Claude is still way ahead of Grok with mobile tools. I find dispatch and remote control Claude Code so useful that I can’t imagine using Grok as a daily until they have similar tools. Grok 4.5 has closed massive model gaps that existed prior to its release, but they still lag way behind when it comes to app tools/desktop interface.

# Claude Code Features and Practical Usage 🚀 Just mention "@/claude" in a PR or issue and watch fixes, features, and reviews happen automatically. Claude Code becomes an AI teammate that works inside your CI. 📌 Title and Feature URL Title: GitHub Actions URL: 📝 Overview Claude Code GitHub Actions integrates Claude Code into your GitHub workflow. Mention "@/claude" on any PR or issue and Claude analyzes your code, creates pull requests, implements features, or fixes bugs. Built on the Claude Agent SDK, it is ideal for automating routine engineering tasks. 🔧 How It Works - It auto-detects whether to run in interactive mode (responding to @/claude mentions) or automation mode (running immediately with a prompt) based on your config. - It respects the repository's CLAUDE.md, following your project standards and existing code patterns. - Code runs on GitHub-hosted runners and uses Sonnet by default (Opus 4.8 can be selected). - Beyond the direct Claude API, it supports Amazon Bedrock and Google Vertex AI. 🛠 Practical Usage - The easiest setup is running "/install-github-app" inside claude in your terminal; it guides you through the GitHub app and secrets (you need repo admin rights). - For manual setup: install the Claude GitHub app ( add ANTHROPIC_API_KEY as a repository secret, and copy examples/claude.yml into .github/workflows/. - Use the action "anthropics/claude-code-action@v1". Pass instructions via "prompt" and CLI arguments via "claude_args". - claude_args examples: --max-turns 5 / --model claude-sonnet-4-6 / --mcp-config /path/to/config.json - Comment examples: "@/claude implement this feature based on the issue description", "@/claude fix the TypeError in the user dashboard component". 🎯 Use Cases - Mention on an issue to auto-create a PR that turns requirements into working code. - Request a standard review on a PR: "@/claude review this for security issues". - Use a schedule (cron) trigger to auto-generate a daily summary of yesterday's commits and open issues. - Wire in the code-review plugin to run its skill automatically on every PR update. ⚠️ Caveats - Never commit API keys directly to the repo; always reference GitHub Secrets (secrets.ANTHROPIC_API_KEY). - Costs accrue both as GitHub Actions minutes and API tokens. Use --max-turns and timeouts to prevent runaway jobs. - If Claude doesn't respond, confirm the comment uses "@/claude" (not "/claude") and that the app and secrets are configured. - v1.0 has breaking changes from beta: remove mode, change direct_prompt to prompt, and move CLI options into claude_args. #ClaudeCode# #CICD#

- Claude = coding. ($20/mo) - Supabase = backend. (Free) - Vercel = deploying. (Free) - Namecheap = domain. ($12/yr) - Stripe = payments. (2.9%/transaction) - GitHub = version control. (Free) - Resend = emails. (Free) - = AI job Agent （Free） - Clerk = auth. (Free) - Cloudflare = DNS. (Free) - PostHog = analytics. (Free) - Sentry = error tracking. (Free) - Upstash = Redis. (Free) - Pinecone = vector DB. (Free) Total monthly cost to run a startup: ~$20 There has never been a cheaper time to build.

Claude Code is the hegemony. Across the enterprises we work with, we see Claude Code dominating 80% of usage and spending. *But* I think this position is tenuous: - Enterprises often lag the frontier by 6 months. Claude Code's big moment was 6 months ago, so we'll see peak enterprise adoption now through eoy - OSS harnesses give enterprises more visibility, control, and choice across providers and models - The only defensibility for a harness is developer adoption, and individual developers are increasingly adopting codex, opencode, etc. Strong piece from @LauraBratton5 on this :

Claude Opus 5 is now available in Perplexity and Perplexity Computer. We evaluated it against six other models on WANDR. It outperformed all but Fable 5, while being 57% cheaper.

Claude Opus 5's effort setting spans a wide range of token usage-performance tradeoffs. On GDPval-AA v2, effort levels span 407 Elo points, with output token usage ranging around 8x from low to max effort. Like with GPT-5.6 Sol, this means Opus 5 can use either far fewer or far more tokens to complete the evaluation than models from other labs, depending on effort settings

Claude Opus 5 is narrowly the most intelligent model on the Artificial Analysis Intelligence Index, offering comparable intelligence to Fable 5 at 26% lower Cost per Task We supported @AnthropicAI to evaluate Claude Opus 5 ahead of release: it sets the highest GDPval-AA v2 and AA-Briefcase scores so far. Opus 5 (max) scores 61 on the Artificial Analysis Intelligence Index, effectively tied with Claude Fable 5 (max, 60), and ahead of GPT-5.6 Sol (max, 59), Kimi K3 (57), and Claude Opus 4.8 (max, 56) Key takeaways: ➤ New leader in agentic knowledge work: Claude Opus 5 (max) scores 1861 Elo on GDPval-AA v2, >100 points ahead of Claude Fable 5 and GPT-5.6 Sol (max). On AA-Briefcase, our proprietary agentic knowledge work benchmark, it scores 1720 Elo, +146 ahead of Fable 5. These benchmarks test the ability of models to produce accurate and well-presented professional outputs using our open source reference agent harness, Stirrup ➤ Joint first place on the Coding Agent Index: Claude Opus 5 (xhigh) with Claude Code leads the Artificial Analysis Coding Index, including the highest score on SWE-Atlas-QnA ➤ Frontier intelligence with reduced cost: Claude Opus 5 (max) costs $2.03 on average per Intelligence Index task, below Claude Fable 5 (with fallback) at $2.75, but still above Claude Opus 4.8 (max) at $1.80 and Claude Sonnet 5 (max) at $1.53. However, at high and xhigh reasoning efforts Opus 5 can outperform both Opus 4.8 and Claude Sonnet 5 at a lower cost per task ➤ Frontier agentic terminal use: 89% on Terminal-Bench v2.1 at max effort, roughly in line with the leader, GPT-5.6 Sol (xhigh) ➤ Outperformance on scientific reasoning: Along with leading agentic performance, Claude Opus 5 scores 53% on Humanity’s Last Exam in line with Fable 5; on CritPt, a frontier physics evaluation developed by Argonne and UIUC researchers, it also matches Fable 5 but sits behind GPT-5.6 Sol, GPT-5.5 Pro, and GPT-5.6 Terra ➤ Factual knowledge still lags Fable 5: As expected from the models’ size classes, Opus 5 still has lower factual knowledge on AA-Omniscience than Fable 5. It improves +7 points on AA-Omniscience Accuracy over Opus 4.8, but answers more often when uncertain - its hallucination rate rises +14 points to 50% ➤ Improving efficiency, but only on the Intelligence vs. Cost per Task Pareto frontier at high Intelligence levels: Opus 5 outperforms Fable 5 at lower cost, but at lower effort levels it sits just behind the GPT-5.6 family on the Intelligence vs. Cost per Task frontier Other model details: ➤ Context window: 1 million tokens (equivalent to Opus 4.8) ➤ Pricing: As with recent Opus launches, tokens cost $5/$25 per million tokens of input/output; cache pricing remains at a 25% premium for cache writes ($6.25 per million tokens) with 5-minute time to live, and 90% discount for cache hits ($0.50 per million tokens) ➤ Five effort settings (low, medium, high, xhigh, max), and support for server-side fallback as with Fable 5. Intelligence Index evaluations were run with Opus 4.8 fallback enabled