRE](), [incident](), [Automation](), [Slack](), [zoom](), [Grafana](), [datadog](), [Artificial Intelligence]() Tags: [ai](), [automation](), [build](), [datadog](), [grafana](), [harness](), [incident](), [integrations](), [jira](), [open](), [services](), [slack](), [sre](), [workflow](), [zoom]() ### AI overview This article explains how Harness AI SRE runbooks automate incident intake and early response. Triggered by alerts, manual actions, or incident changes, a runbook can create tickets, open Slack channels, start Zoom bridges, set incident fields, and record actions in the incident timeline. ### Source excerpt Automate incident intake with Harness AI SRE runbooks: auto-create tickets, open Slack channels, start Zoom bridges, and cut response time to seconds. | Blog ## Refactoring a SQL Table at Scale: Lessons from Harness CI DevFeed: [Refactoring a SQL Table at Scale: Lessons from Harness CI]() Original publisher: [Read original article]() Author: Moshe Tsur Published: 2026-08-06T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [Refactoring](), [Structured-data](), [Databases](), [SQL](), [Latency](), [API](), [ci]() Tags: [api](), [continuous-integration](), [harness](), [latency](), [refactoring](), [schema](), [sql]() ### AI overview Harness describes refactoring a flat SQL table used for CI test results into a normalized schema. The article reports reducing storage per row from 400 bytes to 28 bytes and making API latency constant at any scale. ### Source excerpt How Harness refactored a flat SQL table into a normalized schema, cutting storage per row from 400 bytes to 28 bytes and making API latency constant at any scal | Blog ## How OpenAI Optimized AI Agents for Codex and ChatGPT Work at Scale DevFeed: [How OpenAI Optimized AI Agents for Codex and ChatGPT Work at Scale]() Original publisher: [Read original article]() Author: Gregor Ojstersek Published: 2026-07-29T19:52:55Z Content type: article Language: en Sources: [Engineering Leadership]() Topics: [OpenAI](), [Artificial Intelligence](), [codex](), [ChatGPT](), [API](), [Inference]() Tags: [agents](), [ai](), [ai-agents](), [api](), [chatgpt](), [codex](), [harness](), [inference](), [inference-efficiency](), [openai]() ### AI overview The article examines how OpenAI optimized the harness, API, and inference efficiency of AI agents supporting Codex and ChatGPT Work at scale. ### Source excerpt Inside the Harness, API, and Inference efficiency optimizations that support the fast growth of Codex and ChatGPT Work. ## How TRM Built a Custom Internal Harness for Product and Engineering Work DevFeed: [How TRM Built a Custom Internal Harness for Product and Engineering Work]() Original publisher: [Read original article]() Author: Luca Rossi Published: 2026-07-29T07:31:16Z Content type: article Language: en Sources: [Refactoring]() Topics: [Development](), [Artificial Intelligence]() Tags: [case-study](), [development](), [engineering](), [harness](), [product-development]() ### AI overview This case study describes how TRM built a custom internal harness for product and engineering work. ### Source excerpt How TRM built a custom internal harness for product and engineering work. ## FinOps: Shift from Reactive Cost Cutting to Proactive Cloud Savings DevFeed: [FinOps: Shift from Reactive Cost Cutting to Proactive Cloud Savings]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-07-24T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [finops](), [Optimization](), [Cloud]() Tags: [cloud](), [cost-optimization](), [finops](), [harness](), [optimization]() ### AI overview The article argues that FinOps teams should shift from reacting to cloud-cost overruns toward proactively preventing unnecessary costs before workloads reach production. It explains that rightsizing, commitment discounts, and resource lifecycle management remain useful but are insufficient alone at scale. ### Source excerpt Shift your FinOps savings optimization strategy from reactive cuts to proactive savings. Learn how Harness helps. Explore now. | Blog ## Software Factories, Light and Dark DevFeed: [Software Factories, Light and Dark]() Original publisher: [Read original article]() Author: Addy Osmani Published: 2026-07-22T03:44:07Z Content type: opinion Language: en Sources: [Elevate]() Topics: [Loop Engineering](), [Software](), [Artificial Intelligence]() Tags: [agentic](), [agents](), [harness](), [loops](), [software]() ### AI overview The article revisits the idea of software factories through loops, harnesses, and factories. It distinguishes light factories, where humans remain involved, from dark factories, where agents scope, build, and ship code with limited human review. It argues that autonomy requires carefully designed checks, boundaries, tools, memory, and completion gates. ### Source excerpt A software factory is harnessing loops at scale. ## Native AI Agent Deployment in Harness Continuous Delivery DevFeed: [Native AI Agent Deployment in Harness Continuous Delivery]() Original publisher: [Read original article]() Author: Akshit Madan Published: 2026-07-21T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [AI Agent](), [Deployment](), [Continuous Delivery (CD)](), [Security](), [Software](), [agent observability]() Tags: [agentic](), [ai](), [ai-agent](), [audit-trail](), [continuous-delivery](), [deployment](), [harness](), [progressive-delivery](), [security]() ### AI overview This Harness article introduces agent deployment in Harness Continuous Delivery, with governed pipelines, native runtime support for platforms including Google's Agent Runtime and Amazon Bedrock AgentCore, progressive delivery, policy controls, and audit trails. It explains deployment as a critical stage of the agent development lifecycle and describes coordinating agents with backend services, database changes, and prompt or model configuration. ### Source excerpt Deploy AI agents with Harness Continuous Delivery using governed pipelines, native runtime support, progressive delivery, and built-in security. | Blog ## AI Coding Tip 027 - Force Code Standards DevFeed: [AI Coding Tip 027 - Force Code Standards]() Original publisher: [Read original article]() Author: Maxi Contieri Published: 2026-07-10T14:24:14Z Content type: tutorial Language: en Sources: [Maximiliano Contieri - Software Design]() Topics: [ai-coding](), [coding](), [pull-requests](), [Language models]() Tags: [agents](), [ai-coding](), [analysis](), [code](), [coding](), [harness](), [hooks](), [how-to](), [large-language-model](), [linter](), [pull-request](), [reviews](), [skills](), [trust](), [windows]() ### AI overview A tutorial on enforcing coding standards in AI-assisted development. It recommends converting prose standards into machine-checkable rules, running them through hooks and validator skills, and using an LLM judge for ambiguous semantic violations before code reaches human review. ### Source excerpt TL;DR: Wire your standards into hooks, skills, and a judge, so the harness blocks violations before a human opens the diff. Common Mistake ❌ You paste your coding standards into AGENTS.md and trust t ## Harness Bench: как оценить агентский harness и выбрать связку с моделью DevFeed: [Harness Bench: как оценить агентский harness и выбрать связку с моделью]() Original publisher: [Read original article]() Author: andrivasg (red\_mad\_robot) Published: 2026-06-30T11:30:03Z Content type: article Language: ru Sources: [Redmadrobot EN](), [Redmadrobot RU]() Topics: [Artificial Intelligence]() Tags: [agent-harness](), [ai](), [ai-e2239b5ae8fa](), [ai-evaluation](), [benchmark](), [harness](), [llm](), [mcp]() ### AI overview The article introduces Harness Bench, an open framework for evaluating model-and-harness combinations on real tasks under consistent conditions. It explains why an agent harness affects an AI system's practical capabilities, discusses problems in open-source harnesses that disrupt automated evaluation, and describes how existing benchmarks can be used for reproducible testing. ### Source excerpt Привет! Я Андрей Иванов, NLP-исследователь в R&D-лаборатории red_mad_robot. Когда мы собираем AI-агента, первым делом выбираем модель под задачу. Но в реальном приложении она не работает в одиночку, ей нужен агентский harness -- программная обвязка. Поэтому выбирать приходится не просто модель, а связку "модель + harness". Чтобы делать этот выбор осознанно, мы создали Harness Bench -- открытый фреймворк, который тестирует связки на реальных задачах в одинаковых условиях. В статье расскажу, как он устроен, разберу баги опенсорсных обвязок, которые ломают автоматический прогон, а потом покажу на цифрах, как смена harness влияет на способности одной и той же модели. Читать далее [Next page]()