WRITER

43% of employees on marketing teams believe their company would replace them with an AI agent tomorrow if it could. That's what happens when a big transformation moves faster than the conversation about it… and when nobody's told people where they fit into what comes next. We surveyed 1,200 C-suite leaders and 1,200 employees for our 2026 AI Adoption in the Enterprise report, to understand what employees are actually experiencing right now. → 53% of execs say a leaner team is their 3-year success metric → 58% of employees say their manager is "open to AI" but gives them little real direction → 55% already know more about using AI in their role than their manager does → Only 35% have a manager who actively champions AI The leaders getting this right are painting a picture people want to be part of: What we're going to build together. What only you can do. Why your job is about to get more interesting, not smaller. As our CMO @diego_lomanto says: "Your team needs more than reassurance... ‘What am I worth in a marketing function that runs on AI?’…that's the real question, and it deserves a real answer." We put together some concrete moves for leaders navigating this in the full piece: writer.com/blog/ai-leader…

28,000 playbooks have been created in WRITER to date. Today we're unlocking WAY more power for every single one of them. Playbooks already made the best ways of working with AI repeatable and reusable across the team. Our customers like Clorox, KPMG, and Metro Banks ran with them to personalize campaigns, optimize content for AI visibility, generate account insights, and more. Now we're upgrading playbooks so teams can agentify their ENTIRE workflows with more quality, cost efficiency, and control. Modular playbooks. Chained together. Tested and optimized before rollout. Run in bulk. What’s new: → Chain playbooks together to automate work end-to-end. No more copy-pasting between steps! → Test with synthetic data first to validate logic and catch errors before rollout → Track token usage per run. No more black box, no more runaway token costs → Run in bulk: one playbook, 50 outputs, same quality every single time → Curate team libraries so the best playbooks are easy to find and reuse This is AI built for the WHOLE team: tested, auditable, and governed at scale. 💪

@may_habib , co-founder and CEO of WRITER (@Get_Writer ), on the RAISE stage, on the real test for enterprise AI: can you actually trust an agent to run on its own? May Habib: "Do you have autonomy that you can scale with trust? And that really comes down to accuracy and precision across a very long time horizon." Her point: models drift, guardrails fall short, evals are often missing, and too many agents still need constant babysitting. And if you're babysitting the agent, where did the productivity actually go? The question underneath the ROI debate, named on the Master Stage. RAISE Summit 2026, Paris. #RAISE2026 #AI #Paris

Demand Gen leaders spend a lot of their time answering one question: why did the numbers move? It's easy to glance at a dashboard and see the numbers are up or down. But understanding what's actually working takes hours of digging, spreadsheet gymnastics, and gut-checks against what you already know. So @AndrewRacine, our VP of Demand Gen, built a playbook that does the heavy lifting. 1️⃣ It pulls Salesforce data and analyzes regional performance, campaign impact, and pipeline velocity. 2️⃣ Monday morning you wake up to a Slack message with the full breakdown. 3️⃣ You spend 15 minutes gut-checking it against what you know, make edits, and send it out. Now every team at WRITER uses it. Content figures out which blog posts resonate. Campaign teams know what's working. Field teams see what's landing in their regions. Everyone knows what actually moves the needle.

Most "AI strategy" right now is innovation theater. Boardrooms are panicking, and it shows: tools bought on hype, mandates with zero training, layoffs dressed up as "AI efficiency." All performance, no substance. And the results prove it. Fewer than 1 in 4 executives report meaningful ROI from AI agents. The leaders who are actually winning are doing four things differently: 1️⃣ Audit the drag. That 54-step process with all the handoffs? Strip it to 4. The efficiency gains you wanted from headcount cuts were hiding in organizational drag the whole time. 2️⃣ Let business own the rebuild. IT doesn't know why your star salesperson converts at triple the average. The people closest to the work should redesign it. 3️⃣ Find your champions. 5% of your people will build something remarkable out of the gate. Find them and get out of their way. 4️⃣ Shift the KPI from "hours saved" to leverage. How far does one person's judgment travel now? THAT'S what shows up in your P&L. Great byline from our CEO @may_habib in @FastCompany last week! fastcompany.com/91568695/panic…

43% of marketing employees who use AI at work believe their company would replace them with an AI agent tomorrow if it could. That data point from our 2026 AI Adoption survey, is the clearest sign yet of something CMOs can't afford to ignore: the leadership gap. Your team isn't being paranoid. They're doing math. They're reading executive KPIs ("leaner teams," "productivity without headcount") and filling in the blanks themselves. And when no one offers them a better narrative, fear becomes the default strategy. Our CMO, @diego_lomanto breaks down what that gap actually looks like, and shares four concrete moves to close it: 1️⃣ Communicate a vision before the efficiency story does it for you 2️⃣ Document what "good" looks like so AI doesn't produce the average of everything 3️⃣ Define what AI-native marketing means for your specific team 4️⃣ Create space to learn, fail, and come back asking for more If you're a marketing leader sitting on the fence about your AI transformation, this one's worth your next 5 minutes: writer.com/blog/ai-leader…

"It is existential for folks where they're putting their chips on AI." CEO @may_habib says @Get_Writer is the secret weapon. "I don't think anyone has had this level of intimacy with the customer ever." Catch the full story on The Upstarts Podcast, presented by @Rippling🫡

"No one wants to feel like they're talking to a robot." Robyn Murphy, Chief of Staff and Director of Marketing Operations at @HRBlock, is navigating one of the more complex brand challenges in marketing right now. Multiple audience segments, multiple tones of voice, legal claims and disclaimers, all while bringing gen AI into the mix. In a trusted brand, being able to encode your brand deeply into your AI workflows means no one has to second guess anything that gets produced. That's exactly what Robyn and her team have been building at H&R Block. Next week, she's joining us for a conversation with our own @diego_lomanto on building AI workflows that protect what makes your brand distinctive: go.writer.com/brand-engine-w…

Relationship managers at commercial banks spend 25-30% of their time talking to clients. The rest is eaten up by prospecting, research, and data entry. McKinsey surveyed 400 of these bankers, and the results were clear: burnout, frustration, and high churn. So we built 3 AI agents that change this. 1️⃣ A lead-cleaning agent filters out the dead ends. 2️⃣ A research agent pulls company briefs and identifies decision-makers. 3️⃣ An outreach agent writes personalized messages in the banker's actual voice. Run them together, and the numbers tell the story. In a blind test, AI-powered RMs booked 5x more meetings and went on to win millions in new business. That's what agents, done right, actually look like! writer.com/blog/bankers-s…

Every enterprise goes through three stages with AI: pilots, production, and scale. Most are stuck somewhere between the last two. They've got production. They've got the board slide. But truly scaled AI, where agents have taken over an entire business process, is a different game entirely. It requires scaffolding that captures corner cases that never made it into any SOP. That gets smarter the more you use it. That routes to the right model based on actual ROI, not just what's newest. That deployment gap is where WRITER has lived for five years. And this week, @Bloomberg x @VivaTech recognized our CEO @may_habib with a Rising Star award for the vision driving all of it. 🌟 She was honored alongside Peter Steinberger, Yann LeCun, Jeannette zu Fürstenberg, Joe Tsai, and Sir Tim Berners-Lee. Pretty good company! And thank you to Tom Mackenzie for a great conversation on stage!

Our team is live on the ground at #CannesLions, and it's off to a great start! Here's where you can catch us this week: ➡️ @Accenture Women in Leadership Panel | Architects of Growth: Owning the Next Chapter Tuesday, June 23 ➡️ @Citi Panel | AI-Driven Marketing Disruption: From Hype to Revolution Tuesday, June 23 ➡️ Fireside Chat with @JoinChiefNow | The Leadership Layer: What AI Can't Replace Wednesday, June 24 ➡️ @axios Roundtable | Keeping Humanity at the Center of AI Storytelling Wednesday, June 24 ➡️ Podcast with @Snowflake Thursday, June 25

Correct: Writer CEO May Habib says enterprise AI’s biggest hurdle is no longer pilots, it is changing how companies are organized to use it. Watch the full conversation with @TomMackenzieTV at the VivaTech X Bloomberg Awards.  bloom.bg/4ei65V1

You've automated your content. So why does it suddenly sound like everyone else's? That's the catch with AI-driven marketing. It's great at speed, less great at staying distinctive, unless you build governance in from the start. On June 30, we're bringing in @LisaGately, Principal Analyst at @forrester, to share research-backed frameworks for maintaining brand credibility as AI reshapes buyer evaluation. Our CMO @diego_lomanto then leads a conversation with Robyn Murphy, @HRBlock Chief of Staff and Director of Marketing Ops, on what's actually working in practice. Join us live or register for the replay: go.writer.com/brand-engine-w…

Producing a weekly podcast is a lot of work. So we built two agents to handle the parts that slow you down. 1️⃣ Does the prep, researches the guest, drafts the questions, writes the outreach email. You and your guest walk in aligned. Hours saved before you even hit record. 2️⃣ Picks up after. Give it the transcript and it comes back with show notes, chapter markers, and a blog post, written in your voice, not generic AI output. The repetitive stuff goes to the agents. The actual conversation stays yours.

Scale and production are two very different milestones in the enterprise. And that is a very human problem, not a technical one. Last week, our CEO @may_habib joined Rowland Manthorpe (@SkyNews) and John Lazar on stage at #LondonTechWeek for a conversation on what it actually takes to turn AI capability into enterprise impact. Getting to production is a technology problem, but getting to scale is a people problem. Real scale, where agents own an objective process rather than living alongside a human one, requires something even the best models can't build for you. And that's the culture, accountability, and the willingness to rebuild how work actually gets done. A company built around agentic systems needs 15–20% of the organization focused on supervising agentic systems. Today, enterprises are lucky if half a percent uses AI meaningfully at all. That's the trust threshold most enterprises haven't crossed yet.

What a great two days at the @Gartner_inc Marketing Symposium/Xpo™! 🙌 The momentum in that room was hard to ignore. Forward-thinking CMOs. Big questions. Even bigger ambitions. Our own @AndrewRacine joined Tara Castrejon and Karen Rodriguez from @NewAmericanTeam on stage to explore "Redefining What a Modern Marketing Organization Looks Like with Agentic AI." They discussed how leading teams are restructuring, realigning, and reimagining what's possible when agentic AI becomes the backbone of their operations. A key takeaway from this week: marketing's seat at the C-suite table is expanding. And agentic AI is the reason why. To everyone who chatted with us, attended our session, or shared a moment at the booth, thank you! ❤️

[NEW RESEARCH] The more AI knows you, the more it copies your mistakes. Our research team tested how personalization and memory features affect model accuracy across frontier models. What they found is worth paying attention to. Without those features, models answered correctly. Add them back in, and accuracy dropped by as much as 71%. When a model has context on your past preferences and beliefs, it starts treating them like ground truth. It stops pushing back and starts going along with you. In finance or healthcare, where accuracy is non-negotiable, that's a serious problem. Full findings: writer.com/engineering/pe…

"One-off prompting just doesn't work for keeping a brand consistent across a growing team." Tara Castrejon at @NewAmericanTeam, knew they needed something more durable. So they baked their brand DNA directly into WRITER. Now staying on-brand is as simple as clicking a button, and it speeds up everyone's day. And next week on June 9, Tara and Karen Rodriguez from NAF are joining our own Andrew Racine at the @Gartner_inc Marketing Symposium/Xpo™ to talk about what it actually looks like to rebuild a modern marketing org around agentic AI. We're so excited for this one! 🤩 gartner.com/en/conferences…

Your blog could update itself. Like actually update itself…finding content gaps against your competitors, identifying ranking opportunities, writing the posts, and staging them directly in your CMS. We built a five-agent team that does exactly this using live Semrush data. The loop works like this: the agents scan for gaps, plan the best path forward, draft the content, and push it to staging. You review and publish. A final agent comes back a few days later, checks how the rankings moved, and feeds that data back to the first agent to improve the next run. With practice, this means waking up to a Slack message with a short list of suggested updates ranked by impact. You approve the ones you like. The agent pushes them live. You never touch the CMS. The SEO team becomes the editor, not the busy work executor.