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# Tavily Search Results: Geneva
**Query:** Claude Code latest updates
**Topic:** general
**Results:** 6
**Date:** 2026-02-14 19:05:02
---
## 1. Introducing Claude Opus 4.6 - Anthropic
**URL:** [https://www.anthropic.com/news/claude-opus-4-6](https://www.anthropic.com/news/claude-opus-4-6)
**Score:** 0.8128
### Summary
Product updates
Across Claude and Claude Code, we’ve added features that allow knowledge workers and developers to tackle harder tasks with more of the tools they use every day.
We’ve introduced agent teams in Claude Code as a research preview. You can now spin up multiple agents that work in parallel as a team and coordinate autonomously—best for tasks that split into independent, read-heavy work like codebase reviews. You can take over any subagent directly using Shift+Up/Down or tmux. [...] We’re also accelerating the cyber _defensive_ uses of the model, using it to help find and patch vulnerabilities in open-source software (as we describe in our new cybersecurity blog post). We think it’s critical that cyberdefenders use AI models like Claude to help level the playing field. Cybersecurity moves fast, and we’ll be adjusting and updating our safeguards as we learn more about potential threats; in the near future, we may institute real-time intervention to block abuse.
Product and API updates
We’ve made substantial updates across Claude, Claude Code, and the Claude Developer Platform to let Opus 4.6 perform at its best.
Claude Developer Platform [...] Opus 4.6 gets the highest score in the industry for deep, multi-step agentic search.
Image 4: Bar charts comparing Opus 4.6 to other models on Terminal-Bench 2
Opus 4.6 excels at real-world agentic coding and system tasks.
Image 5
Opus 4.6 extends the frontier of expert-level reasoning.
In Claude Code, you can now assemble _agent teams_ to work on tasks together. On the API, Claude can use _compaction_ to summarize its own context and perform longer-running tasks without bumping up against limits. We’re also introducing _adaptive thinking_, where the model can pick up on contextual clues about how much to use its extended thinking, and new _effort_ controls to give developers more control over intelligence, speed, and cost.
### Full Content
[Skip to main content](https://www.anthropic.com/news/claude-opus-4-6#main-content)[Skip to footer](https://www.anthropic.com/news/claude-opus-4-6#footer)
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Announcements
Introducing Claude Opus 4.6
===========================
Feb 5, 2026
We’re upgrading our smartest model.
The new Claude Opus 4.6 improves on its predecessor’s coding skills. It plans more carefully, sustains agentic tasks for longer, can operate more reliably in larger codebases, and has better code review and debugging skills to catch its own mistakes. And, in a first for our Opus-class models, Opus 4.6 features a 1M token context window in beta 1.
Opus 4.6 can also apply its improved abilities to a range of everyday work tasks: running financial analyses, doing research, and using and creating documents, spreadsheets, and presentations. Within [Cowork](https://claude.com/blog/cowork-research-preview), where Claude can multitask autonomously, Opus 4.6 can put all these skills to work on your behalf.
The model’s performance is state-of-the-art on several evaluations. For example, it achieves the highest score on the agentic coding evaluation [Terminal-Bench 2.0](https://www.tbench.ai/news/announcement-2-0) and leads all other frontier models on [Humanity’s Last Exam](https://agi.safe.ai/), a complex multidisciplinary reasoning test. On [GDPval-AA](https://artificialanalysis.ai/evaluations/gdpval-aa)—an evaluation of performance on economically valuable knowledge work tasks in finance, legal, and other domains 2—Opus 4.6 outperforms the industry’s next-best model (OpenAI’s GPT-5.2) by around 144 Elo points,3 and its own predecessor (Claude Opus 4.5) by 190 points. Opus 4.6 also performs better than any other model on [BrowseComp](https://openai.com/index/browsecomp/), which measures a model’s ability to locate hard-to-find information online.
As we show in our extensive [system card](https://www.anthropic.com/claude-opus-4-6-system-card), Opus 4.6 also shows an overall safety profile as good as, or better than, any other frontier model in the industry, with low rates of misaligned behavior across safety evaluations.
Knowledge work Agentic search Coding Reasoning
Opus 4.6 is state-of-the-art on real-world work tasks across several professional domains.
Opus 4.6 gets the highest score in the industry for deep, multi-step agentic search.
Opus 4.6 excels at real-world agentic coding and system tasks.
Opus 4.6 extends the frontier of expert-level reasoning.
In Claude Code, you can now assemble [_agent teams_](https://code.claude.com/docs/en/agent-teams) to work on tasks together. On the API, Claude can use [_compaction_](https://platform.claude.com/docs/en/build-with-claude/compaction) to summarize its own context and perform longer-running tasks without bumping up against limits. We’re also introducing [_adaptive thinking_](https://platform.claude.com/docs/en/build-with-claude/adaptive-thinking), where the model can pick up on contextual clues about how much to use its extended thinking, and new [_effort_](https://platform.claude.com/docs/en/build-with-claude/effort) controls to give developers more control over intelligence, speed, and cost.
We’ve made substantial upgrades to [Claude in Excel](https://claude.com/claude-in-excel), and we’re releasing [Claude in PowerPoint](https://claude.com/claude-in-powerpoint) in a research preview. This makes Claude much more capable for everyday work.
**Score:** 0.8092
### Summary
At least until last night. The Claude Code team released an update that fundamentally alters this equation. Dubbed MCP Tool Search, the feature introduces "lazy loading" for AI tools, allowing agents to dynamically fetch tool definitions only when necessary.
It is a shift that moves AI agents from a brute-force architecture to something resembling modern software engineering—and according to early data, it effectively solves the "bloat" problem that was threatening to stifle the ecosystem.
The 'Startup Tax' on Agents [...] Claude Code just got updated with one of the most-requested user features | VentureBeat
Anthropic's open source standard, the Model Context Protocol (MCP), released in late 2024, allows users to connect AI models and the agents atop them to external tools in a structured, reliable format. It is the engine behind Anthropic's hit AI agentic programming harness, Claude Code, allowing it to access numerous functions like web browsing and file creation immediately when asked.
But there was one problem: Claude Code typically had to "read" the instruction manual for every single tool available, regardless of whether it was needed for the immediate task, using up the available context that could otherwise be filled with more information from the user's prompts or the agent's responses. [...] It was loading tool definitions like 2020-era static imports instead of 2024-era lazy loading," he wrote. "VSCode doesn’t load every extension at startup. JetBrains doesn’t inject every plugin’s docs into memory."
By adopting "lazy loading"—a standard best practice in web and software development—Anthropic is acknowledging that AI agents are no longer just novelties; they are complex software platforms that require architectural discipline.
Implications for the Ecosystem
For the end user, this update is seamless: Claude Code simply feels "smarter" and retains more memory of the conversation. But for the developer ecosystem, it opens the floodgates.
### Full Content
Claude Code just got updated with one of the most-requested user features | VentureBeat
===============
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Claude Code just got updated with one of the most-requested user features
=========================================================================
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Anthropic's open source standard, the Model Context Protocol (MCP), [released in late 2024](https://venturebeat.com/data-infrastructure/anthropic-releases-model-context-protocol-to-standardize-ai-data-integration), allows users to connect AI models and the agents atop them to external tools in a structured, reliable format. It is the engine behind Anthropic's hit [AI agentic programming harness, Claude Code](https://venturebeat.com/technology/anthropic-cracks-down-on-unauthorized-claude-usage-by-third-party-harnesses), allowing it to access numerous functions like web browsing and file creation immediately when asked.
But there was one problem: Claude Code typically had to "read" the instruction manual for every single tool available, regardless of whether it was needed for the immediate task, using up the available context that could otherwise be filled with more information from the user's prompts or the agent's responses.
At least until last night. [The Claude Code team released an update](https://x.com/trq212/status/2011523109871108570) that fundamentally alters this equation. Dubbed MCP Tool Search, the feature introduces "lazy loading" for AI tools, allowing agents to dynamically fetch tool definitions only when necessary.
It is a shift that moves AI agents from a brute-force architecture to something resembling modern software engineering—and according to early data, it effectively solves the "bloat" problem that was threatening to stifle the ecosystem.
The 'Startup Tax' on Agents
---------------------------
To understand the significance of Tool Search, one must understand the friction of the previous system. The Model Context Protocol (MCP), released in 2024 by Anthropic as an open source standard was designed to be a universal standard for connecting AI models to data sources and tools—everything from GitHub repositories to local file systems.
However, as the ecosystem grew, so did the "startup tax."
Thariq Shihipar, a member of the technical staff at Anthropic, highlighted the scale of the problem in the [announcement.](https://x.com/trq212/status/2011523109871108570)
"We've found that MCP servers may have up to 50+ tools," Shihipar wrote. "Users were documenting setups with 7+ servers consuming 67k+ tokens."
In practical terms, this meant a developer using a robust set of tools might sacrifice 33% or more of their available context window limit of 200,000 tokens before they even typed a single character of a prompt, as [AI newsletter author Aakash Gupta pointed out in a post on X.](https://x.com/aakashgupta/status/2011664388424454262)
The model was effectively "reading" hundreds of pages of technical documentation for tools it might never use during that session.
Community analysis provided even starker examples.
Gupta further noted that a single Docker MCP server could consume 125,000 tokens just to define its 135 tools.
"The old constraint forced a brutal tradeoff," he wrote. "Either limit your MCP servers to 2-3 core tools, or accept that half your context budget disappears before you start working."
How Tool Search Works
---------------------
The solution Anthropic rolled out — which Shihipar called "one of our most-requested features on [GitHub](https://github.com/anthropics/claude-code/issues/7336)" — is elegant in its restraint. Instead of preloading every definition, Claude Code now monitors context usage.
According to the release notes, the system automatically detects when tool descriptions would consume more than 10% of the available context.
When that threshold is crossed, the system switches strategies. Instead of dumping raw documentation into the prompt, it loads a lightweight search index.
When the user asks for a specific action—say, "deploy this container"—Claude Code doesn't scan a massive, pre-loaded list of 200 com
*[Content truncated...]*
---
## 3. Releases · anthropics/claude-code - GitHub
**URL:** [https://github.com/anthropics/claude-code/releases](https://github.com/anthropics/claude-code/releases)
**Score:** 0.8059
### Summary
Claude Opus 4.6 is now available!
Added research preview agent teams feature for multi-agent collaboration (token-intensive feature, requires setting CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1)
Claude now automatically records and recalls memories as it works
Added "Summarize from here" to the message selector, allowing partial conversation summarization.
Skills defined in `.claude/skills/` within additional directories (`--add-dir`) are now loaded automatically.
Fixed `@` file completion showing incorrect relative paths when running from a subdirectory
Updated --resume to re-use --agent value specified in previous conversation by default. [...] Added session resume hint on exit, showing how to continue your conversation later
Added support for full-width (zenkaku) space input from Japanese IME in checkbox selection
Fixed PDF too large errors permanently locking up sessions, requiring users to start a new conversation
Fixed bash commands incorrectly reporting failure with "Read-only file system" errors when sandbox mode was enabled
Fixed a crash that made sessions unusable after entering plan mode when project config in `~/.claude.json` was missing default fields
Fixed `temperatureOverride` being silently ignored in the streaming API path, causing all streaming requests to use the default temperature (1) regardless of the configured override [...] Fixed agent teammate sessions in tmux to send and receive messages
Fixed warnings about agent teams not being available on your current plan
Added `TeammateIdle` and `TaskCompleted` hook events for multi-agent workflows
Added support for restricting which sub-agents can be spawned via `Task(agent_type)` syntax in agent "tools" frontmatter
Added `memory` frontmatter field support for agents, enabling persistent memory with `user`, `project`, or `local` scope
Added plugin name to skill descriptions and `/skills` menu for better discoverability
Fixed an issue where submitting a new message while the model was in extended thinking would interrupt the thinking phase
### Full Content
Releases · anthropics/claude-code
===============
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---
## 4. Claude Developer Platform - Claude API Docs
**URL:** [https://platform.claude.com/docs/en/release-notes/overview](https://platform.claude.com/docs/en/release-notes/overview)
**Score:** 0.7900
### Summary
### September 10, 2025
We've launched the web fetch tool in beta, allowing Claude to retrieve full content from specified web pages and PDF documents. Learn more in our web fetch tool documentation.
We've launched the Claude Code Analytics API, enabling organizations to programmatically access daily aggregated usage metrics for Claude Code, including productivity metrics, tool usage statistics, and cost data.
### September 8, 2025
We launched a beta version of the C# SDK.
### September 5, 2025
We've launched rate limit charts in the Console Usage page, allowing you to monitor your API rate limit usage and caching rates over time.
### September 3, 2025
We've launched support for citable documents in client-side tool results. Learn more in our tool use documentation. [...] ### December 4th, 2024
We've added the ability to group by API key to the Usage and Cost pages of the Developer Console
We've added two new Last used at and Cost columns and the ability to sort by any column in the API keys page of the Developer Console
### November 21st, 2024
We've released the Admin API, allowing users to programmatically manage their organization's resources.
### November 20th, 2024
We've updated our rate limits for the Messages API. We've replaced the tokens per minute rate limit with new input and output tokens per minute rate limits. Read more in our documentation.
We've added support for tool use in the Workbench.
### November 13th, 2024
We've added PDF support for all Claude Sonnet 3.5 models. Read more in our documentation. [...] ### October 3rd, 2024
We've added the ability to disable parallel tool use in the API. Set `disable_parallel_tool_use: true` in the `tool_choice` field to ensure that Claude uses at most one tool. Read more in our documentation.
### September 10th, 2024
We've added Workspaces to the Developer Console. Workspaces allow you to set custom spend or rate limits, group API keys, track usage by project, and control access with user roles. Read more in our blog post.
### September 4th, 2024
We announced the deprecation of the Claude 1 models. Read more in our documentation.
### August 22nd, 2024
### Full Content
Claude Developer Platform - Claude API Docs
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Overview
Claude Developer Platform
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Updates to the Claude Developer Platform, including the Claude API, client SDKs, and the Claude Console.
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For release notes on Claude Apps, see the [Release notes for Claude Apps in the Claude Help Center](https://support.claude.com/en/articles/12138966-release-notes).
For updates to Claude Code, see the [complete CHANGELOG.md](https://github.com/anthropics/claude-code/blob/main/CHANGELOG.md) in the `claude-code` repository.
### February 7, 2026
* We've launched [fast mode](https://platform.claude.com/docs/en/build-with-claude/fast-mode) in research preview for Opus 4.6, providing significantly faster output token generation via the `speed` parameter. Fast mode is up to 2.5x as fast at premium pricing. Interested customers should join
*[Content truncated...]*
---
## 5. Claude Code is the Inflection Point - SemiAnalysis
**URL:** [https://newsletter.semianalysis.com/p/claude-code-is-the-inflection-point](https://newsletter.semianalysis.com/p/claude-code-is-the-inflection-point)
**Score:** 0.5583
### Summary
On January 12, 2026, Anthropic launched Cowork—”Claude Code for general computing.” Four engineers built it in 10 days. Most of the code was written by Claude Code itself. Same architecture: Claude Agent SDK, MCP, sub-agents. It creates spreadsheets from receipts, organizes files by content, and drafts reports from scattered notes. It’s Claude Code minus the terminal, plus a desktop.
Image 17
Image 18 [...] Claude Code is the Inflection Point
Image 1: SemiAnalysis
Image 2: SemiAnalysis
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Claude Code is the Inflection Point
### What It Is, How We Use It, Industry Repercussions, Microsoft's Dilemma, Why Anthropic Is Winning
Doug O'Laughlin, Jeremie Eliahou Ontiveros, Jordan Nanos, and 2 others
Feb 05, 2026
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4% of GitHub public commits are being authored by Claude Code right now. At the current trajectory, we believe that Claude Code will be 20%+ of all daily commits by the end of 2026. While you blinked, AI consumed all of software development. [...] The Price of Intelligence is Collapsing
Now software engineering has and always will be the gold standard information work. But as the quality has finally crossed over a critical threshold, the relationship between coders and their tools have flipped. Coders are effectively just harnessing a black box tool to achieve outcomes, and that was all possible because not only the quality but the cost of the intelligence of tokens has fallen an amazing amount. One developer with Claude Code can now do what took a team a month.
### Full Content
Claude Code is the Inflection Point
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Claude Code is the Inflection Point
===================================
### What It Is, How We Use It, Industry Repercussions, Microsoft's Dilemma, Why Anthropic Is Winning
[Doug O'Laughlin](https://substack.com/@mule), [Jeremie Eliahou Ontiveros](https://substack.com/@jeremieeliahouontiveros), [Jordan Nanos](https://substack.com/@jnanos), and 2 others
Feb 05, 2026
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4% of GitHub public commits are being authored by Claude Code right now. At the current trajectory, we believe that Claude Code will be 20%+ of all daily commits by the end of 2026. While you blinked, AI consumed all of software development.
Our sister publication Fabricated Knowledge described software like [linear TV during the rise of the internet](https://www.fabricatedknowledge.com/p/ai-is-creating-peak-software-media) and thinks that the rise of [Claude Code is going to be a new layer of intelligence on top of software akin to DRAM versus NAND](https://www.fabricatedknowledge.com/p/the-death-of-software-20-a-better). Today SemiAnalysis is going to dive into the repercussions of Claude Code, what it is, and why Claude is so good.
[](https://substackcdn.com/image/fetch/$s_!MG5m!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6ec41954-9498-4c2f-b23a-81e2bae29f82_2761x1579.png)
Source: [Tokenomics Team](http://semianalysis.com/tokenomics-model/), Github, Generated by Claude Code
We believe that Claude Code is the inflection point for AI “Agents” and is a glimpse into the future of how AI will function. It is set to drive exceptional revenue growth for Anthropic in 2026, enabling the lab to dramatically outgrow OpenAI.
We built a detailed economic model of Anthropic and precisely quantified revenue and capex implications for its cloud partners AWS, Google Cloud, Azure, as well as associated supply chains such as Trainium2/3, TPUs and GPUs. This is the [core purpose of the Tokenomics model](https://semianalysis.com/tokenomics-model/).
Anthropic is on track to add as much power as OpenAI in the next three years. Refer to our [Datacenter Industry Model](https://semianalysis.com/datacenter-industry-model/) for a building-by-building tracker of Anthropic and OpenAI. Sam’s AI lab is notably suffering from mutliple data center delays, which we’ve called out months ahead of the headlines, most notably in our Coreweave Q3’2025 earnings preview where we explicitly called out a large CapEx guidance miss.
[](https://substackcdn.com/image/fetch/$s_!P1XQ!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc04de5e0-5ec5-4c11-a6d3-c3dab116d665_927x585.png)
Source: SemiAnalysis [Datacenter Model](https://semianalysis.com/datacenter-industry-model/)
Since more compute means more revenue, we can forecast ARR growth and compare Anthropic to OpenAI directly.
[](https://substackcdn.com/image/fetch/$s_!7xxX!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F7572d353-1443-483a-a286-4cb33d1413f9_927x585.png)
source: SemiAnalysis [Tokenomics Model](https://semianalysis.com/tokenomics-model/)
Notably, our forecast shows that Anthropic’s quarterly ARR additions have overt
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## 6. Claude Code is being dumbed down? | Hacker News
**URL:** [https://news.ycombinator.com/item?id=46978710](https://news.ycombinator.com/item?id=46978710)
**Score:** 0.5271
### Summary
stand any chance of enforcing it. Real defense is rooted in technical measures, imperfect as they may be, but this is just defense through wishful thinking. reply Image 63) Obviously, don't put your SSH keys in a public webroot. But let's say you're managing a web server and have a decent security mindset. But don't you think it's better to regularly check the logs for evidence of an attack vs delete all the logs so they can't be checked? reply Image 64) I sent email to Anthropic (usersafety@anthropic.com, disclosure@anthropic.com) on January 8, 2025 alerting them to this issue: Claude Code Exploit: Claude Code Becomes an Unwitting Executor. If I hadn't seen Claude Code read my ssh file, I wouldn't have known the extent of the issue. reply Image 65) To improve the Claude model, it seems [...] it's good PR for Anthropic if Claude is credited in the AI statements of major scientific publications. As it stands, trajectory in develeopment means I cannot in good conscience recommend Claude Code for scientific domains. reply Image 101) >the session just burns through my token quota Did you ever think that this may be Anthropic's goal? It is a waste for sure but it increases their revenue. Later on the old feature you were used to may resurface at a different tier so you'd have to pay up to get it. reply Image 102) What academic domains are you on the cutting edge of? Genuinely curious what specifically is beyond claude's capabilites reply Image 103) Most recent problems were related to topology, but it can take the wrong direction on many things. This is not an LLM fault; it's a [...] have a screen reader user on the dev team? Is verbose mode the same as the old mode, where only file paths are spoken? Or does it have other text in it? Because I tried to articulate, and may have failed. More text is usually _bad_ for me. It must be consumed linearly. I need _specific_ text. Quality over quantity reply Image 79) "Is verbose mode the same as the old mode, where only file paths are spoken?" -- yes, this is exactly what the new verbose mode is. reply Image 80) And how to get to the old verbose mode then...? reply Image 81) Hit ctrl+o reply Image 82) Wait so when the UI for Claude Code says “ctrl + o for verbose output” that isn’t verbose mode? reply Image 83) That is more verbose — under the hood, it’s now an enum (think: debug, warn, error logging) reply Image 84)
### Full Content
Claude Code is being dumbed down? | Hacker News
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[](https://news.ycombinator.com/vote?id=46978710&how=up&goto=item%3Fid%3D46978710)[Claude Code is being dumbed down?](https://symmetrybreak.ing/blog/claude-code-is-being-dumbed-down/) ([symmetrybreak.ing](https://news.ycombinator.com/from?site=symmetrybreak.ing)) 1072 points by [WXLCKNO](https://news.ycombinator.com/user?id=WXLCKNO)[3 days ago](https://news.ycombinator.com/item?id=46978710) | [hide](https://news.ycombinator.com/hide?id=46978710&goto=item%3Fid%3D46978710) | [past](https://hn.algolia.com/?query=Claude%20Code%20is%20being%20dumbed%20down%3F&type=story&dateRange=all&sort=byDate&storyText=false&prefix&page=0) | [favorite](https://news.ycombinator.com/fave?id=46978710&auth=2a512c3faf74c66bfe87a242d7872ddc714bc7e0) | [690 comments](https://news.ycombinator.com/item?id=46978710) [](https://news.ycombinator.com/vote?id=46981968&how=up&goto=item%3Fid%3D46978710)[bcherny](https://news.ycombinator.com/user?id=bcherny)[2 days ago](https://news.ycombinator.com/item?id=46981968) | [next](https://news.ycombinator.com/item?id=46978710#46979394)[[–]](javascript:void(0)) Hey, Boris from the Claude Code team here. I wanted to take a sec to explain the context for this change. One of the hard things about building a product on an LLM is that the model frequently changes underneath you. Since we introduced Claude Code almost a year ago, Claude has gotten more intelligent, it runs for longer periods of time, and it is able to more agentically use more tools. This is one of the magical things about building on models, and also one of the things that makes it very hard. There's always a feeling that the model is outpacing what any given product is able to offer (ie. product overhang). We try very hard to keep up, and to deliver a UX that lets people experience the model in a way that is raw and low level, and maximally useful at the same time. In particular, as agent trajectories get longer, the average conversation has more and more tool calls. When we released Claude Code, Sonnet 3.5 was able to run unattended for less than 30 seconds at a time before going off the rails; now, Opus 4.6 1-shots much of my code, often running for minutes, hours, and days at a time. The amount of output this generates can quickly become overwhelming in a terminal, and is something we hear often from users. Terminals give us relatively few pixels to play with; they have a single font size; colors are not uniformly supported; in some terminal emulators, rendering is extremely slow. We want to make sure every user has a good experience, no matter what terminal they are using. This is important to us, because we want Claude Code to work everywhere, on any terminal, any OS, any environment. Users give the model a prompt, and don't want to drown in a sea of log output in order to pick out what matters: specific tool calls, file edits, and so on, depending on the use case. From a design POV, this is a balance: we want to show you the most relevant information, while giving you a way to see more details when useful (ie. progressive disclosure). Over time, as the model continues to get more capable -- so trajectories become more correct on average -- and as conversations become even longer, we need to manage the amount of information we present in the default view to keep it from feeling overwhelming. When we started Claude Code, it was just a few of us using it. Now, a large number of engineers rely on Claude Code to get their work done every day. We can no longer design for ourselves, and we rely heavily on community feedback to co-design the right experience. We cannot build the right things without that feedback. Yoshi rightly called out that often this iteration happens in the open. In this case in particular, we approached it intentionally, and dogfooded it internally for over a month to get the UX just right before releasing it; this resulted in an experience that most users preferred. But we missed the mark for a subset of our users. To improve it, I went back and forth in the issue to understand what issues people were hitting with the new design, and shipped multiple rounds of changes to arrive at a good UX. We've built in the open in this way before, eg. when we iterated on the spinner UX, the todos tool UX, and for many other areas. We always want to hear from users so that we can make the product better. T
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