I’ve always believed in diversification. Don’t marry a single tool. Don’t build your entire workflow around one company’s product. Keep your options open, because today’s darling is tomorrow’s deprecation notice.
I still believe that. And this quarter, Anthropic proved exactly why—in both directions.
They shipped 120+ features in 90 days. Two flagship models. Computer use. Managed agents. A CLI. Connectors to 50+ workplace tools. The most aggressive product execution any AI company has shown. While OpenAI ships quarterly and Google on a similar cadence, Anthropic has been shipping weekly. Sometimes daily.
And then, on April 4, they cut off OpenClaw—the largest open-source AI agent project on GitHub—from using Claude subscriptions. Nine days later, OpenClaw announced they’d moved to GPT-5.4. “Anthropic cut us off. GPT-5.4 got better. We moved on.”
So now you dependent on OpenAI? 🫠 https://t.co/2jnzOlHXch
— Pini (@PiniShv) April 13, 2026
I don’t like putting all my eggs in one basket. But when one basket is riding a wave this big—and simultaneously proving why you shouldn’t trust any single basket—you need to understand what’s happening.
The numbers that matter#
In 90 days, Anthropic released:
- 40+ Claude Code updates
- 15+ Cowork updates
- 20+ API changes
- 2 new models (Opus 4.6 and Sonnet 4.6)
- Computer use, Dispatch, Connectors, Channels, Remote Control, and a Plugin Marketplace
Their internal team ships 60–100 releases per day. Anthropic engineers now use Claude for roughly 60% of their own work, up from 28% a year ago, reporting ~50% productivity gains. Claude Cowork was built with Claude Code in 10 days.
That last part is worth sitting with. They used their own tool to build a new product in less than two weeks. The compounding flywheel isn’t theoretical anymore. It’s shipping.
On the business side: $380 billion valuation after a $30B Series G in February. Revenue run-rate at $14 billion, growing 10x annually. Over 500 customers spending $1M+ per year. Eight of the Fortune 10 are Claude customers.
This isn’t a startup experimenting. This is a company executing at a pace that’s forcing the rest of the industry to react.
What actually moved the needle#
I’m not going to do a tier list—you can find those elsewhere. What I want to do is break down the releases that change how developers work, not just what sounds impressive on a changelog.
The model leap: Opus 4.6 and Sonnet 4.6#
Opus 4.6 dropped February 5 with serious specs: 1 million token context window, 128K max output tokens (doubled from 64K), full adaptive thinking support, 80.9% on GPQA Diamond, 80.8% on SWE-bench verified. The adaptive thinking shift is important—the model now decides how deeply to reason per turn rather than consuming a fixed budget, which makes it more efficient for mixed workloads where some turns need deep reasoning and others don’t.
Sonnet 4.6 followed on February 17, becoming the default for Free and Pro plans. Near-Opus performance at 5x lower cost ($3/M input, $15/M output), 79.6% on SWE-bench. This is the model that matters most for daily use. If Opus is for the hard problems, Sonnet is for everything else—and “everything else” is 90% of the work.
The compaction API (beta, launched alongside Opus) deserves attention too. Server-side context summarization for effectively infinite conversations. If you’ve been building agents that run into context limits during long sessions, this is the fix you’ve been writing workarounds for.
Computer use + Dispatch: AI that does things#
I wrote about this when it shipped in late March. Claude can now control your Mac—open apps, navigate browsers, fill spreadsheets, submit PRs. Pair it with Dispatch and you assign tasks from your phone while Claude works on your desktop.
The technical model: Claude reaches for the most precise tool first. Calendar request? Google Calendar connector. Slack message? Slack integration. No connector available? It falls back to screen-based control—mouse, keyboard, browser. The permission model is explicit: Claude asks before touching a new application, and Anthropic scans model activations during computer use to detect adversarial prompt injection.
Mac only. Research preview. It will be unreliable for complex workflows. But the jump from “AI that talks about doing things” to “AI that does things” is real. The security implications are the part that keeps me up at night—prompt injection against a computer-controlling agent is a fundamentally different threat than prompt injection against a chat model.
Claude Code: from assistant to development platform#
Claude Code had the densest quarter of any product line. The headline features:
Remote Control (Feb 24): Supervise Claude Code sessions from your phone via claude.ai/code. Approve or reject changes, monitor long-running tasks without staying at your desk. This changes the workflow from “sit and watch” to “check in when it matters.”
Hooks: Deterministic actions that fire at lifecycle points—session start/end, file changes, tool use. These run 100% of the time, unlike advisory instructions that the model might ignore. This is the automation primitive that makes Claude Code composable with your existing tooling.
Subagents and /simplify: Parallel workers with clean context windows. /simplify distributes agents across changed files for code review, checking for reuse and quality. /batch handles large migration tasks across multiple files. This is multi-agent execution inside a coding tool—the same architectural direction Cursor 2.0 is taking with worktree-based parallelism.
128K output tokens (up from 16K default, 64K max): Quietly massive for code generation. Combined with the 1M token context window, Claude Code can now reason about entire mid-sized production codebases and generate substantial implementations in a single turn.
This isn’t a coding assistant anymore. It’s a development platform with an agent architecture. The Plugin Marketplace, scheduled tasks, voice mode, and MCP elicitation are all infrastructure for a tool that’s meant to run alongside you, not just respond when prompted.
Connectors: the quiet game-changer#
Connectors might be the most strategically important release of the quarter. Claude now integrates bidirectionally with Gmail, Slack, Notion, Figma, Asana, Google Drive, and 50+ other tools.
Bidirectional. Not just “read your Slack messages.” Claude can modify content in connected applications. That’s the difference between a search engine and a coworker. It’s the same logic behind MCP—give the AI access to your real context—but packaged as a consumer-friendly feature with zero setup friction.
The strategic angle: every connector is a switching cost. Once Claude is wired into your Slack, Gmail, and Notion, moving to a different AI provider means rewiring all of those integrations. Anthropic understands this. The convenience is real, and so is the lock-in.
Managed Agents and the platform play#
April 7–9 brought the most architecturally significant releases:
- Managed Agents (public beta): A fully managed framework for running Claude as an autonomous agent. Secure sandboxing, built-in tools, SSE streaming. Create agents, configure containers, run sessions through the API.
- Advisor Tool (public beta): Pairs a fast executor model with a higher-intelligence advisor for strategic mid-generation guidance. A senior engineer reviewing the junior’s work, but as an API parameter.
antCLI: Command-line client for the API with native Claude Code integration and YAML-based resource versioning.
Managed Agents is the one to watch. Until now, building production agent systems meant stitching together your own sandboxing, tool management, and execution infrastructure. Anthropic just said “we’ll handle that.” That’s a platform play aimed directly at the middleware layer that startups were building. It’s also the kind of move that makes you more dependent on Anthropic’s infrastructure, not less.
The OpenClaw situation#
And this is where the story gets uncomfortable.
On April 4, Anthropic blocked Claude subscription access for third-party agentic tools, starting with OpenClaw—the open-source AI agent gateway with over 247K GitHub stars. Users on Pro and Max plans can no longer route their subscription through OpenClaw. They must now use pay-as-you-go “extra usage” billing or direct API access.
Boris Cherny, Anthropic’s Head of Claude Code, explained that “subscriptions weren’t built for the usage patterns of these third-party tools.” The technical argument has merit: OpenClaw achieves ~10% cache hit rates compared to Claude Code’s much higher rates, meaning a single $200/month Max subscriber running OpenClaw continuously could consume $1,000–$5,000 in API-equivalent compute. The economics don’t work at all-you-can-eat pricing.
But the optics are terrible. Anthropic shipped Cowork—which does much of what OpenClaw does—and then cut off the open-source competition. Peter Steinberger, OpenClaw’s creator, characterized it as copying features from the open-source project and then locking out the competition. Whether that’s fair or not, it’s the perception.
OpenClaw’s response was swift. Version 2026.4.5 shipped with GPT-5.4 as the recommended default. “Anthropic cut us off. GPT-5.4 got better. We moved on.” They didn’t just switch models—they built new features around GPT-5.4’s native computer use capabilities. One week to migrate an entire project’s recommended provider.
This isn’t just a drama story. It’s a technical lesson about platform dependency:
If you build on a provider’s subscription model, you’re borrowing capacity they can revoke. OpenClaw users discovered overnight that their $200/month subscription wasn’t a contract—it was a courtesy. API access is still available, but at 5–25x the effective cost for heavy agentic workloads.
The switching cost for model providers is lower than we think. OpenClaw migrated to GPT-5.4 in a week. User testing shows comparable performance after prompt tuning. The model layer is commoditizing faster than any single provider wants to admit. The lock-in is in the tooling, the connectors, the workflow—not the model itself.
Open-source doesn’t protect you from upstream decisions. OpenClaw is MIT licensed. 247K stars. Massive community. None of that mattered when Anthropic decided the economics didn’t work. Your code is open, but your dependency on a closed API is still a single point of failure.
This is exactly why I’ve always maintained a multi-provider workflow. And it’s exactly why Anthropic’s execution makes that stance so conflicted—the tools are genuinely excellent, and using them means accepting the platform risk.
The compounding flywheel (and why it’s hard to ignore)#
The features are impressive individually. What actually matters is the pace.
Anthropic released a major Claude update roughly every two weeks in 2026. Agent Teams and Opus 4.6 shipped the same week. Code Review landed on a Monday, and by Friday they’d added 1M context GA and four more Claude Code features.
This isn’t speed for speed’s sake. It’s compounding. Each feature makes the next one faster to build, because the team building them uses the tools they’re shipping. That flywheel is the real competitive advantage—not any individual model or feature.
The developer experience data reflects this. Claude Code works first try 91% of the time on feature generation, versus 78% for GPT-5 and 65% for Gemini 2.0.
But speed has costs. The Claude Code source leak happened during this sprint—a packaging error that shipped internal source code. When you’re publishing 60–100 internal releases daily, the boring parts of the pipeline need to be bulletproof. They’re clearly not yet.
And context fragmentation remains unsolved. For all 120+ features shipped, Claude still loses memory across conversations. You can’t hand off a complex multi-day project between sessions without significant re-prompting. The compaction API helps for single long conversations, but the cross-session problem persists.
The basket question#
Back to my eggs.
I use Cursor. I use Claude. I use ChatGPT when it’s better for the task. I keep my eye on Gemini’s 2M context window, on GitHub Copilot’s agent mode, on what open-source alternatives like OpenClaw are doing—especially now that they’ve demonstrated you can switch providers in a week.
I’m not going all-in on any single provider. After the OpenClaw situation, I’m more certain of that than ever.
But I’d be dishonest if I didn’t acknowledge what’s happening. Anthropic in Q1 2026 didn’t just ship features. They demonstrated a development velocity that no competitor has matched. They’re eating their own cooking and the compounding is visible. They went from the company behind “the other chatbot” to the company that developers talk about in the same breath as their core infrastructure.
The guys at Anthropic are on the wave. And the OpenClaw story is a reminder that waves carry things—they don’t let you steer.
The question for developers isn’t whether to use Claude. It’s how to use the best tools available without becoming dependent on any one of them. Build your workflows so the model layer is swappable. Keep your context portable. Treat every provider’s pricing model as temporary. And pay close attention to what Anthropic is building—because right now, they’re building faster than anyone else.
Diversification doesn’t mean ignoring the best tools available. It means using them without letting them own you.
What’s your setup? All-in on Claude, spreading your bets, or actively building provider-agnostic workflows? Find me on X, Telegram, or LinkedIn.