Boris Cherny
A Claude Code maintainer or product figure credited here with shipping the new `/usage` command. The mention is relevant for PMs tracking feature-level product changes in developer tools.
Key Highlights
- Boris Cherny is repeatedly cited as a key operator behind Claude Code feature updates, pricing clarifications, and product-quality communications.
- His most notable product contribution in these mentions is the rollout of Claude Code’s `/usage` command for token-level visibility and self-serve debugging.
- He provides useful PM signals on how AI teams handle growth, capacity constraints, cloud-provider differences, and enterprise-driven pricing changes.
- His post-mortem and debugging updates make him especially relevant for PMs focused on reliability and operational excellence in AI developer tools.
- The mentions position him as an important source for understanding feature-level product changes across the Claude and Claude Code ecosystem.
Boris Cherny
Overview
Boris Cherny appears in these newsletter mentions as a visible product and engineering voice around Claude and Claude Code, especially on developer-facing features, pricing mechanics, usage transparency, and operational quality. He is repeatedly cited as the person announcing or clarifying concrete product changes such as the new `/usage` command, installer and UX updates, token-counting infrastructure across cloud providers, and adjustments to dialogue-style defaults and plan limits.For AI Product Managers, Boris Cherny matters less as a general public figure and more as a signal source for how a fast-moving AI developer tool is actually being operated. His mentions provide a practical window into product decision-making at the feature level: how teams expose cost visibility, respond to user complaints about token usage, adapt pricing to enterprise demand, manage capacity constraints, and publish post-mortems when quality issues surface. In that sense, he represents the kind of operator PMs should watch when benchmarking AI tooling strategy and execution.
Key Developments
- 2026-04-06: Boris Cherny said custom token-counting was built for Bedrock, Vertex, and Azure, while Anthropic used its native token-counting endpoint directly. This highlights infrastructure differences across model providers.
- 2026-04-13: He said Claude's default dialogue style was changed to Medium after users complained about high token usage, while noting response quality/length was not simply being cut.
- 2026-04-14: He noted that although Claude can be configured to block `node_modules`, letting the model inspect dependency source code often produces better coding help.
- 2026-04-16: He clarified that updated pricing plans had already gone live months earlier, driven by enterprise customer demand and published publicly.
- 2026-04-24: He published a post-mortem on recent Claude Code quality issues, including investigation steps, root causes, and lessons learned.
- 2026-05-10: He said Claude Code's move to a native installer means npm-based usage stats undercount real adoption; he also reported strong growth, including a major signup spike and 15× growth since January.
- 2026-05-10: He shared that Claude Code UX work was underway to improve responsiveness and add debug logs so users could self-diagnose hangs.
- 2026-05-11: He launched a new `/usage` command in Claude Code to show what actions are consuming tokens and where limits are being hit, helping users self-serve debugging.
- 2026-05-11: He also noted that 5-hour run limits were doubled across Claude Code plans, indicating active tuning of product constraints to improve planning and execution workflows.
- 2026-05-14: He described Mythos Preview as the first model to fully solve UK AISI cyber ranges end-to-end, including the previously unsolved “Cooling Tower,” and said deployment to defenders was moving ahead responsibly, with more to come on Glasswing.
- 2026-05-22: He rolled out an expanded `/usage` view in Claude Code’s CLI, breaking token usage down by Skills, Agents, MCPs, and Plugins, with desktop support planned next.
Relevance to AI PMs
- Use his updates as a playbook for cost transparency. The `/usage` work is a strong example of turning opaque token consumption into an understandable product surface. PMs building AI tools can copy this pattern by exposing spend and limits at the feature, workflow, or tool-call level.
- Watch how user feedback maps to product defaults. The change to Claude’s default style setting, the added debug logs, and doubled run limits show a practical loop from complaints to shipped adjustments. PMs can use the same approach to tune defaults before users churn.
- Study the operational side of AI product management. Cherny’s comments touch pricing segmentation, cloud-provider differences, growth measurement distortions, and post-mortems. For PMs, this is a reminder that AI product success depends on instrumentation, reliability, and capacity policy—not just model quality.
Related
- Anthropic: Core company context for many of the product and infrastructure decisions attributed here.
- Claude / Claude Code: The main products most closely associated with Boris Cherny’s mentions, especially around developer workflows.
- Bedrock, Vertex, Azure: Cloud/model distribution environments that required custom token-counting support.
- Pricing plans / enterprise-customer-demand: Connected to his clarification that plan changes were enterprise-driven and already live.
- Medium, Low, High, effort: Related to response-style or usage-control decisions that matter for token consumption and UX defaults.
- Mythos Preview, UK AISI, Glasswing: Connected to his comments on frontier cyber-defense model performance and deployment.
- claude-code-review, RAG, agentic-search, MCP, Skills, Agents, Plugins: Adjacent developer-tool and agent workflow concepts relevant to the `/usage` command and broader Claude Code ecosystem.
- Opus-46, Sonnet-46, Opus, GPT-4 Turbo: Relevant model landscape entities for PMs benchmarking capability, cost, and developer experience.
- Spotify: A related entity in the corpus, though no direct relationship is established in the cited mentions.
Newsletter Mentions (23)
“Boris Cherny rolled out a new `/usage` command in Claude Code’s CLI to break down token usage by Skills, Agents, MCPs, and Plugins.”
#5 𝕏 Boris Cherny rolled out a new `/usage` command in Claude Code’s CLI to break down token usage by Skills, Agents, MCPs, and Plugins. Desktop support is coming next.
“#10 𝕏 Boris Cherny : Mythos Preview is the first model to fully solve UK AISI’s cyber ranges end-to-end—including the once-unsolved “Cooling Tower”—and is being deployed to defenders as fast as responsibly possible, with more on Glasswing coming soon.”
#10 𝕏 Boris Cherny : Mythos Preview is the first model to fully solve UK AISI’s cyber ranges end-to-end—including the once-unsolved “Cooling Tower”—and is being deployed to defenders as fast as responsibly possible, with more on Glasswing coming soon. #11 in Peter Yang shows that Claude Code and Codex can effortlessly merge, edit, and crop scanned PDFs with simple prompts. He notes it far outperforms the clunky workflows in Preview or Adobe Acrobat.
“Boris Cherny launched a new `/usage` command in Claude Code that provides a deep dive into exactly which actions are consuming your tokens and their limits, so you can self-serve debug.”
#8 𝕏 Boris Cherny launched a new `/usage` command in Claude Code that provides a deep dive into exactly which actions are consuming your tokens and their limits, so you can self-serve debug. #10 𝕏 Boris Cherny doubled the 5-hour run limits on every Claude Code plan this week to streamline planning and execution.
“#5 𝕏 Boris Cherny says Claude Code’s switch to a native installer means npm-only stats undercount its real usage. On Thursday it hit its second-highest signup day ever with 15× growth since Jan 1—now you can ask Claude to debug your SQL. #6 𝕏 Boris Cherny is enhancing Claude Code’s UX for snappier performance and adding debug logs so users can self-serve hang diagnostics.”
GenAI PM Daily May 10, 2026 GenAI PM Daily 🎧 Listen to this brief 3 min listen Today's top 11 insights for PM Builders, ranked by relevance from X, Blogs, and LinkedIn. PromptLayer’s multi-step agent evaluation framework #1 𝕏 Jason Zhou launched `/goal` support in CodeX and Hermes agents for one-step autonomous coding, advising use of interview mode, clear stop conditions, and a goal-buddy to manage state and goal files. #2 📝 PromptLayer Blog What Is Agent Evaluation? A Practical Guide for AI Teams - Agent evaluation tests whether an AI agent reliably completes tasks across real inputs, edge cases, and new versions by scoring not just final outputs but multi-step behavior via black-box, trajectory, and component-level evaluations, using metrics like task completion rate, tool selection accuracy, unsupported-claim rate, latency/cost per step, and regression pass rate. PromptLayer offers tracing with span-level context, reusable datasets, batch evaluations, backtesting, regression testing, automated evaluation triggers on new prompt versions, and flexible pipelines including code execution, human input, conversation simulation, regex checks, and LLM assertions. #3 in Udi Menkes built his new product’s entire data flow in a single interactive HTML file—complete with diagrams, in-page navigation, and color-coded complexity—letting his team understand it in minutes instead of hours. #4 𝕏 Garry Tan suggests diagramming your AI agent codebases and architecture in plain ASCII, then relentlessly questioning each component to clarify design and accelerate product development. #5 𝕏 Boris Cherny says Claude Code’s switch to a native installer means npm-only stats undercount its real usage. On Thursday it hit its second-highest signup day ever with 15× growth since Jan 1—now you can ask Claude to debug your SQL. #6 𝕏 Boris Cherny is enhancing Claude Code’s UX for snappier performance and adding debug logs so users can self-serve hang diagnostics. #7 𝕏 Harrison Chase calls LangSmith an org-wide platform for building AI agents that speeds up cross-functional collaboration and tightens feedback loops. #8 𝕏 Santiago showcases a step-by-step guide for constructing Python-powered multi-agent systems from scratch, leveraging MCP and A2A patterns to incrementally add complexity and enable collaborative AI agents. #9 𝕏 Garry Tan spends $2K/mo on Openclaw AI tokens to turbocharge product development and startup insights. He’s “tokenmaxxing” now with a goal to make these capabilities affordable for everyone in 18 months. #10 𝕏 Harrison Chase argues that treating AI agents as systems to measure and iteratively improve isn’t just a technical challenge—it demands intentional human collaboration and team processes. #11 in Peter Yang warns that unedited AI-generated markdown can compound small errors over time—what starts as 5% “slop” quickly balloons into an overwhelming pile of confusing, unverified content. Found this valuable? Share it with another PM - they can subscribe at genaipm.com Unsubscribe • Switch to Weekly
“Boris Cherny published a post-mortem on recent Claude Code quality issues, detailing the investigation steps, root causes, and key takeaways for improving LLM tooling.”
#18 𝕏 Boris Cherny published a post-mortem on recent Claude Code quality issues, detailing the investigation steps, root causes, and key takeaways for improving LLM tooling. #19 𝕏 Jeff Dean provided advice on the Decoupled DiLoCo training system, enabling graceful failure handling in large-scale jobs by letting (N-1)/N units proceed when one fails.
“Boris Cherny clarifies that the new pricing plans went live six months ago (in November) in response to enterprise customer demand and have been publicly available on their site since then.”
#20 𝕏 Boris Cherny clarifies that the new pricing plans went live six months ago (in November) in response to enterprise customer demand and have been publicly available on their site since then.
“Boris Cherny shows that while you can configure Claude to block node_modules, in practice allowing it to read your dependencies’ source code often yields more helpful insights.”
#13 𝕏 Boris Cherny shows that while you can configure Claude to block node_modules, in practice allowing it to read your dependencies’ source code often yields more helpful insights.
“#11 𝕏 Boris Cherny says Claude’s default dialogue style was switched to Medium after users complained about high token usage.”
GenAI PM Daily April 13, 2026 GenAI PM Daily 🎧 Listen to this brief 3 min listen Today's top 14 insights for PM Builders, ranked by relevance from X, Blogs, and YouTube. #11 𝕏 Boris Cherny says Claude’s default dialogue style was switched to Medium after users complained about high token usage. He clarifies that response lengths haven’t been cut and future tweaks will follow user feedback.
“Boris Cherny built custom token-counting for Bedrock, Vertex, and Azure (which lack a native API) while using Anthropic’s built-in token-counting endpoint directly.”
#4 𝕏 Boris Cherny built custom token-counting for Bedrock, Vertex, and Azure (which lack a native API) while using Anthropic’s built-in token-counting endpoint directly.
“#4 𝕏 Boris Cherny explains that a surge in Claude usage from third-party tools has outstripped the design of existing subscriptions, so capacity is being managed carefully and prioritized for product and API customers.”
GenAI PM Daily April 04, 2026 GenAI PM Daily 🎧 Listen to this brief 3 min listen Today's top 17 insights for PM Builders, ranked by relevance from X, Blogs, and LinkedIn. Claude subscriptions will no longer cover usage on third-party tools like OpenClaw. #4 𝕏 Boris Cherny explains that a surge in Claude usage from third-party tools has outstripped the design of existing subscriptions, so capacity is being managed carefully and prioritized for product and API customers. #6 𝕏 Boris Cherny argues that subscription plans are optimized for specific usage patterns rather than raw token counts. He notes that building at scale involves trade-offs that prioritize certain use cases over others.
Related
Anthropic's coding assistant used for programming and automation tasks. The newsletter references it for building a custom approval device and for writing and research workflows inside AI agents.
AI company behind Claude. The newsletter references Claude usage and later notes Anthropic may have reached product-market fit.
Anthropic's model family used for agent orchestration and developer workflows. In this newsletter it is highlighted as powering CodeRabbit's agent orchestration system.
Anthropic’s latest Opus-class model release with a 1 million-token context window. It is positioned for long-context planning, coding, and agentic task execution.
A pattern for answering questions by retrieving relevant context and generating responses from it. The newsletter highlights multimodal RAG for searching across audio, image, and video data.
A Claude model used in the newsletter's example to run Python code and analyze a floor plan. It is discussed as part of an agentic workflow inside Claude Cowork.
A large language model used here to generate a corpus for retrieval evaluation. In AI PM contexts, it is relevant as a model choice for content generation and analysis tasks.
An AI-powered code review feature from Claude Code designed to provide deep PR feedback, catch bugs, and improve development workflows. It is presented as a research-preview beta for Team and Enterprise.
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