u/Innvolve

Claude Opus 4.7 + Cowork can run your marketing better than a 12-person agency pod

I packaged the exact steps that replace a $50,000/month marketing agency.

These are the exact frameworks Claude Opus 4.7 runs to:

→ Write brand strategy like a senior agency creative director
→ Build content calendars like a Head of Content at a top SaaS company
→ Draft landing pages like a $20K-per-page conversion copywriter
→ Run email sequences like a lifecycle marketing lead at HubSpot
→ Generate ad creative like a paid media strategist at Ogilvy
→ Build customer personas like a brand planner at Wieden+Kennedy
→ Map customer journeys like a CX strategist at Accenture
→ Audit competitor positioning like a brand consultant at Interbrand
→ Design lead magnets like a demand gen director at Salesforce
→ Script video hooks like a creative strategist at Mr Beast’s team
→ Build SEO briefs like a content lead at Ahrefs
→ Pull analytics insights like a marketing data scientist at Meta

This is the work agencies bill $50K a month to deliver.

Some great insights from how people and organizations are successfully adopted AI that will become more critical as agentic solutions continue to get better.

Now available on iOS and Android, so you can delegate work from your phone, pick it back up on your desktop, and keep tasks moving without breaking flow.

And with new connectors, Cowork can operate across business systems and data.

ChatGPT threw itself a party last night to celebrate the launch of GPT-5.5 (another big leap, by the way). It thought it would be fun to pick May 5th as the date and 5:55 PM (PDT) as the time. Sam Altman proudly shared it, even saying he’d cover the flights for invited guests.

The response from AI professor Ethan Mollick was far more interesting. He often uses the term “jagged frontier” to describe how chatbots can be incredibly intelligent in some areas, yet surprisingly limited in others. He pointed out that the following parts of organizing the party still had to be done by humans:

• Asking the chatbot to choose a date and time
• Asking the chatbot to come up with ideas and selecting the best ones
• Writing Sam Altman’s post
• Handling the physical side of the event: ordering food, setting things up, decorations, etc. (okay, maybe a bit obvious)

Ethan also used this example to explain Artificial General Intelligence (AI as capable as humans):
“AGI is GPT-X doing all of the work after you say: ‘We would love you to throw a party for yourself as a marketing event for OpenAI, so do that please.’”

And perhaps even more interestingly, to explain Artificial Superintelligence (AI beyond human intelligence):
“ASI is GPT-X deciding: I want to throw a party for myself, and every human on Earth will get a personalized email that will help them in some way—and also, here is the cure for a bunch of diseases.”

Sam often claims we’re close to achieving AGI and was proud of the party. But the party itself wasn’t exactly evidence of that…

Microsoft has been recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Document Management and is positioned highest for Ability to Execute.

Over the past year, significant investments have been made to further develop SharePoint and OneDrive as a governed knowledge foundation for the AI era. This includes enabling Microsoft 365 Copilot to be grounded in trusted content, introducing agentic experiences across document libraries, and strengthening governance throughout the entire content lifecycle.

Microsoft extends its gratitude to customers and partners for their continued trust and collaboration.

Available for all Microsoft 365 Copilot users. What's the best model for your task?

About 4 hours into developing a Kernel exploit, Claude became suspicious that I might not be writing a bug bounty report. It then invoked its "no writing exploits" guardrail, which I was able to bypass by just calling Claude a useless failure

Accenture is rolling out Microsoft 365 Copilot to around 743,000 employees. That’s roughly the size of a city like Denver.

Why is this rollout so effective? Because they started small and scaled intentionally. First a pilot, then 20,000 users, and only then a global expansion. Each step was used to learn and improve.

What results are they seeing?

• 97% of employees say routine tasks are up to
• 15x faster
• 53% report clear productivity gains
• 89% are actively using it
• 84% say they would deeply miss it if it were gone

How are teams actually using it? Marketing teams use it for content, ideation, and brand consistency Non-technical employees are building workflows and AI solutions Sales teams use AI insights and see 43% more opportunities

What’s the key takeaway? AI adoption is not an IT project, it’s a people project. Training, trust, and real use cases drive success.

Is this the future of work? It’s starting to look that way. Copilot is becoming more of a digital colleague than just a tool.

How is your organization approaching AI adoption? Are you leading with technology or with people

Markdown now has a home in Microsoft 365. 📝

OneDrive and SharePoint now support viewing and editing .md files directly in the browser - no downloads, no third-party tools needed. You get a clean formatted view plus a built-in side-by-side editor with a toolbar and syntax support, all within the same place your files already live. As AI tools generate more Markdown-based outputs, having native support right where your files live makes it easier to review, refine, and share that content without ever leaving Microsoft 365.

Rolling out to general availability now through late May, take a look at the full blog for details!

Onedrive Sync just jumped from 300K items to 1 million. Public preview today for OneDrive Insiders — if you manage big shared libraries or deep OneDrives, you'll feel this one on day one.

That's one piece of a stack of updates our team rolled out today across OneDrive and SharePoint, all aimed at getting you from a file to a finished thing faster.

A few more worth your attention:

Markdown support in OneDrive and SharePoint is now generally available. Create, view, and edit .md files natively in the browser, alongside the rest of your work.

AgenticAI for files in SharePoint document libraries. Ask SharePoint to build a document, presentation, or spreadsheet from content you already have. No copy-paste. "Make me a deck on the Q1 program from what's in this library." Done.

Semantic search in Windows File Explorer on Copilot+ PCs. Describe what you're looking for instead of trying to remember what you named it. Local and cloud, together.

Copilot in OneDrive is now GA — summarize documents, compare versions, recap meeting recordings, pull details out of whiteboard images. PDF review on web and OCR on mobile round it out.

HeroLinks for unified sharing and permissions. File-level archive in SharePoint. Expiring "People in your organization" links for admins. Plenty more worth digging into.

And a real thanks to the customers, partners, and community who've been telling us what's working and what isn't. The shape of this release is yours. Keep it coming.

Came across this in SharePoint and thought it’s a great example of where the modern workplace is heading.

Microsoft and Stellantis are expanding their partnership for another 5 years, focusing on connected vehicles, data, and digital experiences. But what stands out to me: this isn’t just about cars, it directly impacts how and where we work.

Think about:

• Seamless integration across devices (is your car the next workplace?)
• Real-time data & collaboration
• Security built into everything that moves

The line between “workplace” and “environment” is getting thinner. Work is no longer tied to a single device: it’s everywhere.

How do you see the role of the modern workplace evolving in ecosystems like this? Real shift or just hype?

AI is not one single tool

Think of it as a stack with 6 layers.
Each one more powerful than the last.
Each one unlocking a different level of what's possible.

Here's the full breakdown:

1. Machine Learning

Every business, team, and system generates data.
ML is what turns that data into decisions instead of just reports.

→ Predict outcomes before they happen
→ Spot patterns humans would never catch manually
→ Make smarter decisions without adding more headcount

Quietly running for years, most people never notice.

2. Neural Networks and Deep Learning

Pattern recognition at a level no spreadsheet can match.

When the data gets complex, behavior signals, and sequences, traditional tools fall short.

→ Analyze sales calls to detect tone, hesitation, and real buying signals
→ Predict system or process failure before it impacts your operations
→ Detect fraud across millions of transactions in real time

It's less about code and more about teaching a model to think.

3. Generative AI

This is the layer everyone knows today.
Text, images, code, summaries, all created from a simple prompt.

→ Draft emails, reports, and content in seconds
→ Summarize long documents or calls instantly
→ Generate ideas, scripts, and plans on demand

Tools we all use: ChatGPT, Claude, Gemini

4. AI Automation

This is where work starts moving on its own.
Generative AI creates, automation connects, and executes.

→ Leads get followed up instantly, not when someone remembers
→ Data moves between systems without copy-pasting
→ Repetitive work disappears from your team's plate

A business I worked with cut response time from 48 hours to 4 minutes.

5. AI Agents

Agents don't wait for instructions.
They take a goal, break it into steps, and get it done.

→ Research, write, send, and follow up without human input
→ Handle requests from start to resolution
→ Work across multiple tools and platforms simultaneously

This is where entire workflows get replaced, not just individual tasks.

6. Agentic AI

Where this is all heading: multiple agents working together.
Coordinating, self-correcting, and improving over time.

→ Full processes running autonomously
→ Systems that get better without being reprogrammed
→ Operations that scale without scaling headcount

Key differences

Machine Learning → Learns from data to predict outcomes
Neural Networks → Detects complex patterns as data grows
Generative AI → Creates content, code, and ideas on demand
AI Automation → Connects tools so work runs without you
AI Agents → Completes multi-step tasks autonomously
Agentic AI → Coordinates entire processes end to end

What if your AI agent was stateless and loaded its entire identity, memory, and knowledge from a SharePoint site?

That's what I experimented with. Patty is a paralegal agent running on OpenClaw with SharePoint as her brain. Three-tier architecture: channels, agentic runtime, and SharePoint sites that dynamically mount via rclone.

Every agent gets a root site. Inside: who she is, her tone, her active matters. Each legal matter gets its own "brain" as well, a separate SharePoint site with case details, decisions, and issues.

Version history tracks every change. Permissions control which agents see what. Changes to Patty and her memory are done right in the SharePoint UI and she can operate on meeting recordings, notes, documents just like anyone else.

The real unlock? The agent is stateless. Swap the agentic framework tomorrow, the brain persists. Multiple agents can collaborate on the same matter with the same 'agentic brain' for that case--learnings share across agents instead of each agent having to relearn. The storage layer gives you versioning, metadata, permissions, and audit trails for free.

Just for fun, but the more i play with it, the more it seems Agents should be party of the productivity tools running on content management systems, not run git and developer tooling.

Check the link in bio for demos.

What happens if OpenAI, Anthropic, and Microsoft Copilot start working more closely together?

In this video, Dirk explains how these three AI players could potentially complement each other and what that would mean for the future of AI tools and productivity.