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Category: Anthropic

News, analysis, and profiles covering Anthropic the company and its team.

  • How to Build a Daily Briefing With Claude Cowork

    How to Build a Daily Briefing With Claude Cowork

    Last refreshed: June 9, 2026

    Claude AI · Tygart Media
    What this builds: A Cowork task that runs each morning, pulls context from Notion, checks your calendar and email, and delivers a structured daily briefing — without you opening anything. Estimated setup time: 90 minutes. Daily time saved: 20-30 minutes of morning context-gathering.

    One of the most practical Cowork automation setups is a daily briefing task — a scheduled agent run that assembles your morning context before you start work. Here’s exactly how to build it.

    Daily Briefing Prompt Patterns by Use Case

    Use Case Data Sources to Connect Key Prompt Elements
    Agency/freelancer Gmail, Calendar, Notion tasks Client deadlines, unread client emails, today’s meetings
    Real estate agent MLS alerts, Gmail, Calendar New listings, showing schedule, pending follow-ups
    Content creator Analytics, social mentions, Calendar Top performing posts, scheduled publishes, comments to address
    Operations manager Project tools, Slack digest, Calendar Blockers, overdue tasks, team standup agenda
    Researcher RSS/news feeds, email, Calendar New papers in field, upcoming deadlines, reading backlog

    What the Briefing Covers

    A well-designed daily briefing task pulls from 3-5 sources and returns a single structured summary. Typical sections: today’s calendar events (from Google Calendar MCP), open priority tasks (from Notion MCP), any overnight emails that need a response (from Gmail MCP), one or two metrics worth knowing (from whatever dashboard you track), and a suggested priority order for the day. The whole thing arrives as a Notion page or appears in a Cowork run log by the time you open your laptop.

    Step 1: Set Up Your MCP Connections

    The briefing task needs read access to the services it pulls from. In Claude Desktop settings, confirm you have active MCP connections for the services you want to include. At minimum: Notion (for tasks and project status) and Google Calendar (for today’s schedule). Gmail is optional but adds significant value if you get time-sensitive emails. Configure these in claude_desktop_config.json before building the task.

    Step 2: Write the Task Prompt

    The prompt is the core of the task. It needs to be specific about what to pull, how to structure the output, and where to write it. A working prompt structure:

    Daily Briefing Prompt Template:

    You are producing my daily morning briefing. Run these steps in order:

    1. Check my Google Calendar for today’s events. List all events with time, title, and any location or meeting link.
    2. Open my Notion [Priority Tasks database] and list any tasks marked P0 or P1 that are not yet complete.
    3. Check Gmail for any unread emails received in the last 12 hours that appear to need a response. List sender, subject, and one-sentence summary.
    4. Write the compiled briefing to a new Notion page titled “Daily Briefing — [today’s date]” under [your briefing parent page].

    Format the briefing with clear sections: Calendar, Priority Tasks, Email Review, Suggested First Action. Keep it scannable — bullet points, not paragraphs.

    Step 3: Create and Schedule the Task

    In Claude Desktop, open Cowork and create a new task. Paste your prompt. Set the schedule to daily at a time before you start work — 6:00 AM or 7:00 AM typically. Make sure Claude Desktop is configured to launch at startup on your machine so it’s running when the task fires. If your machine is off or sleeping when the task fires, it will be skipped — there’s no catch-up mechanism.

    Step 4: Test It Manually First

    Before relying on the scheduled run, trigger the task manually once. Verify it’s pulling from the right Notion database, writing to the correct parent page, and that the calendar and email integrations are connecting. Most first-run failures are MCP authentication issues — the MCP server needs to be authenticated with each service before the task can use it.

    Iteration: Making It Better Over Time

    The first briefing will be useful but imperfect. After a week of runs, refine the prompt based on what’s missing or what’s noise. Common refinements: add a “what’s overdue” check from Notion, filter email to only flag certain senders or subjects, add a weather check for field-based work, or include a one-line summary of the prior day’s Cowork run logs. Each iteration takes 5 minutes to update the prompt; the task runs better every week.

    Can Claude Cowork send me a daily briefing automatically?

    Yes — you build a Cowork task with the briefing prompt, connect it to your MCP sources (Notion, Google Calendar, Gmail), and schedule it to run each morning. The briefing appears in Notion before you start work. Claude Desktop must be running and your machine must be awake at the scheduled time.

    What MCP connections does a daily briefing task need?

    Minimum: Notion (for tasks) and Google Calendar (for schedule). Optional but valuable: Gmail (for overnight emails). All must be configured in claude_desktop_config.json and authenticated before the task can use them.

    Related: How Claude Cowork Can Actually Train Your Staff to Think Better — a 7-part series on using Cowork as a training tool across industries.


    How do I set up a daily briefing with Claude Cowork?

    In Claude Cowork, create a new conversation and write a system prompt that instructs Claude what to include in your briefing: today’s calendar events, unread priority emails, open tasks, and any custom data sources you’ve connected. Save this as a Project so the instructions persist. Then either open it each morning or use Claude Cowork’s scheduling capability to trigger it automatically.

    Can Claude Cowork pull data from my calendar automatically?

    Yes. Claude Cowork can read your connected calendar (Google Calendar, Outlook) when you grant it access through the MCP connector. It can list today’s events, upcoming deadlines, and suggest prep materials for meetings — all as part of a morning briefing prompt.

    What’s the best prompt for a Claude Cowork daily briefing?

    A strong briefing prompt includes: (1) Today’s date and day of week. (2) List all calendar events today with times. (3) Summarize the top 5 unread emails by priority. (4) List open tasks due today or overdue. (5) Flag anything that needs a decision before noon. Keep it under 500 words output for a scannable briefing.

    Can I schedule the daily briefing to run automatically?

    Yes. Claude Cowork supports scheduled tasks. You can configure your daily briefing to run at a set time each morning — Claude will execute the prompt, pull fresh data from connected sources, and deliver the output to your Cowork window or a connected channel. This turns the manual morning check into a fully automated routine.

  • Claude vs Notion AI: Inside the Database vs Outside — What the Tests Actually Show

    Claude vs Notion AI: Inside the Database vs Outside — What the Tests Actually Show

    Last refreshed: May 15, 2026

    Model Accuracy Note — Updated May 2026

    Current flagship: Claude Opus 4.7 (claude-opus-4-7). Current models: Opus 4.7 · Sonnet 4.6 · Haiku 4.5. Claude Opus 4.7 (claude-opus-4-7) is the current flagship as of April 16, 2026. Where this article references Opus 4.6 or earlier models, those references are historical. See current model tracker →. See current model tracker →

    Claude AI · Tygart Media · Tested March 2026
    The key distinction: Notion AI (with Claude Sonnet 4.6 or Opus inside) has native semantic access to your entire workspace — it traverses database relationships, reads inline comments, and synthesizes across pages it was never explicitly pointed at. Claude connected via API has to be told exactly where to look. Same model, fundamentally different information access.

    There are now two ways to run Claude inside Notion: through Notion AI (where Anthropic’s models power Notion’s built-in AI features with workspace search enabled), and through direct Claude integration (where your Claude instance connects to Notion via the API or MCP). Most people assume these are equivalent — same Claude model, same output. They are not. The difference isn’t the model. It’s the context layer underneath it.

    What “Inside the Database” Actually Means

    When you use Notion AI with workspace search enabled, Claude (or another model) is operating with native Notion context. It can traverse relational links between databases the way a human would navigate a workspace — following a CRM record to its linked action items, pulling content pipeline data alongside revenue records, reading the inline comment threads that live on specific blocks. It doesn’t just retrieve documents; it understands the relationships between documents.

    When you connect Claude to Notion via the API, Claude receives whatever data you explicitly fetch and pass to it. It reads exactly what you give it, nothing more. A cross-database synthesis requires you to make multiple API calls, stitch the data together, and pass the combined result. You are the relationship layer; Claude is the reasoning layer on top of your assembly work.

    Real Test Results: The Same Task, Both Ways

    We ran a structured test in March 2026 — asking multiple AI models inside Notion AI (with workspace search) to produce a complete client health summary across four databases simultaneously: Master CRM, WordPress Site Operations, Content Pipeline, and Revenue Pipeline. Then comparing what Claude via API alone could produce on the same client.

    The result was not close on the first run. Notion AI with Claude Sonnet 4.6 took approximately 35 seconds and returned:

    • Revenue Pipeline data ($2,000/month Closed Won)
    • CRM contact details with email and phone
    • WordPress ops: Health Score, post count, connection method, specific IPs
    • A cumulative content table (Pre-2026: 30, Jan: 529, Feb: 375, Mar: 164 = 1,098 total)
    • SEO performance comparison: Clicks +2,217%, SEO Value +3,028%, Keywords +271% (Dec 2025 vs Feb 2026)
    • 7 prioritized attention items with a strategic bottom-line summary

    Claude Opus 4.7 inside Notion earned what we graded S — executive intelligence tier. It opened with a strategic framing (“Overall Health: Needs Attention”), named all Notion sources it queried, built a full P0-P3 priority matrix with rationale, and surfaced findings none of the other models caught: a hardcoded phone number as the root cause of attribution gap, a missing contact form on the /contact-us/ page, and the exact date of each optimization action in the content workflow.

    The single finding that made the difference: Opus 4.6 inside Notion connected a 403 error from an SEO drift detector to a specific operational blind spot — and traced it back to a configuration issue that had been invisible because it required reading both a monitoring log and an infrastructure record simultaneously. Claude via API would have needed those two documents explicitly fetched and merged before it could reason across them.

    What Claude Inside Notion Can Do That External Claude Cannot

    Capability Notion AI (Claude inside) Claude via API/MCP
    Semantic traversal across linked databases ✅ Native ❌ Manual fetch required
    Read inline comments and discussion threads ✅ Yes ❌ Not via standard API
    Cross-reference dashboard data with page content ✅ Automatic ❌ Requires explicit assembly
    Follow relational links without being told to ✅ Yes ❌ Must specify each fetch
    Identify discrepancies between related records ✅ Can catch stale data ⚠ Only if you provide both records
    Access workspace search across all pages ✅ Full semantic search ⚠ API search is keyword-based
    Run without human assembly of context ✅ Yes ❌ Requires orchestration layer

    What External Claude Does Better

    The inside-the-database advantage is real, but it’s not the whole story. Claude connected externally through the API or MCP has capabilities Notion AI cannot replicate:

    Taking actions. Notion AI can read and summarize. External Claude can read, reason, and then act — publish a WordPress post, update a Metricool schedule, send an email, write a file to GCP. Notion AI is fundamentally a read and summarize layer. External Claude connected to tools is an execution layer.

    Custom system prompts and instructions. External Claude sessions can be loaded with specific operational context, role definitions, and multi-step task chains. Notion AI’s model selection is relatively fixed — you pick the model, but you can’t deeply configure its behavior the way you can with a direct API call.

    Model routing and cost control. External Claude lets you route specific tasks to specific model tiers — Haiku for bulk classification, Sonnet for standard work, Opus for strategic synthesis. Notion AI doesn’t expose that level of routing control to the user.

    Automation and scheduling. External Claude runs in Cowork tasks, Cloud Run cron jobs, and triggered pipelines. Notion AI runs when a human opens a page and asks a question.

    The Architecture That Gets the Most From Both

    The most powerful setup is not a choice between them — it’s using both for what each does best. Notion AI with workspace search is the intelligence layer: the “eyes” that can synthesize across your entire knowledge base and surface what matters. External Claude is the execution layer: the “hands” that take action based on what the intelligence layer surfaces.

    Practically: run a Notion AI query with Opus 4.6 to get the full client health picture and identify the top 3 priorities. Then hand those priorities to external Claude (via Cowork or a direct API call) to execute: draft the emails, update the records, publish the content. The separation of concerns — Notion AI for global workspace intelligence, external Claude for structured action — is more powerful than either alone.

    One concrete implementation: a daily Cowork task that first calls the Notion MCP to fetch key database records, then passes that assembled context to Claude for action planning, then executes a task list. The fetch step approximates what Notion AI does natively, but you control exactly what gets assembled. For well-defined, repeating workflows, this is often sufficient. For exploratory synthesis (“give me the full picture across this client’s history”) where you don’t know in advance what’s relevant, Notion AI’s native traversal is materially better.

    Model Performance Inside Notion AI (March 2026 Test)

    Model Grade Speed Best For
    Claude Opus 4.7 S ~60s Executive summaries, strategic framing, P0-P3 priority matrices. Found unique issues no other model caught.
    Claude Sonnet 4.6 A+ ~35s Operational detail, SEO metrics, granular data presentation. Best for recurring ops reports.
    GPT-5.2 A+ ~90s Deepest data mining. Named individuals, deadlines, specific IDs. Slowest but most thorough.
    Gemini 3.1 Pro A ~25s Fastest response. Strong all-rounder. Best for quick status checks.
    GPT-5.4 A ~40s Clean structured output. Good first-pass default for routine checks.

    The multi-model finding: no single model caught everything. Running the same query through three models and distilling their unique findings produced materially better intelligence than any single model alone. Opus 4.6 found the hardcoded phone number and missing contact form. GPT-5.2 found the CRM coverage gap and named specific people with deadlines. Sonnet 4.6 built the clearest data tables. Together: a complete operational picture.

    Is Notion AI the same as using Claude directly?

    No. Both can use Claude models, but Notion AI with workspace search has native semantic access to your entire Notion workspace — it traverses linked databases and reads relationships automatically. External Claude via API only sees data you explicitly fetch and pass to it. Same model, different context layer.

    Which is better: Claude inside Notion or Claude connected via API?

    Depends on the task. Notion AI (Claude inside) is better for cross-database synthesis and global workspace intelligence — it can see everything without you assembling it. External Claude is better for taking action — publishing, updating, scheduling, automating. The most powerful setup uses both: Notion AI for intelligence, external Claude for execution.

    Can Claude via API replace Notion AI?

    Partially. The Notion MCP lets external Claude fetch database records, but it still requires you to specify what to fetch. Notion AI’s native traversal follows relationships automatically without explicit instruction. For exploratory synthesis across an unknown-in-advance data landscape, Notion AI’s native context is materially better than assembled API context.


  • Running Claude Inside a GCP VM: The Fortress Architecture Explained

    Running Claude Inside a GCP VM: The Fortress Architecture Explained

    Last refreshed: May 15, 2026

    Claude AI · Tygart Media
    What this architecture solves: Claude API calls made from inside a private GCP VPC never touch the public internet. Your data, prompts, and outputs stay within your cloud perimeter. This is the standard for regulated industries and the right model for any organization where data sovereignty matters.

    Most Claude API usage works the same way: your application makes a call to api.anthropic.com across the public internet. For consumer apps and developer projects, that’s fine. For enterprises handling sensitive data — healthcare, finance, legal, government — “fine” isn’t the bar. The Fortress Architecture runs Claude inference through Google Cloud’s Vertex AI from inside a private VPC, so sensitive data never crosses a public network boundary.

    The Core Architecture

    Instead of calling the Anthropic API directly, your application calls Claude through Vertex AI from within a GCP Compute Engine VM or Cloud Run service inside your VPC. VPC Service Controls create a security perimeter around your Vertex AI resource. Requests to Claude stay inside that perimeter — they originate from your private network, route through Google’s internal infrastructure to Vertex AI, and return inside the same boundary.

    From a data flow perspective: your application → private VPC → Vertex AI API (Google internal) → Claude model inference → back through VPC → your application. No public internet hop at any point.

    Why a VM Instead of a Direct API Call

    Running Claude through a VM — rather than a developer’s laptop or a serverless function with public internet access — gives you several properties that matter at enterprise scale:

    Consistent identity. All Claude calls originate from a known service account with specific IAM permissions. There’s no risk of a developer accidentally using personal credentials or exposing an API key.

    Network isolation. The VM sits inside a VPC with firewall rules. You control exactly what it can reach and what can reach it. No lateral movement from a compromised endpoint reaches your Claude integration.

    Audit trail. Every Claude API call through Vertex AI generates Cloud Logging entries. You get a complete, immutable record of what was asked and when — essential for compliance in healthcare and financial services.

    Centralized cost control. All AI spend flows through one GCP project with budget alerts and quotas. No shadow AI spending from individual developers using personal API keys.

    Implementation Pattern

    The standard setup: a Cloud Run service or Compute Engine VM runs your Claude-connected application code inside a VPC. A service account with roles/aiplatform.user is the only identity that can call Vertex AI. VPC Service Controls restrict Vertex AI access to requests originating from your perimeter. Cloud Logging captures all API activity. Budget alerts on the GCP project catch unexpected usage spikes.

    The application code itself is straightforward — the Anthropic Python or Node.js SDK with the Vertex AI configuration flag set. The security comes from the infrastructure layer, not the application layer.

    When This Architecture Is Worth the Setup

    For a solo developer or small startup, this is overkill. The setup overhead — VPC configuration, service accounts, VPC Service Controls, Cloud Logging — is a full day of infrastructure work. For organizations where a data breach involving patient records, financial data, or privileged legal communications would be catastrophic, that day of setup is a trivial cost against the risk.

    The categories where this architecture is essentially required: HIPAA-covered healthcare applications, financial services with SOC 2 or PCI requirements, legal services handling privileged communications, government contractors, and any application processing PII at scale.

    The Real Operational Benefit Beyond Security

    The compliance story is obvious. The less-discussed benefit is operational consistency. When all Claude usage flows through a single controlled channel, you get uniform behavior (same model version, same parameters, same rate limits), centralized prompt management (update the system prompt in one place, not in every developer’s local config), and predictable costs. The Fortress Architecture is as much an operational discipline as it is a security model. See The Fortress Architecture: Full Guide for the complete technical breakdown and Claude on Vertex AI: Why Route Through GCP for the Vertex AI setup.

    Can you run Claude inside a private GCP VPC?

    Yes — through Vertex AI with VPC Service Controls. Claude requests originate inside your private network perimeter and never cross the public internet. This is the standard architecture for regulated industry deployments.

    Is Claude HIPAA compliant on GCP?

    Vertex AI is available under Google Cloud’s HIPAA BAA. Running Claude through Vertex AI inside a VPC with appropriate controls can support HIPAA-compliant architectures. Consult your compliance team on the full requirements for your specific application.

    Why run Claude on a GCP VM instead of calling the API directly?

    A VM inside a VPC gives you network isolation, a consistent service account identity, complete audit logging, centralized cost control, and the ability to apply VPC Service Controls. For enterprise deployments, this is the correct architecture — not a development shortcut.

  • Claude Release History: Every Model From Claude 1 to Claude 4.6

    Claude Release History: Every Model From Claude 1 to Claude 4.6

    Last refreshed: June 9, 2026

    Model Accuracy Note — Updated June 9, 2026

    Current flagship: Claude Opus 4.8 (claude-opus-4-8). Current models: Opus 4.8 · Sonnet 4.6 · Haiku 4.5. Claude Opus 4.8 (claude-opus-4-8) is the current Opus-tier model as of June 9, 2026; Claude Fable 5 is the overall flagship. Where this article references Opus 4.6 or earlier models, those references are historical. See current model tracker →. See current model tracker →

    Claude AI · Tygart Media · Last Updated June 2026
    Current models (June 2026): Claude Opus 4.8 and Claude Sonnet 4.6 — released February 2026. Claude Haiku 4.5 — October 2025. Original Claude 4.0 models deprecated, retiring June 15, 2026.

    Anthropic has released over a dozen Claude models since the first public launch in March 2023. This page is the complete record — every model, its release date, the key capability it introduced, and its current status. It’s updated when Anthropic ships new releases.

    The Complete Claude Model Timeline

    Model Released Key Capability Status
    Claude 1 March 2023 First public release. Constitutional AI, 100K context. Retired
    Claude 1.3 July 2023 Improved reasoning and code generation. Retired
    Claude 2 July 2023 Doubled context to 100K, stronger coding and analysis. Retired
    Claude 2.1 November 2023 Reduced hallucination rate, tool use support added. Retired
    Claude 3 Haiku March 2024 Fastest, cheapest Claude 3 tier. Near-instant responses. Deprecated
    Claude 3 Sonnet March 2024 Balanced performance/cost. First strong coding model. Deprecated
    Claude 3 Opus March 2024 Top benchmark scores at launch. Best reasoning of the generation. Deprecated
    Claude 3.5 Sonnet June 2024 Outperformed prior Opus on most benchmarks at Sonnet price. Landmark release. Deprecated
    Claude 3.5 Haiku October 2024 Speed/cost tier for Claude 3.5 generation. Deprecated
    Claude 3.5 Sonnet v2 October 2024 Computer use capability introduced. Improved coding. Deprecated
    Claude 3.7 Sonnet February 2025 Extended thinking. First Claude with explicit chain-of-thought reasoning. Deprecated
    Claude Sonnet 4 May 2025 Claude 4 generation launch. Major coding gains, SWE-bench leadership. ⚠ Retiring June 15, 2026
    Claude Opus 4 May 2025 Maximum capability in Claude 4 generation at launch. ⚠ Retiring June 15, 2026
    Claude Haiku 4.5 October 2025 Speed/cost tier for 4.x generation. 200K context. ✅ Current
    Claude Opus 4.8 February 5, 2026 1M token context window (beta then GA). Improved long-horizon reasoning. ✅ Current flagship
    Claude Sonnet 4.6 February 17, 2026 Near-Opus performance. 1M token context. Dramatically improved computer use. ✅ Current default

    The Generational Leaps That Mattered Most

    Claude 3.5 Sonnet (June 2024) — The Benchmark Flip

    This was the release that established Claude as a serious competitor to GPT-4. Claude 3.5 Sonnet outperformed Claude 3 Opus on most benchmarks at half the cost — the first time a Sonnet-tier model beat the prior generation’s flagship. It also introduced Artifacts, the interactive output canvas that became a defining Claude feature. Every generation since has followed this pattern: new Sonnet outperforms prior Opus.

    Tracking Claude Releases?

    I’ll email you when something meaningful ships — no noise, no newsletter cadence.

    Just a personal note when Anthropic releases something that actually changes how you should be working.

    Email Will → will@tygartmedia.com

    Claude 3.7 Sonnet (February 2025) — Extended Thinking

    Extended thinking gave Claude an explicit reasoning layer before responding — the model could work through a problem step-by-step before committing to an answer. This was Anthropic’s answer to OpenAI’s o1 and marked the beginning of “reasoning models” as a mainstream concept in Claude’s lineup.

    Claude Sonnet 4 (May 2025) — Coding Leadership

    The Claude 4 launch pushed Claude to the top of SWE-bench Verified, the real-world software engineering benchmark that matters most to developers. Claude Code launched alongside it and reached $1B in annualized revenue by November 2025 — one of the fastest-growing developer tools in history.

    Claude Sonnet 4.6 (February 2026) — Computer Use at Scale

    The 4.6 generation’s most significant practical advance was dramatically improved computer use — Claude’s ability to navigate browsers, fill forms, click through interfaces, and operate software autonomously. Combined with the 1M token context window reaching general availability, this made Claude genuinely useful for long-horizon agentic tasks that previously required constant human intervention.

    What Comes Next

    Claude 5 has not been officially announced as of May 2026. No official announcement as of June 2026. The pattern suggests Claude 5 Sonnet will outperform current Opus 4.6 at lower cost — consistent with every prior generation transition. See Claude 5 Release Date: What We Know.

    For current API strings and deprecation deadlines, see the Current Claude Model Version Tracker.

    When was Claude first released?

    Claude 1 launched publicly in March 2023. Anthropic was founded in 2021 by former OpenAI researchers, and Claude was in limited testing before the public launch.

    How many Claude models are there?

    As of June 2026, Anthropic has released approximately 16 public model versions across 5 generations (Claude 1 through Claude 4.6). Three models are currently active: Opus 4.6, Sonnet 4.6, and Haiku 4.5.

    What was the best Claude model ever released?

    Claude Sonnet 4.6 (February 2026) holds the current highest benchmark scores and represents the peak of the Claude 4 generation. On SWE-bench Verified it scores 79.6% — among the highest of any model at its release.


    Claude Opus 4.8 — April 2026

    Claude Opus 4.8 launched as the flagship, replacing Opus 4.6 as the most capable generally available model at the time. As of June 9, 2026, Claude Fable 5 surpasses it and holds the top position. Key changes:

    • Step-change improvement in agentic coding over Claude Opus 4.7
    • API string: claude-opus-4-8
    • Pricing: Same as Opus 4.6 — $5/$25 per million tokens (input/output)
    • Breaking changes vs Opus 4.6 — review the Anthropic migration guide before upgrading
    • Available on direct API, Amazon Bedrock (27 regions), and Vertex AI

    Claude Fable 5 — June 2026

    On June 9, 2026, Anthropic released Claude Fable 5 — the public debut of its Mythos-class model tier and the first Claude positioned above Opus. Key facts:

    • New top tier: scored more than 10% higher than Claude Opus 4.8 on some benchmarks at launch
    • API string: claude-fable-5
    • Pricing: $10/$50 per million tokens (input/output) — double Opus 4.8
    • Context: 1M tokens, 128K max output
    • API surface: adaptive thinking only; sampling parameters removed

    Full coverage of the launch month: Claude updates June 2026.

    Current active model strings: claude-fable-5 · claude-opus-4-8 · claude-sonnet-4-6 · claude-haiku-4-5-20251001

    Frequently Asked Questions

    What is the most recent Claude model as of June 2026?

    As of June 2026, the most recent Claude model is Claude Fable 5, released June 9, 2026 – a new tier positioned above Opus (1M token context, 128K output, $10/$50 per million tokens). Below it sit Claude Opus 4.8 (Opus-tier flagship), Claude Sonnet 4.6 (best speed/intelligence balance), and Claude Haiku 4.5 (fastest).

    When did Claude 4 launch?

    Claude 4 launched in 2025 with Claude Sonnet 4.5 and Claude Opus 4.6 as the initial releases, followed by Opus 4.7 and Opus 4.8. In June 2026, Anthropic added Claude Fable 5 as a new tier above Opus. The Claude 4 generation introduced 1M token context windows and significantly improved reasoning.

    How many Claude models have there been?

    Anthropic has released models across four major generations: Claude 1 (2023), Claude 2 (2023), Claude 3 (2024 — Haiku, Sonnet, Opus), and Claude 4 (2025–2026 — Haiku 4.5, Sonnet 4.5/4.6, Opus 4.6/4.7/4.8). Each generation brought major capability improvements.

    What replaced Claude 3 Opus?

    Claude Opus 4.6, released in 2025, replaced Claude 3 Opus as Anthropic’s flagship model. It was subsequently succeeded by Opus 4.7 and then Opus 4.8, the current flagship as of June 2026.

    What is the difference between Claude Sonnet 4.5 and 4.6?

    Claude Sonnet 4.6 is the successor to Sonnet 4.5, with improvements in reasoning, coding, and instruction following. Sonnet 4.6 is currently Anthropic’s recommended model for the best combination of speed and intelligence at $3 input / $15 output per million tokens.

    Does Claude have a release history page?

    Anthropic maintains official model documentation at platform.claude.com. This page tracks Anthropic’s model release history chronologically from Claude 1 through the current Claude 4 generation, including API model IDs and approximate release dates.

    Get alerted when Claude releases a new model

    We track Anthropic’s releases, pricing, and limits daily and send a short note when the lineup changes. Occasional, no spam.

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  • Claude Updates April & May 2026: Infrastructure Expansion, Security Beta, Managed Agents

    Claude Updates April & May 2026: Infrastructure Expansion, Security Beta, Managed Agents

    Last refreshed: May 15, 2026

    May 2026 Updates Now Live

    SpaceX compute deal, Claude Security Beta, Managed Agents public beta, and more.

    → See May 2026 Updates

    What Changed — Quick Answer

    • Current flagship: Claude Opus 4.7 (claude-opus-4-7)
    • Claude Code: Generally available — install guide here
    • Retired: Claude Sonnet 4, Claude Opus 4 (April 20, 2026)
    • Haiku 3: Fully retired — migrate to claude-haiku-4-5-20251001
    • Pricing: Opus 4.7 same as 4.6 — $5/$25 per MTok

    Full breakdown below. Current model tracker →

    Model Accuracy Note — Updated May 2026

    Current flagship: Claude Opus 4.7 (claude-opus-4-7). Current models: Opus 4.7 · Sonnet 4.6 · Haiku 4.5. Claude Opus 4.7 (claude-opus-4-7) is the current flagship as of April 16, 2026. Where this article references Opus 4.6 or earlier models, those references are historical. See current model tracker →. See current model tracker →

    Change Status Action Required
    Claude Opus 4.7 launched Current flagship Update API string to claude-opus-4-7
    Claude Sonnet 4 retired Retired Apr 20 Migrate to claude-sonnet-4-6
    Claude Opus 4 retired Retired Apr 20 Migrate to claude-opus-4-7
    Claude Haiku 3 retired Retired Feb 2026 Migrate to claude-haiku-4-5-20251001
    Claude Code generally available Live Install guide →
    Managed Agents in public beta Beta Use managed-agents-2026-04-01 header
    300K output tokens on Batches API Available Use output-300k-2026-03-24 header

    Claude AI · Tygart Media · Updated April 2026
    This month’s biggest changes: Claude Sonnet 4 and Opus 4 (original 4.0 models) deprecated — retiring June 15, 2026. Cowork generally available on macOS and Windows. New plugin marketplace. Advisor tool in public beta. Computer use added to Cowork for Pro/Max users.

    Anthropic shipped a significant number of product updates in April 2026. This digest covers everything that changed — model deprecations, Cowork updates, Claude Code releases, and API additions — in one place. Bookmark this and check the Current Claude Model Tracker for the latest model strings.

    Model Changes

    Claude 4.0 Deprecation — Action Required by June 15

    Anthropic announced the deprecation of claude-sonnet-4-20250514 and claude-opus-4-20250514 — the original Claude 4.0 model versions from May 2025. Both retire from the Anthropic API on June 15, 2026. If you have either string in production code, migrate to claude-sonnet-4-6 and claude-opus-4-7 respectively. Full migration guide: Claude 4 Deprecation: What to Migrate To.

    1M Token Context Window — Now Generally Available

    The 1 million token context window for Claude Opus 4.7 and Claude Sonnet 4.6 is now generally available at standard pricing with no long-context surcharge. Previously in beta, this window supports approximately 750,000 words or about 2,500 pages of text in a single session. Also available on Vertex AI for both models.

    Cowork Updates

    Cowork Generally Available

    Claude Cowork reached general availability on macOS and Windows via Claude Desktop this month, exiting the research preview label. The GA release added expanded usage analytics, OpenTelemetry support for monitoring Cowork activity, and role-based access controls for Enterprise plans so admins can customize which Claude capabilities each team group can access.

    Computer Use in Cowork

    Pro and Max plan users can now give Claude access to computer use within Cowork — meaning Claude can open files, run dev tools, navigate browsers, point, click, and interact with what’s on screen to complete tasks autonomously. No setup required for Pro/Max users. This makes Cowork’s Dispatch feature substantially more capable, letting Claude take multi-step actions on your computer while you’re away.

    Scheduled and Recurring Tasks

    Cowork now supports creating and scheduling both recurring and on-demand tasks from within the app. Previously this required configuration outside the main interface. A new Customize section in Claude Desktop groups skills, plugins, and connectors in one place.

    Plugin Marketplace

    Anthropic launched a new plugin marketplace for Team and Enterprise plans with admin controls for managing which plugins are available to which users. Enterprise admins can approve, restrict, or block specific plugins org-wide.

    Claude Code Updates

    Vertex AI Setup Wizard

    Claude Code v2.1.98 and later include a /setup-vertex wizard that automates Google Cloud Vertex AI configuration — project selection, region, model pinning — without manually setting environment variables. Run claude --version to check if you’re on a supported version. Full setup guide: How to Run Claude Code on Vertex AI.

    Advisor Tool — Public Beta

    The Anthropic API now supports a public beta advisor tool (beta header: advisor-tool-2026-03-01). The pattern: pair a faster executor model with a higher-intelligence advisor model that provides strategic guidance mid-generation. Long-horizon agentic workloads get close to advisor-solo quality at executor-model costs. Useful for tasks where you want Opus-level reasoning with Sonnet-level speed on the bulk of token generation.

    Worktree Switching and PreCompact Hooks

    Claude Code added a path parameter to the EnterWorktree tool for switching into existing worktrees, PreCompact hook support (hooks can now block compaction by returning a decision block), and background monitor support for plugins via a top-level monitors manifest key.

    Interactive Connectors in Claude Mobile

    The Claude mobile app can now connect to fully interactive apps — live charts, diagrams, and shareable assets rendered visually inside conversations. Pull up live data, sketch diagrams, and build assets directly in the mobile chat interface.

    What to Watch in May 2026

    The June 15 deprecation deadline for Claude 4.0 models is the immediate action item for any team running the original 4.0 model strings. Claude 5 remains unannounced but expected Q2-Q3 2026 based on release cadence — see Claude 5 Release Date: What We Know. The advisor tool beta is worth testing for any team running complex agentic pipelines.

    What changed in Claude in April 2026?

    Key April 2026 changes: Claude 4.0 models deprecated (retiring June 15), Cowork reached general availability with computer use for Pro/Max users, 1M token context window became generally available, plugin marketplace launched, and the Vertex AI setup wizard shipped in Claude Code.

    What is the Claude Cowork update in April 2026?

    Cowork reached general availability with computer use for Pro/Max users, scheduled recurring tasks, a new plugin marketplace for Team/Enterprise, and enterprise role-based access controls. Previously in research preview.

    May 2026 Updates

    • Claude Opus 4.7 launched — new flagship, step-change in agentic coding, same pricing as Opus 4.6 ($5/$25/MTok). API string: claude-opus-4-7. Note: includes API breaking changes vs 4.6.
    • Claude Haiku 3 retired — all requests now return errors. Migrate to claude-haiku-4-5-20251001.
    • Claude Managed Agents in public beta — fully managed agent harness with secure sandboxing, built-in tools, and SSE streaming.
    • 300K output tokens on Message Batches API for Opus 4.7, Opus 4.6, and Sonnet 4.6 via output-300k-2026-03-24 beta header.
    • Claude in Amazon Bedrock now open to all customers in 27 regions.

    See the current model version tracker for the full active model list.

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    Update: May 2026 Infrastructure & Enterprise Launch

    Added May 9, 2026

    The following changes landed after this article’s original publication date. Model strings and pricing remain current as of this update.

    SpaceX Colossus 1 Compute Deal — Rate Limits Doubled (May 6, 2026)

    Anthropic announced a compute partnership with SpaceX, gaining access to the Colossus 1 data center. Immediate effect on paying subscribers:

    • 5-hour rate limits doubled for Pro, Max, Team, and seat-based Enterprise
    • Tier 1 API customers: 1,500% increase in max input tokens/minute; 900% increase in max output tokens/minute
    • Peak-hours throttling eliminated for Pro and Max subscribers
    • Free plan: No change — explicitly excluded from all increases

    Source: anthropic.com/news/higher-limits-spacex

    Claude Security Beta — Enterprise Vulnerability Scanning (April 30, 2026)

    Anthropic opened Claude Security (formerly Claude Code Security) to all Enterprise customers. Powered by Claude Opus 4.7, it traces data flows across a codebase the way a security researcher would — not through signature matching. Every finding ships with confidence rating, severity, reproduction steps, and a recommended fix.

    Technology partners embedded in Claude Security: CrowdStrike, Microsoft Security, Palo Alto Networks, SentinelOne, TrendAI, and Wiz. Services partners deploying Claude Security solutions: Accenture, BCG, Deloitte, Infosys, and PwC.

    Note: Claude Mythos Preview (the model that found 271 Firefox vulnerabilities for Mozilla in April) remains invitation-only through Project Glasswing. Claude Security Beta uses Claude Opus 4.7 and is available to all Enterprise subscribers.

    Managed Agents Public Beta (April 2026)

    Multiagent Orchestration and Outcomes moved to public beta. Dreaming (agents that review and improve their own memory between sessions) remains developer preview — invitation-only access. Use the managed-agents-2026-04-01 beta header to access Managed Agents via the API.

    Model Deprecation Reminder: June 15, 2026

    Claude Sonnet 4 and Claude Opus 4 (original 4.0-generation, 20250514 date-string model IDs) retire June 15, 2026. If you have any API integrations using those strings, update them before that date. Current active models: claude-opus-4-7, claude-sonnet-4-6, claude-haiku-4-5-20251001.



  • How to Run Claude Code on Vertex AI Using Your GCP Credits

    How to Run Claude Code on Vertex AI Using Your GCP Credits

    Last refreshed: May 15, 2026

    Model Accuracy Note — Updated May 2026

    Current flagship: Claude Opus 4.7 (claude-opus-4-7). Current models: Opus 4.7 · Sonnet 4.6 · Haiku 4.5. Claude Opus 4.7 (claude-opus-4-7) is the current flagship as of April 16, 2026. Where this article references Opus 4.6 or earlier models, those references are historical. See current model tracker →. See current model tracker →

    Claude AI · Tygart Media
    What this sets up: Claude Code running through your Google Cloud account instead of the Anthropic API. Same models, same capabilities — billed to GCP. New GCP accounts can run this for free using $300 in signup credits.

    Claude Code is Anthropic’s terminal-native coding agent. By default it bills through your Anthropic account. But you can route it entirely through Google Cloud’s Vertex AI — meaning it charges your GCP account instead, and you can use existing GCP credits, startup credits, or free trial credits to run it at no incremental cost. Here’s the exact setup.

    What You Need Before Starting

    A Google Cloud account with a project created. Vertex AI API enabled on that project. Claude models requested and approved in Vertex AI Model Garden. Claude Code installed (npm install -g @anthropic-ai/claude-code). The gcloud CLI installed and authenticated. That’s it — no Anthropic API key required once this is configured.

    Need this set up for your team?

    I set up Claude integrations, GCP infrastructure, and AI workflows for businesses. If you’d rather ship than configure — will@tygartmedia.com

    Step 1: Enable Vertex AI and Request Claude Model Access

    In the Google Cloud Console, go to Vertex AI > Model Garden and search for “Claude.” Request access to at least Claude Sonnet 4.6 (the primary Claude Code model) and Claude Haiku 4.5 (used for lightweight operations). Without Haiku, Claude Code will use Sonnet for everything — slower and more expensive for simple tasks. Enable Opus 4.6 as well if you need maximum capability for complex tasks.

    Model access approval is typically instant for most GCP accounts.

    Step 2: Authenticate with Google Cloud

    Run both commands below — the first authenticates your user account, the second sets application default credentials that Claude Code will pick up automatically:

    gcloud auth login
    gcloud auth application-default login

    Set your project: gcloud config set project YOUR-PROJECT-ID

    Enable the Vertex AI API: gcloud services enable aiplatform.googleapis.com

    Step 3: Configure Claude Code to Use Vertex AI

    Set these environment variables. On macOS/Linux, add them to your ~/.zshrc or ~/.bashrc. On Windows, use PowerShell’s [System.Environment]::SetEnvironmentVariable at the User level so they persist across sessions.

    macOS / Linux:
    export CLAUDE_CODE_USE_VERTEX=1
    export CLOUD_ML_REGION=global
    export ANTHROPIC_VERTEX_PROJECT_ID=your-project-id
    export ANTHROPIC_DEFAULT_SONNET_MODEL=claude-sonnet-4-6
    export ANTHROPIC_DEFAULT_HAIKU_MODEL=claude-haiku-4-5@20251001
    Windows (PowerShell — run once, persists across sessions):
    [System.Environment]::SetEnvironmentVariable("CLAUDE_CODE_USE_VERTEX","1","User")
    [System.Environment]::SetEnvironmentVariable("CLOUD_ML_REGION","global","User")
    [System.Environment]::SetEnvironmentVariable("ANTHROPIC_VERTEX_PROJECT_ID","your-project-id","User")

    Step 4: Verify the Setup

    Launch Claude Code and run /status. You should see API provider: Google Vertex AI and your GCP project ID. If you see the Anthropic API provider instead, your environment variables haven’t loaded — restart your terminal and try again.

    Step 5: Use the New Wizard (Claude Code v2.1.98+)

    If you’re on Claude Code version 2.1.98 or later, you can skip manual environment variable setup. Run /setup-vertex inside Claude Code and the wizard walks you through project selection, region, and model pinning automatically. Run claude --version to check your version first.

    Region Selection: Global vs Regional Endpoints

    Use CLOUD_ML_REGION=global unless you have specific compliance reasons to pin to a region. Global endpoints get the latest models first, have better availability, and don’t incur the 10% regional pricing premium. If you need data residency in a specific geography, use us-east5, us-central1, or europe-west1 — but verify your target Claude models are available in that region first, as not all models are available in all regions.

    Model Pinning for Teams

    If you’re deploying Claude Code to multiple team members, pin specific model versions rather than using aliases. Model aliases like “sonnet” resolve to the latest version, which may not be enabled in your Vertex AI project when Anthropic ships an update. Pinning prevents silent failures on update day:

    export ANTHROPIC_DEFAULT_SONNET_MODEL=claude-sonnet-4-6
    export ANTHROPIC_DEFAULT_HAIKU_MODEL=claude-haiku-4-5@20251001

    Common Error: 429 Resource Exhausted

    If you see 429 errors after setup, your project’s Vertex AI quota for Claude models needs to be increased. Go to Cloud Console > IAM & Admin > Quotas, filter by “anthropic,” and request an increase for the models you’re using. Approvals are typically fast for standard business accounts.

    Can I run Claude Code on Vertex AI for free?

    Yes if you have unused GCP credits. New Google Cloud accounts receive $300 in free credits. All GCP credits — startup programs, free trial, committed use discounts — apply to Claude usage through Vertex AI.

    Do I need an Anthropic API key to use Claude Code on Vertex AI?

    No. When configured for Vertex AI, Claude Code authenticates through your Google Cloud credentials (gcloud). No Anthropic API key is needed or used.

    Is Claude Code on Vertex AI slower than the direct Anthropic API?

    In practice, latency is comparable. The global endpoint routes dynamically and generally performs well. Regional endpoints may add slight latency depending on your geographic distance from the selected region.

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    We’ve deployed Claude on Vertex AI for content operations, internal tools, and automated publishing pipelines. If you’re an engineering team looking to integrate Claude into your GCP environment, we can help scope and build it.

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  • Claude on Vertex AI: Why Route Through GCP Instead of Direct API

    Claude on Vertex AI: Why Route Through GCP Instead of Direct API

    Last refreshed: May 15, 2026

    Model Accuracy Note — Updated May 2026

    Current flagship: Claude Opus 4.7 (claude-opus-4-7). Current models: Opus 4.7 · Sonnet 4.6 · Haiku 4.5. Claude Opus 4.7 (claude-opus-4-7) is the current flagship as of April 16, 2026. Where this article references Opus 4.6 or earlier models, those references are historical. See current model tracker →. See current model tracker →

    Claude AI · Tygart Media
    Bottom line: Routing Claude through Google Cloud’s Vertex AI makes sense if you’re already on GCP, need enterprise compliance controls, want billing consolidated under your cloud account, or want to run Claude inside a private VPC. For individual users and small teams, the direct Anthropic API is simpler.

    Anthropic offers two ways to access Claude programmatically: directly through the Anthropic API, or through Google Cloud’s Vertex AI. They run the same models with the same capabilities. The difference is infrastructure, billing, compliance, and control. Here’s when each makes sense — and why teams running production AI workloads on GCP increasingly choose Vertex.

    What You Actually Get Through Vertex AI

    When you access Claude through Vertex AI, the request routes through Google Cloud infrastructure rather than Anthropic’s own endpoints. You get access to every Claude model — Opus 4.6, Sonnet 4.6, Haiku 4.5 — with the same capabilities including the 1M token context window on Opus and Sonnet. Nothing is stripped down. The key differences are on the infrastructure and billing side, not the model side.

    Five Reasons to Route Through GCP Instead of Direct API

    1. Consolidated GCP billing

    If your organization already runs on Google Cloud, adding Claude through Vertex AI means all AI spending appears on a single GCP bill. No separate Anthropic invoice, no separate API key management system, no separate budget approval process. For enterprise finance teams, this is often the deciding factor — Claude becomes a line item on the existing cloud budget rather than a new vendor relationship.

    2. Use existing GCP credits

    Google Cloud offers $300 in free credits to new accounts, startup credits through various programs, and committed use discounts for larger organizations. All of these apply to Claude usage through Vertex AI. Teams with unused GCP credit can run substantial Claude workloads at no incremental cost. New GCP accounts can effectively run Claude Code for free until credits are exhausted.

    3. IAM and access control

    Vertex AI integrates with Google Cloud IAM, meaning you can control who in your organization can access Claude using the same permission system you use for every other GCP service. Roles, service accounts, audit logs — all standard GCP tooling applies. This eliminates the need for a separate API key distribution system and makes access revocation immediate and centralized.

    4. VPC Service Controls and private networking

    For organizations with strict data residency or network isolation requirements, Vertex AI supports VPC Service Controls that prevent Claude API calls from leaving your private network perimeter. Claude requests originate from inside your GCP VPC rather than from an internet-facing endpoint. This is the core of what some teams call a “Fortress Architecture” — running AI inference inside a secured cloud environment where data never traverses the public internet. For regulated industries (healthcare, finance, legal), this is often a compliance requirement, not a preference. See The Fortress Architecture: Why Regulated Industries Need Their Own Cloud for the full architecture breakdown.

    5. Regional data residency

    Vertex AI lets you pin Claude requests to specific GCP regions — US, EU, or specific regional endpoints. For organizations subject to GDPR or other data residency requirements, this ensures AI processing stays within the required geographic boundary. The Anthropic direct API does not offer equivalent regional controls.

    When the Direct Anthropic API Is Better

    Vertex AI adds setup overhead — you need a GCP project, Vertex AI enabled, model access requested in Model Garden, and IAM configured. For individual developers, startups, and teams that don’t already run on GCP, this overhead isn’t worth it. The direct Anthropic API is faster to set up (generate a key, start calling), has the best rate limits for getting started, and doesn’t require cloud infrastructure knowledge.

    Also: new Claude models appear in the direct API before they appear in Vertex AI’s Model Garden. If you need day-one access to new releases, direct is faster.

    Pricing Comparison

    Model Anthropic Direct Vertex AI (Global) Vertex AI (Regional)
    Claude Opus 4.7 input $5/M tokens $5/M tokens +10% premium
    Claude Sonnet 4.6 input $3/M tokens $3/M tokens +10% premium
    Claude Haiku 4.5 input $0.80/M tokens $0.80/M tokens +10% premium

    Global endpoint pricing matches Anthropic direct. Regional endpoints add a 10% premium for the data residency guarantee. If you don’t need regional pinning, use the global endpoint and pay identical rates.

    Is Claude on Vertex AI the same as the Anthropic API?

    Same models, same capabilities, different infrastructure. Vertex AI runs on Google Cloud with GCP billing, IAM, and VPC controls. The direct Anthropic API is simpler to set up but lacks GCP-native enterprise controls.

    Can I use GCP free credits for Claude on Vertex AI?

    Yes. New GCP accounts receive $300 in free credits. Startup programs and other Google Cloud credits all apply to Claude usage through Vertex AI. Teams with existing GCP credits can run Claude workloads at no incremental cost until credits are exhausted.

    Is Claude on Vertex AI more expensive than the direct API?

    At the global endpoint, pricing is identical to Anthropic direct. Regional endpoints (for data residency) add a 10% premium. If you don’t need regional pinning, the cost difference is zero.

  • Current Claude Model Version Tracker — June 2026

    Current Claude Model Version Tracker — June 2026

    Updated July 6, 2026

    Tracker update: Claude Sonnet 5 shipped June 30, 2026 and is now the default Sonnet, replacing Sonnet 4.6. As of July 6, 2026, Anthropic’s lineup is Claude Fable 5 (top tier above Opus; $10 in / $50 out per MTok; Mythos 5 is the limited-availability sibling), Claude Opus 4.8 ($5/$25), Claude Sonnet 5 (released June 30, 2026; now the default for Free and Pro; introductory $2/$10 per MTok through Aug 31, 2026, then $3/$15), and Claude Haiku 4.5 ($1/$5). Opus 4.7 and Sonnet 4.6 are now legacy. Full details: the Claude Fable 5 Complete Guide.

    Last refreshed: June 9, 2026

    Model Accuracy Note — Updated June 9, 2026

    Current flagship: Claude Opus 4.8 (claude-opus-4-8). Current models: Fable 5 (top tier) · Opus 4.8 · Sonnet 5 · Haiku 4.5. Claude Opus 4.6 referenced in this article has been superseded. See current model tracker →

    Claude AI · Tygart Media · Updated June 2026
    Latest models (updated June 2026): Claude Fable 5 (claude-fable-5) is the top tier, with Claude Opus 4.8 (claude-opus-4-8) and Claude Sonnet 4.6 (claude-sonnet-4-6) below it. Original Claude 4.0 models deprecated — retiring June 15, 2026.

    Anthropic releases model updates frequently and the naming can be confusing. This page tracks the current Claude model lineup, the exact API strings to use, what’s deprecated, and what’s coming next. Bookmark it and check back — it’s updated when Anthropic ships changes.

    Current Models (June 2026)

    Model API String Context Best For
    Claude Fable 5 claude-fable-5 1M Highest capability — frontier reasoning and agentic tasks
    Claude Opus 4.8 claude-opus-4-8 200K (1M beta) Complex reasoning, long-horizon agentic tasks (highest Opus tier)
    Claude Sonnet 4.6 claude-sonnet-4-6 200K (1M beta) Production default — near-Opus performance at lower cost
    Claude Haiku 4.5 claude-haiku-4-5-20251001 200K Speed, cost efficiency, high-volume tasks

    Deprecated Models (Action Required)

    Model API String Retirement Date Migrate To
    Claude Sonnet 4 (original) claude-sonnet-4-20250514 June 15, 2026 claude-sonnet-4-6
    Claude Opus 4 (original) claude-opus-4-20250514 June 15, 2026 claude-opus-4-8

    If you have 20250514 in any API calls or model strings in production code, you have until June 15 to update them. Search your codebase for that date string now.

    What Changed From 4.0 to 4.6

    The Claude 4.6 models (released February 2026) are meaningful upgrades over the original 4.0 release (May 2025). Key improvements in Sonnet 4.6: near-Opus-level performance on coding and document comprehension, dramatically improved computer use (navigating browsers, filling forms, operating software), better instruction-following with fewer errors, and the 1M token context window in beta. Opus 4.6 adds the same 1M context with additional improvements to long-horizon reasoning and multi-step agentic tasks.

    Model Naming: How It Works

    Anthropic uses a generation.version format. The “4” is the major generation (fourth architecture generation). The “.6” is a version increment within that generation — a meaningful capability update without a full architecture change. Haiku, Sonnet, and Opus are tiers within each generation: speed/cost, balanced, and maximum capability respectively. The date suffix in API strings (like 20250514) is the training cutoff snapshot used for that specific release.

    What’s Coming Next

    The next-generation model shipped in June 2026 as Claude Fable 5 (claude-fable-5), the new top tier above Opus 4.8, priced at $10 input / $50 output per MTok with a 1M token context window. The earlier “Fennec” codename speculation is resolved — Fable 5 is the released product. See Claude 5 Release Date: What We Know for the latest.

    Model Selection for API Developers

    For most production use cases in June 2026: use claude-sonnet-4-6 as your default. It handles the vast majority of tasks at better economics than Opus. Use claude-opus-4-8 for tasks that require maximum reasoning depth — complex multi-step analysis, difficult coding problems, long-horizon agentic runs. Use claude-haiku-4-5-20251001 for high-volume, latency-sensitive, or cost-constrained tasks where raw capability is less critical than speed.

    What is the latest Claude model right now?

    As of July 2026, the newest and most capable model is Claude Fable 5 (claude-fable-5). The current Opus-tier model is Claude Opus 4.8 (claude-opus-4-8), Claude Sonnet 5 (claude-sonnet-5) is the production default (released June 30, 2026, replacing Sonnet 4.6), and Claude Haiku 4.5 (claude-haiku-4-5-20251001) is the speed/cost tier.

    Is Claude Sonnet 4.6 better than Claude Opus 4?

    Yes, in most practical benchmarks. Claude Sonnet 4.6 outperforms the original Opus 4.0 on coding, document comprehension, and instruction-following — at a lower price point. This follows Anthropic’s consistent pattern of new Sonnet tiers exceeding prior Opus tiers.

    What Claude model string should I use in my API calls?

    Use claude-sonnet-4-6 for most tasks. Use claude-opus-4-8 for maximum capability. Use claude-haiku-4-5-20251001 for speed and volume. Avoid claude-sonnet-4-20250514 and claude-opus-4-20250514 — these retire June 15, 2026.



    Current Claude Models — May 2026

    Anthropic’s current production model lineup as of May 2026:

    Model API String Context Best For
    Claude Opus 4.8 claude-opus-4-8 200K tokens Complex reasoning, long-form analysis
    Claude Sonnet 4.6 claude-sonnet-4-6 200K tokens Everyday tasks, best balance of speed and quality
    Claude Haiku 4.5 claude-haiku-4-5-20251001 200K tokens High-volume, latency-sensitive tasks

    Deprecated as of May 2026: Claude 3 Opus, Claude 3 Sonnet, Claude 3 Haiku (Claude 3.5 Haiku remains available). See the full deprecation timeline.

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    The Claude Implementation Playbook is a dense 9-section PDF you can attach directly to any AI conversation — pricing tables, model API strings, routing logic, context engineering rules. Verified May 2026.

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    Frequently Asked Questions

    What is the current Claude model version in June 2026?

    The current Claude models as of June 2026 (verified from Anthropic’s official API docs): Claude Fable 5 (top tier, model ID: claude-fable-5), Claude Opus 4.8 (highest Opus tier, model ID: claude-opus-4-8), Claude Sonnet 5 (claude-sonnet-5, production default, released June 30, 2026), and Claude Haiku 4.5 (claude-haiku-4-5-20251001). Sonnet 4.6 is now legacy.

    What is Claude Opus 4.8?

    Claude Opus 4.8 is Anthropic’s most capable Opus-tier model as of June 2026 (Claude Fable 5 sits above it as the overall top tier). It offers the best performance for complex reasoning, long-horizon agentic coding, and high-autonomy work. API pricing is $5 input / $25 output per million tokens with a 1M token context window.

    What model does Claude Pro use?

    Claude Pro gives access to Claude Opus 4.8, Claude Sonnet 5, and Haiku 4.5, subject to per-session usage limits. For heavier usage, Claude Max 5x ($100/month) or Max 20x ($200/month) provide significantly more headroom.

    How do I know which Claude version I’m using?

    In claude.ai, the model selector appears when starting a new conversation. In the API, the model version is explicitly set in your API call parameters (e.g., claude-opus-4-8). The API always returns the exact model ID used in each response.

    Is Claude Opus 4.8 the same as claude-opus-4-8?

    Yes. Claude Opus 4.8 is the marketing name; claude-opus-4-8 is the API model ID. Both refer to the same model. Unlike earlier Claude versions, the 4.8 model ID has no date suffix — it is a pinned snapshot, not an evergreen alias.

    What happened to Claude Opus 4.7?

    Claude Opus 4.8 succeeded Claude Opus 4.7 as the top Opus-tier model (Claude Fable 5 is the overall flagship above Opus). Opus 4.7 remains available via API but Anthropic recommends Opus 4.8 for new deployments. Users currently on Opus 4.7 should migrate — see Anthropic’s migration guide at platform.claude.com.

    Get alerted when Claude pricing or limits change

    We track Anthropic’s models, pricing, and limits daily and send a short note when something changes that affects what you pay or build. Occasional, no spam.

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  • Claude Managed Agents Integrations: Complete List (Notion, Asana, Sentry, and More)

    Claude Managed Agents Integrations: Complete List (Notion, Asana, Sentry, and More)

    Last refreshed: May 15, 2026

    Claude AI · Tygart Media
    Current supported integrations (April 2026): Notion, Asana, Sentry, Rakuten, Intercom, Cloudflare, Confluence, Jira, Linear, PagerDuty, Stripe, and dozens more via the MCP ecosystem. Anthropic is actively expanding the list.

    Claude Managed Agents is Anthropic’s enterprise agentic service — Claude running as an autonomous agent connected to your tools, taking multi-step actions without a human in the loop for every decision. The integrations list is what most teams are researching before adopting it, and it’s not clearly documented in one place. Here’s the complete breakdown.

    What “Integration” Means in This Context

    When Anthropic says Claude Managed Agents supports an integration, they mean Claude can authenticate with that service, read data from it, take actions in it (create, update, complete tasks), and reason across multiple services in a single agentic run. This is different from a simple API connection — Claude is actively using the tool the way a human would, not just pulling data from it.

    Confirmed Integrations at Launch

    Integration What Claude Can Do
    Notion Read/write pages, update databases, synthesize across workspaces, create meeting notes, manage project trackers
    Asana Create and update tasks, move items between projects, mark completions, generate status reports
    Sentry Triage errors, assign issues, summarize error patterns, escalate to relevant team members
    Rakuten Process affiliate data, update campaign parameters, generate performance summaries
    Intercom Draft support responses, route tickets, escalate complex issues, update customer records
    Cloudflare Monitor security alerts, update firewall rules, generate traffic reports
    Confluence Create and update documentation, summarize meeting notes into wiki pages
    Jira Create tickets, update sprint boards, generate burndown summaries, escalate blockers
    Linear Manage engineering issues, update cycle progress, triage incoming bugs
    PagerDuty Respond to incidents, escalate alerts, create post-mortems
    Stripe Query transaction data, generate revenue summaries, flag anomalies
    GitHub Review PRs, create issues, summarize commit history, manage release notes

    The MCP Layer: Extending Beyond the Default List

    Beyond the out-of-the-box integrations, Claude Managed Agents supports any service that exposes a Model Context Protocol (MCP) server. MCP is the open standard Anthropic developed for connecting AI models to external tools. If your internal systems, proprietary databases, or less common SaaS tools have an MCP server, Claude can integrate with them through the same managed agent infrastructure — no custom code required on the Claude side.

    This is why the integration list is effectively unbounded: the default set covers the most common enterprise tools, and MCP handles everything else.

    How This Differs from Claude in Chat with MCP Connectors

    Using Claude Chat with MCP servers configured requires a human actively running the conversation. Claude Managed Agents runs autonomously — you define the objective and the integrations, and Claude executes multi-step workflows without a human prompting each step. The agent can read from Notion, check Sentry for errors, create a Jira ticket, update Asana, and send a summary to Intercom in a single autonomous run.

    Pricing Note

    Claude Managed Agents is an enterprise-tier offering priced per session and per hour of agent runtime. It’s not available on individual Claude plans. For current pricing, see Claude Managed Agents Pricing: Complete Cost Analysis.

    Does Claude Managed Agents work with Notion?

    Yes. Notion is one of the confirmed launch integrations. Claude can read pages, write and update databases, synthesize across workspaces, and manage project trackers autonomously.

    Can Claude Managed Agents connect to custom internal tools?

    Yes, through the MCP (Model Context Protocol) layer. Any internal tool or proprietary system that exposes an MCP server can be connected to Claude Managed Agents without requiring changes on the Claude side.

    Is Asana supported in Claude Managed Agents?

    Yes. Asana is a confirmed integration. Claude can create and update tasks, move items between projects, mark completions, and generate status reports autonomously within Asana.


  • How Claude Cowork Task Scheduling Works

    How Claude Cowork Task Scheduling Works

    Last refreshed: May 15, 2026

    Claude AI · Tygart Media
    How it works in plain terms: Cowork tasks are stored instruction sets that Claude executes on a schedule. You write the prompt once; Claude runs it at the scheduled time using whatever tools and MCP connections you have configured.

    Claude Cowork’s scheduling feature is one of the least-documented parts of the product, but it’s the most powerful. Understanding how it actually works — what triggers tasks, what Claude has access to when running them, and what the limitations are — changes how you design automation with it.

    How Cowork Tasks Are Stored

    Each Cowork task is a named, persistent instruction set saved locally in your Claude Desktop environment. The task contains: a name, a prompt (the full instruction Claude follows each run), a schedule, and optionally a working directory and a set of enabled tools. Tasks are stored in JSON format under your Documents folder at ~/Documents/Claude/Scheduled/ alongside a scheduled-tasks.json index file.

    What Triggers a Scheduled Task

    Tasks run on cron-style schedules configured when you create the task. Common schedules include daily at a specific time, weekly on specific days, or on-demand (manual trigger only). When the scheduled time arrives, Claude Desktop wakes the Cowork runner, loads the task prompt, and executes it with the configured tools and MCP connections active.

    Critical limitation: Claude Desktop must be running and your machine must be awake when the scheduled time fires. Cowork is not a cloud scheduler — it depends on the local process being live. If your machine is asleep or Claude Desktop is closed, the task is skipped for that run with no retry.

    What Claude Has Access to During a Task Run

    When a Cowork task runs, Claude has access to everything configured in your Claude Desktop environment at that moment: all active MCP servers (Notion, Gmail, Google Drive, etc.), the Cowork bash VM for executing scripts and filesystem operations, any skill files mounted in the VM, and the working directory specified in the task config. It does not have access to the interactive chat thread — the task runs in its own isolated context.

    Task Memory: What Carries Over Between Runs

    Nothing carries over automatically. Each task run is stateless — Claude starts fresh with only the task prompt as its context. If your task needs to know what happened last time (what was published, what changed, what errors occurred), you have to build that logging into the task itself. The standard pattern: at the end of each run, write a log entry to a Notion page or local file; at the start of the next run, read that log to pick up context.

    This is why well-designed Cowork tasks always end with a Notion write and start with a Notion read.

    How to Design a Reliable Cowork Task

    Tasks that work well have four components: a clear single objective per task (do one thing, do it well), explicit context loading at the start (read the log, check what already exists), a defined success condition Claude can verify, and a logging step at the end that captures what ran and any errors. Tasks that try to do too many things in one run, or that assume Claude will remember previous runs without explicit context, fail inconsistently.

    When to Move Tasks to GCP Instead

    Cowork scheduling works well for tasks that need to run during your working day when your machine is on. For anything that needs to run at 3 AM, run on a strict schedule with zero missed executions, or process large amounts of data that would exhaust the local VM disk — those belong on GCP Cloud Run or a Compute Engine cron job, not Cowork. The architectural principle: Cowork for interactive-adjacent automation, GCP for always-on production pipelines.

    How do I create a scheduled task in Cowork?

    Open Claude Desktop, navigate to the Cowork section, create a new task, write your prompt, and set the schedule. Tasks are saved locally and run when Claude Desktop is open at the scheduled time.

    Why did my Cowork task not run at the scheduled time?

    Most likely Claude Desktop was closed or your machine was asleep. Cowork tasks require Claude Desktop to be running. Tasks that miss their scheduled time are skipped — there is no retry or catch-up mechanism.

    Can Cowork tasks run while I am using Claude Chat?

    Yes. Cowork tasks run in a separate context from the chat interface. Active Cowork task runs do not interrupt or share context with your current chat sessions.