🔄 Run 10 Coding Agents on 1 App

Hey folks,

Anthropic recently launched a legal plugin for Claude Cowork and by Tuesday the software sector had lost $285 billion in market value. Thomson Reuters dropped 18% in a single session, the biggest one-day drop since April. The plugin automates document review, contract analysis, and legal research. Wall Street's read is if AI can replace $500/hour legal work, every software company selling to knowledge workers is now on notice.

Today in AI:
→ OpenAI's Codex app turns your Mac into an agent command center
→ Apple added AI agents to Xcode that run builds and tests
→ Prompt of the Day:

Let's dive in..

🖥️ OpenAI's Codex Turns Your Mac Into an Agent Center

What if you could hand off ten coding tasks at once and come back to finished tasks?

That's the pitch behind OpenAI's new Codex desktop app for macOS, which launched this week. It's a workspace where you spin up multiple AI agents, each working on a separate task in its own thread, and they all run in parallel without stepping on each other's code. The features that matter:

• Multi-agent workspace: Each agent gets its own thread and Git worktree. You can have one agent fixing bugs, another writing tests, and a third refactoring a module, all on the same repo with no merge conflicts

• Skills: Pre-built capabilities you install with a click. OpenAI shipped a library that includes Figma context, Linear project management, Vercel deploys, and PDF generation. Stripe built their own within hours of launch

• Automations: Schedule agents to run on a timer. OpenAI uses this internally for daily issue triage, CI failure summaries, and release briefs. Set it up once, results land in a review queue every morning

• 30-minute autonomy: Agents can work independently for up to 30 minutes before checking back in. That's enough time to complete a full feature branch

The bigger deal is the workflow change. Instead of sitting in a chat window watching an AI write code line by line, you assign tasks like a manager delegating to a team. The Codex app syncs context between the CLI, VS Code extension, and desktop app, so you can start a task in your terminal and pick it up on the desktop.

For your team: If your developers are still using AI coding tools one task at a time, this is worth a pilot. The multi-agent approach means your team's AI capacity scales with the number of tasks, not the number of people watching the screen.

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🍎 Apple Just Added AI Agents to Xcode

Apple shipped Xcode 26.3 with built-in support for Claude Agent and OpenAI Codex. Not autocomplete. Not chat in a sidebar. Full agentic coding where AI can create files, run builds, execute tests, and iterate on fixes autonomously. Here's what the agents can actually do inside Xcode:

• Break down tasks: Describe what you want to build. The agent figures out the steps

• Navigate your project: Agents can explore file structures, read documentation, and understand your architecture before writing code

• Build and test: Builds directly, catches errors, and fixes them in a loop

• Verify visually: Agents take screenshots through Xcode Previews to check if UI looks right

• Access Apple docs: Full Apple developer documentation has been optimized specifically for AI agents to read

The bigger play: Xcode 26.3 also supports Model Context Protocol, the open standard that's becoming the USB-C of AI tools. That means any MCP-compatible agent can plug into Xcode, not just Claude and Codex. Apple's VP of Developer Relations, Susan Prescott, called it "supercharging productivity and creativity."

For your team: If you're building iOS or macOS apps, this changes the workflow. Agents that can run builds and tests autonomously aren't just writing code faster. They're catching bugs before you even look at the PR.

🎯 Prompt Of The Day

Copy this. Run it quarterly on your top 3 competitors. Early warning system for strategic shifts.

"Conduct deep competitive intelligence on [COMPETITOR NAME]:

COMPANY OVERVIEW:
- Founding story and key milestones
- Leadership team (backgrounds, previous companies)
- Funding history (rounds, investors, valuations, burn rate estimates)
- Employee count and growth trajectory (check LinkedIn headcount)
- Office locations and expansion patterns

PRODUCT DEEP-DIVE:
- Complete product catalog with descriptions
- Pricing tiers (current + historical changes)
- Feature comparison vs top 3 alternatives
- Technology stack (from job postings, tech blogs, BuiltWith)
- Recent product launches (last 12 months)
- Roadmap clues (from: job postings, conference talks, patent filings, customer surveys)

MARKET POSITIONING:
- Target customer (size, industry, characteristics, job titles)
- Ideal Customer Profile (ICP) based on case studies
- Messaging and positioning (analyze website, ads, content)
- Brand voice and personality
- Key differentiators they claim

GO-TO-MARKET STRATEGY:
- Marketing channels (paid, organic, partnerships)
- Content strategy (blog topics, frequency, engagement)
- Sales approach (inbound vs outbound, PLG vs sales-led)
- Partnership ecosystem (integrations, resellers, tech partners)
- Event presence (conferences, webinars, sponsorships)

CUSTOMER INTELLIGENCE:
- Review analysis (G2, Capterra, TrustPilot - what do users love/hate?)
- Common complaints (from Reddit, Twitter, support forums)
- Feature requests and gaps (from public roadmap, user forums)
- Churn signals (Glassdoor reviews, customer testimonials that stopped)

STRATEGIC VULNERABILITIES:
- What are they bad at? (based on reviews, hiring patterns)
- What markets are they ignoring?
- Where are they overextended?
- Technology debt or legacy issues
- Pricing weaknesses or gaps

THREAT ASSESSMENT:
- How aggressive are they in OUR market?
- What would it take to compete effectively?
- What could they do that would hurt us most?
- Early warning signals to monitor

Use: Recent sources only (last 18 months). Prioritize primary sources (their blog, official announcements, verified reviews). Flag speculation vs confirmed facts. Include URLs for verification."

🐝 AI Buzz Bits

🔄 Gemini is testing ChatGPT chat imports. Export your conversations from ChatGPT, Claude, or Copilot, upload to Gemini, and continue those chats with full context attached. Google's play to make switching easier. The catch: imported chats become part of your Gemini activity data and can be used to train Google's models.

🏈 Anthropic trolled OpenAI with a Super Bowl ad. The 60-second pregame spot opens with words like "BETRAYAL" and "DECEPTION" before showing AI assistants pivoting mid-response to pitch products. Tagline: "Ads are coming to AI. But not to Claude."

🏎️ Claude is now Williams F1's "Official Thinking Partner." Anthropic's first sports sponsorship puts Claude branding on cars, drivers, and team kits starting with the 2026 car reveal. Engineers use Claude for race strategy, car development, and operations.

🛠️ Tool Spotlight

1. Amp — Sourcegraph's coding agent that picks the best AI model for each task automatically. Uses Claude Opus, Gemini 3 Pro, and GPT-5.1 under the hood. No model-switching on your end.

2. Lightfern — AI writing tool for email that predicts what you're trying to say and drafts it before you finish typing. Works inside Gmail and Outlook.

3. Goose — Block's open-source AI agent that runs entirely on your machine. Self-improving and it builds its own new skills.

4. ChurnTools — Curated directory of customer retention and churn reduction tools. Free resource hub with risk assessments and guides.

For a full list of 1500+ AI tools, visit our Supertool Directory