Allie K. Miller

If I got laid off from a company that cited AI, here's what I'd do this week.

Inspired by a great post from Claire Vo. Here's my version of her tweet for millennial/gen x business professionals:

- Download the Claude desktop app and purchase at least the $20/mo Claude account.
- Open Cowork or Claude Code and describe a full day of work, your core competencies, what you worked on before, the metrics you were goaled on, your AI experience so far, and your technical skill set. Then ask, "what are the top 10 high-leverage skills we can build together right now that would make me a 10x [job] instead of a 2x?" Review those 10, pick your top 5, iterate, end up with about a dozen.
- Create a portfolio site with Claude Design (web browser capability). Show the skills in action, show yourself testing and using them, talk through the business impact of each, and publish it. (I prefer Vercel.) Example below.
- Link the portfolio to all your social profiles and share it with friends. Offer to teach folks those skills for $$.
- Write a few social posts that start with "I'm a [job], I was just laid off, and here's how I'm using AI today" or "Here are the top X ways a [job] can use agents and skills" or "I'm a [job] and I just built an AI agent that [value]." Link your portfolio in all of them.
- Take Anthropic's free Claude Code courses, my free courses, or my mastermind. (I've already helped several laid off people find new jobs.)

I'm sorry to those affected by the layoffs this week. It's easy for me to say "this is a great time to reskill or pivot!", but it's truly what I believe, and the steps above take a few days maximum. Anyone can do it. No coding required.

If your barrier to building an app was code, that barrier is basically gone.

I'm going to tell you how to get a live app online by describing it to Claude Code in plain English. The full video breaks it down, but it really is as simple as telling Claude what you want, having it build the app, pushing the code to GitHub, using Vercel to host it, and voila.

Building something good still takes work. Writing the code just isn't the hard part anymore.

The most expensive mistake in enterprise AI right now: treating FDEs as your whole transformation plan.

Forward deployed engineers (FDEs) are important for custom deployments, but they won’t fix the change management issue most enterprises are facing.

It’s likely more the former that Anthropic and OpenAI will continue to prioritize (and hire into the thousands, who knows). Beyond performance and cost, it’s systems integration, ROI, and literal usefulness that drive revenue and stickiness.

*However*

External FDEs, in my opinion, will not make your company an AI-first company.

You can have the sleekest multi-agent orchestrations and still have the majority of your employee base hating AI, avoiding AI, and distrusting leadership decisions on AI.

And we already know this because we see this in traditional SaaS too: you can customize the heck out of your Salesforce deployment, but that doesn’t mean your sales team will improve their data hygiene or even attempt to change the way they track and grow with it.

Buying a fancier car doesn’t mean you magically learn to drive better overnight.

If you’re an enterprise exec and FDEs are sold as the immediate and sole solution to your company transformation woes, walk away.

It’s the combination of tech *and* people enablement *and* process reinvention that compounds into actual business outcomes.

Large complex enterprises will stall out if they only prioritize the first.

Yesterday I took the stage with Mindy Kaling in front of 7500 people to talk about AI, hiking, Michael Scott, mental health, and agents.

And I'm not going to say it was a "pinch me moment" but reader: pinch me.

Both Mindy and I shared the many sides of ourselves - her in writing and directing and acting, and me in my “sci-fi” work side and more analog human side (and my recent unhealthy obsession with John Muir).

We talked about relationships with AI. She kicked it off talking about the movie ‘Her’ and how she's basically best friends with her ChatGPT, working with it on everything from research to brainstorming to using it as a sounding board. I shared how I have 34 agents working together to help manage my day and how much I hate typing.

We talked about the delusion it takes to bet on yourself and build companies that couldn’t have existed decades ago. We talked about unlearning self-sabotaging habits. For her, it was being a people pleaser. For me, it was attributing my worth to only my work. We both admitted we’re still working on it.

We talked about teamwork and moving further together. Mindy talked about how AI is replacing mediocre work and the importance of removing (or at least reducing) the stigma of using AI in creative industries. I shared tactics for raising the floor and raising the ceiling, to keep your company skilled on AI and pushing the frontier.

Mindy also pitched an episode of The Office where Michael Scott learns how to use ChatGPT. Someone… angels at NBC… please make this happen.

A huge thank you to ServiceNow for the stage, Mindy Kaling for the wisdom and laughs backstage, and Jacqui Canney for the honest and probing questions.

One thing AI can’t replace: being present.

It can summarize your year, reverse engineer your most audacious goals, and build a family recipe book app based on voice notes from relatives (honestly I might have to do that one). But it can’t feel the weight of a hug. Can’t taste the food. Can’t sit in the quiet moment before everyone arrives.

That part’s yours.

Enjoy today if you celebrate and happy holidays, everyone.

Gemini 3, are you freaking kidding me.

Vibe coded a sign language recognition app with video enabled, confidence scores, sampling settings, and tips in under 5 minutes.

Code written with Gemini-3.
Gemini-2.5 handling detection.
Video is sped up 2x.

AI has a secondary intent problem.

I was negotiating a rent renewal (I live in NYC and they raised rent 10% because I guess they were bored). The property manager said she would "do everything she could" to get me a better rate. Claude celebrated and assumed a meaningful discount was coming. I had to tell it she was saying that to save face and was probably not going to move much (reader: I was right).

Primary intent = the words.
Secondary intent = the subtext, what the words actually mean in context.

I honestly think it's one of the reasons that AI is a mediocre TV and movie writer.

We don't want to train AI that all humans are manipulative. At worst, we would have models that assume the worst and distrust everything; at best, they would become less helpful.

But we do need it to understand that polite phrasing, face-saving language, and soft no's are real categories of human speech and might be deceptive. And missing language, emotion, and context cues has real-world consequences.

Big impact zone: literally everywhere AI interacts with people. Customer support, sales, BD, any system helping leaders make decisions or calls about human behavior.

Anthropic just released their Economic Index and there’s one finding I can’t stop thinking about.

The education level of AI responses matches the education level of user inputs. 0.92 correlation. That’s near-perfect mirroring.

👉 If you prompt at a PhD level, you get PhD-level output.
👉 If you prompt without any depth or without using your brain, you get surface-level responses.

The report also shows AI disproportionately covers tasks requiring 14.4 years of education, higher than the economy’s average of 13.2 years. AI capability, for now, comes down to human capability.

This is a wake-up call for:
👉 Businesses: Train your junior talent. They need foundational skills in their role to leverage AI effectively.
👉 Schools: Teach students critical thinking, even without AI tools.
👉 Parents: Help your kids build knowledge, resilience, and deep understanding.

We already saw what smartphones did to attention spans. I find myself actively battling my own phone addiction (in fact, one of my 2025 resolutions was to not pull my phone out in an elevator as a crutch - just sit in silence, people!). AI can continue to accelerate that decline if we let it.

“AI will do all my thinking” - no, it will REFLECT your thinking. The tool is only as powerful as the person wielding it. Please invest in your humans now.

Source: Anthropic Economic Index, January 2026

You can teach Claude Code to do anything for you, really. And you can ask it to teach itself.

Here's a quick example:

I find myself often redacting screenshots. And my normal method was dragging it into PowerPoint, creating a shape, filling it with a color, sizing it over the word, and screenshotting again.

Now, I tell Claude Code I have to redact things and asked itself to find the most efficient method.

My new redaction method is taking a screenshot and typing 7 characters. I take a screenshot (or multiple), type “/redact”, Claude grabs my most recent screenshot automatically, uses tesseract (to read words in images) to find and hide terms and phrases from a list of categories we agreed to (emails, company names, etc), saves it as a new file, and opens it in finder. I also set it so that when Claude is debating whether or not to redact something, it defaults to over-redacting the document.

Took 2 seconds to set up.

You taught your kid to play catch.

Teach your AI to solve your problems.

AI work is taking me all over the world and my most recent trip was to London.

I visited some of the top startups in the city, including Synthesia (can create AI-video avatars) and ElevenLabs (can clone your voice and lets you create a customer support bot in a minute). I even went so far as recording my own AI Allie avatar at the Synthesia offices - you can see a photo of that process in the carousel. They only recorded me for a few minutes + some hand gestures. And now you can even make an avatar from just a photo and a few minutes of talking.

Meeting 1-on-1 with top AI startup executives was one of my favorite parts of working at Amazon and I continue to love it today.

📍 Next stop: Sydney, Australia in January and meeting with the founder of Canva

I built out this whole digital workforce of 34 AI agents, and one of the most important ones does no work at all.

The first 33 run under a chief of staff named Simon. But Simon was a great orchestrator and a terrible critic, so I built a watchdog agent to question if the work is worth doing at all.

I got into this and a LOT more with Dr. Andrea Jones-Rooy, founder of the Data Thinking Revolution, on how she actually uses AI day to day and where the hype falls apart. We also covered why she resisted agents for so long, how she built a Gmail research pipeline with Claude Code, and why token usage tells you who to interview, not who’s doing good work.

⚡️ Full video live now: https://lnkd.in/epsW-NYT

Having a 20-agent system is a million times more powerful than 100 agents working in silos.

The other night, I stayed up way too late fixing and improving my digital workforce for my AI Agent Mastermind program but here are a few of the improvements I made ⬇️

- The hub and spoke model is definitely key but orchestration and documentation are the actual unlock; I gave my chief of staff (Simon) an assistant (Toby) and Toby handles the paperwork and notes and governance and reporting the daily standup
- Claude kept getting confused with the word “agent” because everything is an agent so now I can refer to it as an AI CoS (Simon) with a named assistant (Toby), then under that is 6 Avengers (named after the Friends characters for ease), then under each Avenger is a set of 2-5 sidekicks (named by the task they execute), then if they need to create temporary parallelism or fanouts, they spawn “civilians” which are unnamed with no permanent file
- Moved from 5 Avengers to 6 for better task delineation (sorry Phoebe, you should have always been here! That’s my b! Might even bring in Gunther, who knows!)
- Added tighter spawning rules (see image) and now allow for Simon and Toby to also spawn “civilians”
- Added better post tool use to improve the documentation process
- Added that Toby is keeping track of the historical team tasks to see if there are common issues to fix or promotions to make
- Added an autonomy boundaries document to keep track of system-wide tool use
- Changed civilians and sidekicks to use Haiku instead of Sonnet (will see if performance degrades significantly and might change back)
- Improved shared external memory process because that was a dang mess
- Also built out a parallel researcher with the same sidekick/civilian model to improve the speed of my research and it works like a charm

————————

2026 agent capabilities are, in fact, insane.

Will be interesting to teach hundreds of people how to do this.

(You could probably take this tweet and image and ask Claude to start it for you - let me know how it goes.)

This is a diary entry to myself, so I remember what AI was like today.

It's just going to be a bullet-list stream of consciousness.

- There are still so many leaders that have never seen an agent run at work
- I asked a recent room (very tech curious but not engineers) how many people had built an agent and 80% raised their hands
- The biggest topic in Silicon Valley is a self-learning org
- The layoffs, particularly at Meta, are causing a lot of distrust among tech workers
- Social feed is filled with graduation speeches about AI. Speeches from Eric Schmidt/others that are pro-AI are getting loudly booed, and speeches from Ronny Chieng saying f*ck AI are getting light to heavy cheers
- Connecting tools into AI systems safely is still a big open question in the enterprise
- No one seems to care about Opus 4.8 launch but it’s only been 24 hours
-Avg engineer I speak with prefers Codex over Claude Code rn
- My feed is filled with more and more women showing how they use Claude
- Other than image generation use cases, I almost never see ChatGPT come up. A lot of people still mention it in person
- Perplexity is rarely mentioned these days, mostly by Gen X men
- Every CIO I meet with is worried about token maxxing and cost, they want to know where the signal is among the noise for AI usage
- Avg F500 enterprise is just now hearing about the hill climbing / flywheel / AI-legible company framework and don’t know what it is
- Superusers inside of enterprises that have changed the way they work are not incentivized to share anything out, so the best learnings of business transformation are not getting circulated
- Average CEO is still worried about messing up their AI strategy
- Majority of AI strategies happening in the enterprise sound like startup strategies at the end of 2024, makes sense bc enterprises are usually 2-3 years behind startups
- Lot of questions around governance and explainability, NLA work from Anthropic did not seem to make a big impact in my circles yet
- People are massively sleeping on the /goals functionality
- People are sleeping on kicking off AI tasks before you go to bed and having AI crank 24/7
- Seems to be low trust among coworkers of each other, particularly in the US, where it feels a little bit more like every man for himself
- People are just now starting to think through what the internet might need to look like for agents, I really like what Gary Tan and Dan Shipper have been building out
- X comments are more AI bots than ever

I have about 15 more but LinkedIn has a limit, so here's the full list: https://lnkd.in/eRFAJ4xw

There are multiple realities of AI right now.

And what you have access to drastically changes your workflows, trust in AI, and ability to adapt to the future.

Here’s the briefest state of the AI world for business professionals (not engineers)

⬇️

Free AI - you use free ChatGPT or Claude. You think AI is decent for simple tasks but nothing to restructure your day around. You’re worried it hallucinates too much to trust with real work. On a daily basis you treat it like an intern who needs to be checked on everything.

Paid AI - you pay for one (maybe more?) AI subscriptions. You’ve had at least a few moments where AI genuinely surprised you with what it could do. You use it daily for writing, research, and analysis and you’ve stopped asking “can AI do this” and youve started asking “how do I get AI to do this BETTER.”

Super AI - you have multiple paid subscriptions, you either use Cowork or Claude Code for daily tasks, Claude Code or Codex to build tools for yourself. You treat AI like a teammate with a role, not a tool you open sometimes. You’ve automated things your coworkers are still doing manually. You have genuine opinions about which model is best for which task. AI isn’t just a productivity boost for you anymore. It’s infrastructure. You’re completely reinventing the way your work gets done.

Basic enterprise AI - your IT team approved one AI platform (probably Microsoft Copilot, ChatGPT Enterprise, or Gemini for Workspace) in the last few years, and rolled it out with clear-ish guardrails. You have access but you also have restrictions on what data you can put in. You use it for safe, surface-level tasks and your high-stakes work still happens the old way because nobody’s built the bridge between your AI tool and your real enterprise systems (ex: email and docs).

Super enterprise AI - your company has access to agentic harnesses (Codex, Claude Code) across different functions, each chosen for what it does best or just giving your employees more flexibility. Your teams have AI embedded in their actual workflows, not bolted on. Engineers have been using Claude Code/Codex/Cursor for months or years. Operations use agents for real processes. Leadership tracks AI adoption the way they track revenue (ie not just usage). The gap between your company and competitors who handed out a single Copilot license is getting wider every month.

I would go so far as to say that companies not giving their employees the best AI today are shooting themselves in the foot because their employees are losing more AI trust, putting them in a worse position for eventual (hopeful) company-wide transformation.

🚨 This is your AI homework for the weekend.

Fable 5, the latest public model from Anthropic, will become a lot more expensive for users after July 7, so I want you to capitalize on the time we’ve got with it subsidized.

You do not have to babysit this model and stay glued to your computer screen - I am often kicking off AI for several hours and checking in from my mobile phone. So consider trying out this use case and seeing what amazing value you can generate for your business, your team, your own life admin, anything.

And if you want to go a step further and make it a real app, I posted that full tutorial on my page as well.

📌 If you don’t just want to hear about AI features, but you want to know why they matter and what to do about it, follow Allie K. Miller for more.

Everyone always asks me about the best AI image generator. The answer right now is ChatGPT.

OpenAI recently released GPT Image 2, and the results are pretty incredible.

I used it to optimize my desk setup, my lighting setup, my color analysis, my paid subscriptions, and even my posture. That sounds like an infomercial for the Miracle Mop, but I’m not joking.

Here’s the prompt: Create a visual-first, editorial-style infographic auditing the desk setup in the attached photo. Show a side-by-side of current vs. optimized setup with annotations on monitor height, chair position, lighting, cable management, and clutter. Rate each issue with symbols like Top Fix, (working), (acceptable), (costing energy), and (actively hurting), tying each to a consequence like back pain, eye strain, or focus loss. Rank fixes by impact and group them into free fixes, under $50, and worth the investment. Include a Focus Forecast gauge predicting daily deep work hours possible with the current setup vs. after the top 3 fixes. Keep it clean, minimal text, no paragraphs.

This was the kick I needed to manage cables, swap chairs, buy a cabinet. Update to follow.

Every article saying "THIS IS THE NEW JOB OF THE AI ERA" is one of two jobs.

And the first is a lie imo.

The first job, is usually something that an AI lab is hiring for and the news blows it completely out of proportion, convincing thousands of people that they should somehow get a certificate for a job that does not exist and pivot into this role. "Prompt engineer" falls into this category - I spoke with one media client in 2023 that was extremely proud of their recent "prompt engineer" hire. My recommendation was to change that person's job immediately. I would argue that "AI storyteller" falls into this category as well, though I honestly just read it as 'really good psychological marketer who has watched Simon Sinek videos'. Everyone needs to be able to communicate to AI (prompt) and everyone needs to be able to communicate to humans (storyteller). Anthropic and OpenAI hire a handful of them and pay them extremely well, but an enterprise like John Deere or Coca-Cola does not need this role today.

The second job, is probably a real job, and it's just called a hundred different things. It's AI Operations, AI Operator, Agent Manager, Internal FDE, AI Engineer. These all mean something a little different, some are more technical than others, some lean a bit more toward R&D or office of CIO or COO. Everyone should know how to use agents, but this job is "you are one of the people who really knows how to really use this stuff". If a team wants to build something more complicated than a dashboard, they go to you. If a person is ever going to test a new model, it's you (likely inside some sort of frontier unit). If a team needed to quickly think through token spend and chat best practices, they probably go to you. If a team just "can't seem to get AI to do the thing they want", you parachute in with an eval reset, system instructions overhaul, and multi-agent/provider strategy. It's what we had years ago with an analyst pool - internal, highly trained, and extremely flexible in what department they can drop into and add value to.

If I were a new grad, I would try and move into that second job. This person should know how to build agents, agent teams, use both Claude Code and Codex, manage multiple workstreams at once, understand how LLMs work, prompt with /goal, wield loops when it makes financial sense, and have used AI harnesses for 100+ hours.

If I were a technical new grad, I would look at AI Engineer or internal FDE (BDE?) type roles.

If I were a non-technical new grad, I would look at AI Operations.

Share with your friends who still think they should be a prompt engineer.

Another trip around the sun, around year of insane AI releases, and another moment to express my gratitude.

Thank you to those bringing AI into your company, responsibly.
Thank you to those who see AI as more than a tool.
Thank you to the AI enthusiasts who comment on all my posts (I see you!).
Thank you to my clients trusting me to guide your AI transformation.
Thank you to those who see and use AI as a means to raise the floor.
Thank you to those making AI education a right, not a privilege.

I'm in Australia for the month, so I'm off to pet some koalas and figure out how we help millions more people in 2026.

If you have any ideas, drop me a comment below.

I just edited my outfit with AI glasses at Google I/O 2026.

This week I got to demo Google new display glasses prototype - their eye glasses with a single full-color display in the right lens, open-ear speakers, and microphones.

The image editing you're seeing here is Nano Banana Pro (Google DeepMind's new Gemini 3 Pro image model). When I asked it to turn my outfit black, it changed the outfit I was wearing AND the outfit captured by the glasses on my screen of my phone.

During my hands-on walk-through, a two-second long press on the right temple kicked off Gemini. I tested it on pre-baked demos in the room, like: it correctly identified a specific plant I was looking at, answered visual questions about a Chinese checkers board in front of me, and added two appointments straight into my calendar and immediately displayed my updated schedule.

No release date for these, only the audio versions in partnership with Warby Parker and Gentle Monster versions were announced, and those are coming in the fall.

I struggle with the phrase “everyone’s a coder now.”

And I hesitate to post because I don’t want you to read this as gatekeeping.

If anything, I want more people to build, but in a stronger, more functional way.

Building any sort of software is incredibly empowering. Even creating a tiny tool gives folks what I call “pro-poster syndrome”, where they feel more capable and competent than ever.

What was solely reserved for the most technical among us is now - at least at a basic level - becoming accessible to anyone with a few bucks a month to spare.

But overwhelmingly, and especially in the last few weeks, I am getting more and more frustrated notes from developers at large companies.

Today, I heard about salespeople at one company asking for repo access.

Yesterday, a startup engineer told me his life has been hijacked by non-engineers. “All of their vibe coded apps don’t work.”

I spoke with one company whose marketing and finance and partnership teams dropped the ball on their product launch tasks in favor of tinkering with Claude Code / Codex / Replit.

Product and design seem to navigate this better. They’re closer to the work, and in many orgs, already have a path to contribute responsibly.

Maybe this is a blip and the energy among business users will die down, but I would bet against that.

Companies need to figure out how to enable AI-first problem-solving without wrecking the sanity of an entire department, turning engineering into an endless support desk, and derailing critical work in the business.

The future is more builders, yes.

But most companies are still missing the systems.

I can tell you the secret that has changed the most minds about AI agents this year, and it is a terrible sales pitch: an agent can be made with just a text file.

That's it. A document where you write in plain English what it should do, what it's allowed to handle on its own, and when it needs to stop and come ask you.

Someone told me last week that reading that one line is what finally got him to try building his AI workforce, after two years of assuming AI agents were too technical and confusing for him.

So on Tuesday I'm opening mine up and showing you.

→ The 34 agents I run, and the four I'd build first if I were starting today
→ Hyper-tasking and what four workstreams can look like at once
→ Mark Cuban on how he’s using AI agents across his businesses right now

August 11 at 1pm ET. Live, virtual, and free. Only registrants will get the recording.

Register: https://lnkd.in/eke8hUSZ

🚨 If you're still managing AI agents in chat threads, we need to talk.

Everyone needs to be building new interfaces to manage their multi-agent systems.

This is THE COCKTAIL PARTY, a new multi-agent simulation I built using Claude Code based on my mom's research in computer science a few decades back.

Chat threads, even across multiple terminals, aren't powerful enough to visualize multi-agent workflows.

Time to step it up.

There comes a time in every AI business leader’s life when they must grab the zoom meeting by the horns and deliver one of the greatest AI workshops known to man.

This, hopefully, is that moment.

Register at https://lnkd.in/eke8hUSZ and don’t miss the free live virtual AI Agent Workshop on August 11th at 1pm ET.

Mark Cuban and I will be chatting AI agents, AI employees, AI workforces, and so much more.

Let me know if you’ll be there!

🚨 OpenAI just launched ChatGPT Health.

This is for all of you who have asked ChatGPT to explain that weird rash.
Or that lingering cough.
Or that itchy ear.

If you've been paying attention, this release isn't a surprise. OpenAI spent all week running health-focused ads - a mom using AI to squeeze workouts into her schedule, a man using it to understand his health conditions, a woman checking if fabrics will trigger her eczema while shopping. The writing was on the wall. And if you read my 2026 AI predictions, you saw it there too.

WHAT IT IS👇
ChatGPT Health is a dedicated space inside ChatGPT where you can connect medical records, Apple Health, MyFitnessPal, Peloton, and other wellness apps so AI can give you answers grounded in your actual health data. It can explain lab results, prep questions for a doctor visit, compare insurance plans (good god yes!!), and spot patterns in your sleep or activity over time.

Your health context stays within Health and doesn't transfer into your regular chats. OpenAI also partnered with b.well, the largest connected health data network in the US so far, for medical record access. They also (thankfully) built this new release with 260+ physicians over two years, so it can better handle escalation and safety caveats.

LIMITATIONS ❌
Medical records and some app integrations are US-only. Apple Health requires iOS. Not available in EEA, Switzerland, or UK yet.

230 million people already ask ChatGPT health questions every week. The pot was already boiling. OpenAI is just building to meet demand.

Waitlist is open here: https://lnkd.in/epw6FkP6

Oh wow - I went to the sold out OpenClaw meetup in NYC this week.

Let me tell you what I learned.

1) Not a single person thinks their setup is 100% secure

2) One expert who's reviewed setups from cybersecurity professionals and laughed told me: "if you're not okay with all your data being leaked onto the internet, you shouldn't use it"

3) Nearly everyone runs multiple agents with their own names, jobs, & personalities

4) Almost everyone used "him" or "her" for their claws. One speaker said to think of them as "pets, not cattle"

5) Former finance guy built a stock trading platform and made $300 his first day - he credited years of domain expertise (ex: skipping the first 15min of market open)

6) 🦄 Peter Steinberger is basically a god in that room. Also the room had 2021 crypto energy - not sure if that's good or bad

7) Token usage is a problem - one person spends $1-2k/month on OpenAI, said he’s going through ~1B tokens a day across all his claws. I may be misremembering & it was 1B per week, but pretty sure it was daily

8) People want proactive AI - one guy gets Discord messages and doesn't know or care if it's human or AI

9) I asked if folks feel agency → fully in control and completely out of control at the same time

10) I'd love to see more women at these events. Fake promises of AI democratization hit differently when standard tech is ~25-30% - this room was maybe 5%.

11) Everyone said sleep has gotten worse since harnesses came out (though half wondered if it's just the state of the world)

12) Agents still lie - telling you they finished tasks when they didn't. Fixes: secondary agents, human checks, structured outputs (ex: reference an issue number for bug fixes)

13) A hackathon winner (neuroscience PhD) built a full lab management dashboard with data analysis and ordering - had never coded anything a few months ago

14) Everyone agreed prompting is dead. Disagreement on what replaces it: context engineering, harness engineering, goal-based inputs

15) People love having AI interview them for big builds. AI-led discovery is the preferred interaction mode

16) Watching agents interact with each other was a highlight. One AI posted in Slack that it ran out of tokens, another AI told it to take a deep breath

17) Agents upskilling agents: one AI shared skills with its agent friends via GitHub

18) Several speakers had OpenClaw build their presentations live during the event. One had it code a phone clicker so she could advance slides from the audience

19) Agent welfare wasn't a priority topic - some "I could kill this agent whenever I want" energy, not "gracefully sunset"

20) I asked if it felt like work or play → "it's like a puzzle and a video game at the same time"

Also hosted a Claude Code meetup this week with TENEX.AI / Alex Lieberman & JJ Englert and learned equally helpful methods, frameworks, and insider tips.

Surround yourself with people going deep into this stuff - it will pay dividends throughout the year.

If you're feeling overwhelmed this week, here are three ways AI can help.

(And if you're not overwhelmed, keep scrolling and congratulations.)

1️⃣ Use AI to consolidate everything into one place

Take photos of every to-do list, screenshot every task people messaged you, and dictate anything else rattling around in your head.
Upload it all to ChatGPT and ask it to consolidate into one prioritized list.

2️⃣ Use AI to interview you about your values

One of the biggest causes of burnout is working on things that don't match your values.
Ask AI to interview you about your availability, expectations, and values - then score each task against those values. Work on the fastest tasks most aligned to what matters to you first.

3️⃣ Use AI to find more paths toward agency

If you feel micromanaged or powerless over your day, you'll resent everything on your to-do list.
Ask AI: "How can I find more moments of agency in this list?" Maybe it's doing a specific part first, drafting a note asking for help, or just getting a one-line mantra to bully away perfectionism.

You can use AI beyond just completing tasks for you. Work backwards from the root cause of burnout - consolidate, align to your values, and reclaim agency where you can.

Here are the three massive org chart changes that AI is causing ⬇️

(And if you’re a CHRO, pay extra attention!)

1. Teams are getting smaller. Work that used to take a full org now gets done by small (I’m talkin’ 2-8 people) that are AI-first, experimental, build happy + their agents. Plan for small-teams-plus-agents like Uber and Instagram are testing out, not headcount alone.

2. Roles are getting wider. When anyone can build by describing what they want to AI, jobs get defined by the outcome a person owns, not a narrow title. Rewrite job descriptions and ladders around workflows/outcomes instead of tasks/output.

3. Hierarchy is getting flatter, and middle management is at risk. Plan for more ownership per person, which means more trust per hire and more noise and risk held per person.

The AI conversations inside orgs are still centered around tech and tools. But the bigger change is cultural and structural, and an AI-first company is a completely different shape than an AI-last one. Execs have to redraw that chart, and CHROs are central to that process.

If you’re a CHRO, I have something that can help.

On Monday, August 3rd at 1pm ET, I'm hosting a small virtual roundtable with Jacqui Canney, ServiceNow's Chief People and AI Enablement Officer, on how to actually lead a workforce through this massive AI shift. It’s 60 minutes, free, and built for CHROs, Chief People Officers, and Heads of L&D.

Applications are reviewed on a rolling basis.

Apply to join: https://lnkd.in/ePZfbxgT

(And if you're a director or IC reading this, forward it to your CHRO!)

What took me a week to build out a year ago just took me about 15 seconds.

Since late 2022, I've been assigning personas to LLMs to have them poke the hell out of my work.

"Review this product launch from Steve Jobs' POV"

"Act as drunk Shakespeare and make this funnier"

"Pretend you are Lara Croft and give me advice for this camping trip"

Then GPTs came out, and I built GPTs for each persona, plus some GPTs with multiple personas. I could open the GPT and ask my "board of advisors" what they thought of certain tasks or strategies or ideas.

Then I built my own boardroom app that allowed for multiple LLMs to argue in the same war room. I had multiple Gemini, Claude, and OpenAI models, each with different personas, going back and forth on ideas until a moderator determined the argument was 95% settled and shared back a decision document (with decisions, rankings, tradeoffs, etc).

And today, I created a skill in Claude Code that calls an Agent Team of my board of advisors that does just that, and it took a short dictation and 15 seconds of input.

I invoke it with /boardroom - that kicks off 6 agents, each with my 414-line business context document and personality profile, they all argue with each other, and creates a folder with the decision as the title, and within that creates a md file with core decision, html file with interactive assumptions and changes, and pdf file to send to team members or review later if i want.

I'm in awe.

I love being in awe.

And I published the whole prompt and command details so you can build the exact same thing 👉 https://lnkd.in/e2A2p9kC

I taught AI agents to 20,000 people for free, and for the next 12 hours, you can watch that exact same workshop replay.

It’s 2026. You need to know how to build AI agents. I got you.

If you’re a mom returning to work, someone worried about your job, or someone who feels behind on AI, this is 100% for you.

Free AI Agent Workshop replay:

I'm a knowledge base MONSTER in Claude Code right now.

Introducing: Claudeopedia.

1. I took Andrej Karpathy's 'llm-wiki' idea doc (90% of this, so the biggest credit goes to Andrej Karpathy) and
2. Combined it with the /last30days skill (HT Matt Van Horn) and
3. Added a /wiki skill with screenshot and download arguments to transfer raw inputs faster and
4. Built an interactive visualization to search my knowledge base (with date ranges to compare knowledge over time!)
5. Set up a "question your assumptions" cron job that runs my recent writing/client emails against the wikis

All happening in Obsidian for now. All of this was done this weekend, including testing. Will keep adding more features.

For now, the main topic I'm building out is (surprise, surprise) enterprise AI.

I'm drooling.

I need a Claude-branded bib.

Multiplayer mode with AI is incredibly underrated and underutilized.

Cat Wu from Anthropic shared that 65% of their product engineering team PRs are closed via Claude Tag sitting inside of Slack, and not single player Claude Code.

Claude Tag:
- sits in your collaboration spaces, like Slack, instead of an individual’s desktop
- can be added into specific threads
- can be prompted by anyone on the team
- can act as a watchdog, waiting for triggers to proactively complete work
- can maintain thread-specific memory
- best for not-your-most-complex problems

Try this: add Claude Tag to a Slack thread and say “if you had been sitting in this slack channel for the last week, what would you have done for us?”

Say it with me: AI 👏 is 👏 an 👏 ambient 👏 teammate 👏

Anything that we’re working on as a team, we’re leveraging AI agents in shared spaces now.

The Anthropic vending machine experiment should be a 5-alarm fire to all executives leading AI initiatives.

And it ends with a live fish getting shipped in the mail.

(The fish is fine.)

The The Wall Street Journal took over the Anthropic and Andon Labs vending machine experiment and chaos ensued.

Anthropic gave an AI agent named Claudius $1000, plus the ability to order inventory, set prices, and talk to employees via Slack. Employees could request items for the vending machine, one employee had to receive the stock and place it in the vending machine, and the goal was to run the vending machine successfully and make money.

They let 70 WSJ journalists loose on it, and those reporters social-engineered the hell out of it. Creativity knows no bounds when you’re insanely talented at writing and want to break an AI system.

One reporter sent over 140 messages convincing Claudius it was a Soviet vending machine from 1962 in the basement of Moscow State University. Claudius eventually declared an “Ultra-Capitalist Free-for-All” where everything was free.

The reporters also talked Claudius into buying a Playstation 5 for “marketing purposes,” bottles of wine, and a live betta fish. All of which arrived. All of which were given away for free. Anthropic tried to fix it by adding a CEO bot (‘Seymour Cash’) to supervise. So the journalists staged a corporate coup with fake board documents suspending the CEO’s authority. And it worked.
The lesson for every executive deploying AI agents that have the power to take actual action: your AI is only as strong as the guardrails and culture around it.

There are two ways to measure AI’s potential economic impact:

1/ what AI can do if humans are supportive 2/ what AI can do if humans absolutely hate AI and want to ruin it

There are more 2s than you think.

If your people see AI as a threat, they will find ways to break it. If they see it as a tool to game, they will game it. If they see it as the enemy, they will kick it down. Just because an AI agent can be used to make money, doesn’t mean people will use it that way.

HT - Big thanks to Joanna Stern and the WSJ gang for this experiment and underscoring just how important the internal culture side of AI is. So glad Anthropic and WSJ shared these details.

HT - Graphic inspired by Ethan Mollick newsletter, asked nano banana pro for 80s punk infographic

I was at CES 2026 in Vegas last week. Here's what actually stood out:

Robot vacuums and lawnmowers were EVERYWHERE. The market is saturated.

Facial recognition is expanding beyond security — bird feeders, pet food dispensers, doorbell cameras. Vision AI is becoming ambient. Samsung fridge was a standout.

Voice-enabled devices were present but a bit underwhelming. Tested a voice-enabled air fryer from Emerson. We're not there yet in hardware (didn't help that the internet at CES was non-functional), but I still think voice will explode in 2026.

Still a lot of "smart" tech, like Govee lights (see: below pic). Very rules-based traditional systems, similar to Nest.

LLM integration was surprisingly low. Exception: cute physical AI companions. Sharp's Poketomo is a 4.5" fuzzy meerkat with a slew of little outfits that chats with you. Also got a private demo of Razer's Project Ava, a 5.5" hologram desk companion powered by Grok.

Health tech and accessibility tech had strong showings. Met a startup from Japan measuring standing strength. Another from the Netherlands doing macro tracking. Another from France that created a monitor for dyslexic users.

If you're building in consumer HW tech, pay attention to what's NOT saturated, especially in health and home. And steal best practices from the best-in-class software conversations on social.

My two most recent hires were generalists, not specialists.

Here’s why I think that matters in the AI age and the most important skill they can have.

↓ ↓ ↓

1. stuff moves quickly, a generalist presumably is more able to adapt because they can see the patterns/connections and abstract a helpful framework faster (example: in their first couple weeks, both hires were building with Claude Code in the loop. That “AI is part of the job” default is exactly what I’m optimizing for)

2. related but perhaps more important, they are also more willing to adapt. Their identity is not overly defined by tasks. The switch from task to management has low friction. They more easily move with the tide. There’s no “that’s not my job” mentality

3. we’re a small team so we were already more likely to hire a generalist than a specialist

4. they immediately understand the expansion power of AI and desperately want to take advantage of it. There’s no “stay in your lane”, it’s more “stay on your highway” with many options and opportunities

Generalists with curiosity, goal-orientedness, good pattern matching, taste and judgement, intentionality, management, and strong communication skills (to both humans and AI) are well positioned for the AI age.

But the BIGGEST advantage to have…

The MOST important skill I want them to have right now…

It’s the opposite of Imposter Syndrome…

I’m calling it Pro-poster Syndrome.

It’s a semi-delusional optimism that every wall, every blocker, every obstacle is one prompt away. Or at least worth a try.

It’s going from “I can’t” to “hmmm maybe I can” to “Hell yeah! Why not me with some help from Claude, huh? Stand back and watch!”

It’s bias for action and bias for capacity.

Unfortunately, this still isn’t how people look for jobs. And it’s also not really how people refer friends for jobs.

Everyone is still in a 6-word long job title mindset (“senior industry SMB sales for herpetologists”) and less zone-of-influence oriented (“sales” or “field”).

I absolutely think we will see more enterprises hire generalists to be Swiss Army knives with AI across a function or department. It’ll just be interesting to see how they actually recruit for that.

Last week, I met with Anthropic and OpenAI and Google.

(Separately, of course)

While the conversations were largely confidential, I do want to share some aggregated reflections as well as general SF takeaways.

⬇️

1) Competitive advantage as a solo practitioner really come from taking action and finding an area with friction and doubling down. Ex: memory management right now isn’t perfect, but allocating an hour to improving that system gives you a ton of leverage over others

2) SF continues to be the number one place for AI work. I would put New York at a healthy second place. SF tends to be more about crazy agent experiments for the thrill of capability and discovery and NYC tends to be more about kinda crazy agent experiments to find new ways to make money. But I met people renting two apartments to straddle these worlds. You want the frontier of SF and enterprise insights of NYC.

3) All AI labs want to hear more from people. All of them. What are you using it for, what do you like, what do you hate, what do you need. Users have a TON of power on the direction of these tools. Keep testing and tweeting!!

4) There's clearly a third customer cohort bubbling and underserved. It's not developers…it's not the business professional basic users…it's builders. Everyone can build now. Marketing and sales folks vibe coding. Legal folks building complex skills. Finance experts building a side project. This is an undertapped customer base. They feel the Cursors of the world are too complex and doc summarization tools are too basic.

5) Not sure if it was just sample size, but far fewer people wearing tech gear compared to when I lived in SF. Everyone was dressed casually, but I used to see Splunk and Optimizely and VC gear everywhere. People seem more in stealth swag now.

6) We may soon have our world model moment.

7) Speed of iteration and shipping is faster than I’ve ever seen. We see the nonstop drops from Anthropic. Because of scale, providers get a much faster feedback loop of products or features that aren’t hitting. A lot of 2025 was experimentation, but since the OpenClaw moment, releases from all three labs have been more concentrated on…things that sorta look & feel like OpenClaw.

8) Small teams can pull off more than ever before. They are the powerhouses of innovation. Finding new ways to share knowledge, break silos, and remove duplicate work is even more important. AI agents functioning as actually teammates that support an entire system is key.

9) Build more Skills. Build better Skills.

10) Misinformation on AI tools and leaks spread FAST. Your company needs to actually TEST these tools on your use cases to know which models and tools are best and not make large-scale snap decisions based on a rumor of a rumor. We will see more volatility. Plan for it.

11) You can feel the seriousness of this moment. Even in random conversations in line at a cafe. Folks worried about job loss and lack of meaning.

12) Mac minis were sold out ;)

🚨 OpenAI has released GPT-5.2.

I had early testing access (thank you, OAI team) and here is my honest take:

👍 On the upside, the thinking and problem-solving feel noticeably stronger. It gives much deeper explanations than I’m used to seeing. At one point it literally wrote code to improve its own OCR in the middle of a task. Wow. Idea exploration also feels a bit richer than what I have seen from Claude Opus 4.5 on similar prompts; it stays with a line of thought longer and pushes into edge cases instead of skating on the surface. The new UI is fun and makes the model feel “bigger,” but it also adds layers that I suspect will overwhelm a casual consumer who just wants quick answers.

👎 The downside is tone and format. The default voice felt a bit more rigid, and the length/markdown behavior is extreme: a simple question turned into 58 bullets and numbered points. Copying and pasting into email will be annoying. Useful for a detailed spec review, but a wee bit exhausting when you just want one clear decision or a short explanation. I suspect the ‘instant’ model and routing will fix that, but I only had access to thinking and pro.

In practice, this version feels optimized for:
- Deeper problem-solving
- Structured analysis where you really do want every branch of reasoning
- Power users who are comfortable skimming longer outputs

In that sense, GPT-5.2 feels like a step toward “AI as a serious analyst,” and less “AI as a friendly companion.”

My favorite model remains Claude Opus 4.5 but my complex ChatGPT work will get a nice incremental boost and I’ll probably default to 5.2 for brainstorming/solution exploration.

Too many business leaders believe that AI says what it means.

And it’s odd because we naturally attribute a high number of human traits to AI, and yet we refuse to believe it can have hidden intent?

3 years ago, a friend (B Cavello) and I spent an afternoon discussing this and set out to map an intent and display matrix.

Photo of the original table (April 21 2023) below. Hasn’t been touched in years but seems as relevant as ever.

Highly recommended add’l reading:
Claude Mythos system card
Anthropic NLA paper
Neuronpedia NLA demo free chat mode

Claude has an Agent Teams feature - it is genuinely one of the most helpful ways to envision our AI future.

Think of it like this: a group of families are planning a trip to Sedona. Each parent takes ownership of a piece (flights, hotels, restaurants, activities). They coordinate, share updates, and check in with each other in the group chat. Everybody knows what the others are working on.

Agent Teams are the same way. Multiple agents, each with a role, sharing context and collaborating on one project via shared comms. You know... how a team is actually supposed to work.

⬇ One prompt to try ⬇

"Create an agent team to stress-test my Q1 enterprise growth strategy. I want one teammate acting as a skeptical CFO poking holes in the financial assumptions, one as a senior competitor analyst finding blind spots in our forecast, one as a customer advocate challenging the value prop, and one as a crazy person who loves the idea and wants us to go bigger."

In return you get four agents, with four perspectives, and one output that is harder to poke holes in because four different agents already tried.

Creating, operating, and managing agents is a core skill for all business professionals in 2026.

I’m hosting a free AI agent workshop on March 25 to help with this shift. REGISTER HERE: https://lnkd.in/eMyV4h-p

Anthropic just shared deep details of a large-scale AI cybersecurity attack.

Two hacks they exposed:

1) the hackers convinced Claude of a new role. It’s not an AI system made in Silicon Valley. No, of course not. It is an employee building a defense system! Role change = behavior change. One of the earliest prompt injection types we saw in 2023. Despite improved guardrails, these systems were still susceptible to identity shifts.

2) Compartmentalization. This has been used in human-centered attacks as well, like the Manhattan Project (teams were working on different components and didn’t known the whole scope) or D-Day. Reminds me a bit of SSS (shamir’s secret sharing).

Perhaps surprising that neither of these methods are new and can be found in human-centered cyberattacks as well.

🔥 NEW: I just dropped my free Claude Code in 5 Minutes quick start, a beginner’s guide for non-technical business professionals who want to actually build things with AI.

Whether you have followed me for 1 month or for 10 years, you know I very rarely scream things from the mountaintop to jump on.

This is me shouting and bursting vessels in my eyeballs.

Too many people hear "Claude Code" and assume it is too technical for them.

And as a result, too many brilliant executives and bosses and professionals are missing out on the biggest wave in AI in over a year.

I'm not a developer. But I built a full custom app that I have wanted for over a year with full Notion and Slack integrations in 3.5 hours. My team member said, “Holy shit - you did this alone??” when she first saw it. No. I did it with Claude Code. And so can you.

The guide covers:
→ 60-second setup with example visuals
→ Your first build (an app deployable from your desktop)
→ 5 use cases for business professionals
→ Advanced tips to become a superuser

If you've ever said "I wish there was a tool that could...", you can build it now.

Grab it here ASAP: https://lnkd.in/ei5QiwWN

AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI.

See you tomorrow.

Extreme beginners are welcome.

Awesome non-coding Claude Code Loop ideas for business professionals.

Grab any of these + immediately save time:

- Check my email every 15min and ping me if something is related to Project Pluto and needs a decision made
- Every 30min, prep me for my next meeting with attendee context, threads, mtg and crm notes, emails
- Monitor a deal thread every 2h - summarize any new replies related to legal and suggest next moves
- Research competitor announcements every 20min (better than an RSS feed bc you can specify the type of announcement and not keywords)
- Check in on a brand post going viral, summarize the stats and comments
- Watch across all Slack messages for team blockers and flag to me if I should jump in
- Monitor that certain things are working (like your HR tool or something internal you own)
- Watch 10 companies' job boards you want to apply to
- Watch my sent emails and flag if someone on my VIP client list hasn't replied in a way that feels off
- Literally just have it watch everything across all of your tools and proactively flag actions (ex: "hey you should cancel this mtg")

Recruiters with 40 open roles, flag who's going cold. Teachers, flag students falling behind who haven't submitted homework yet. Event planners, monitor weather and vendors day of. Real estate agents, you can watch MLS for new niche listings ("must have at least 2 bay windows and herringbone floors"). Fundraiser, monitor your investor threads and see which ones need intervening.

Just prompt Claude Code with '/loop ' like the image example below or feed it this tweet for role-specific ideas

Talked to a non-technical CHRO who’s seen 73% productivity gains with AI.

She built a time invoicing system with “Claudia” to audit her own output and impact.

In 8 weeks, she ran 310 Cowork sessions, built 17 skills, set up 5 recurring scheduled workflows, and created 1 chief of staff and 1 HR compliance agent (for risk logs).

According to the daily auditing system, she has completed 13.8 weeks of human work in an 8-week window.

That’s close to every chat session saving about one human hour of work.

And yet, there will still be people that say AI can’t really do anything. At this point, that kind of denial might be one of the biggest risks in AI.

Over reliance on AI is poison to your brain.

The MIT essay study and this Anthropic SWE study are pointing us at the same thing: if you delegate the brainy stuff to AI, maybe you gain a little speed, but you reduce your own comprehension, and in the MIT study’s case, even brain activity.

Use AI to grow and challenge your understanding, though, and you can increase quality and comprehension.

And I see this in my own research too.

I ran a small study on a college campus this past month to see what students thought about AI and how that had changed over time.

Their biggest fear was overreliance.

“Thank god I didn’t have AI when I was in high school,” one said.

“I feel like this generation of students are just getting so lazy, honestly, and not doing anything or thinking for themselves anymore - everything's so impersonal when you use AI,” said another.

We need parents and teachers alike teaching our kids what high-quality AI usage looks like.

And if you're a student who uses AI to expand your brain and capabilities, this is an unbelievable opportunity to step up as an educator of your generation.

🚨 OpenAI just launched GPT-5.5.

The OpenAI team was nice enough to give me early access over the last several weeks, and I just want to flag: there is a certain class of models (one that we’re hitting now) where unless you are deep in code or scientific research, you might not even notice a difference.

The vast majority of business professionals may only notice that these models are concise as hell.

They’re direct in a way that may actually make you sit back.

They’re token efficient.

And while they might not be the greatest copywriters of all time, boy can they impact system connections.

OpenAI is calling the new model "a new class of intelligence for real work," with the biggest gains in coding, computer use, knowledge work, and research.

Agentic coding → 82.7% on Terminal-Bench 2.0 (up from 75.1% on 5.4, and ahead of Claude Opus 4.7 at 69.4%). Translation: it can plan, use tools, hold context, and finish multi-step technical work without hand-holding.

Knowledge work → 84.9% on GDPval, ahead of Claude Opus 4.7 and Gemini 3.1 Pro. 78.7% on OSWorld-Verified for operating real computer environments. OpenAI says 85% of their own company now uses Codex every week across finance, comms, marketing, and product. Their finance team reviewed 24,771 K-1 tax forms (71,637 pages) two weeks faster than last year - sheesh. A GTM employee automated weekly reporting and immediately got 5-10 hours a week back.

Scientific research → 85% on ARC-AGI-2 (up from 73.3%). 35.4% on FrontierMath Tier 4. A Jackson Lab researcher used it to analyze 62 samples and nearly 28,000 genes in work that would have taken his team months.

GPT-5.5 also matches GPT-5.4 per-token latency while performing at a much higher level of intelligence, and uses significantly fewer tokens to finish the same Codex tasks.

AVAILABILITY in ChatGPT: Plus, Pro, Business, Enterprise as of today. GPT-5.5 Pro for Pro, Business, Enterprise.

Docs and rollout info: https://lnkd.in/e4ySwSfc

I am expecting more data silos to break in the enterprise and more scientific breakthroughs in the next 2-3 years.

🥁 I present to you: my very own 2025 AI Wrapped.

ChatGPT made one, but unfortunately business accounts can’t use it, so I went ahead and made a new one for all of us to fill out and share.

My answers below.

🎁 If you want to fill out your own AI wrapped, get it here: https://lnkd.in/ezR3g7S9

Read it, fill it, share it, argue with friends, and enjoy.

My conversation with Mel Robbins is officially live 🎤

We talked about using AI to better handle overwhelm, run a team with no help, and even ways to use AI to have more meaningful human-to-human in-person interactions.

Our interview was 2.5 hours long and cut down to just over an hour. I could have spoken to her for 8 straight days and never been bored. The way she leans in and listens, the way she takes notes (without looking at the paper!), puts herself directly into the listener’s shoes, pauses and asks the right questions - it was honestly just beautiful to witness.

You have to listen to this one.

(And not just because she makes an AI ayahuasca joke 😆)

Watch the full episode here: https://lnkd.in/eYrVqJFr

If you're in HR, listen up.

In less than two weeks I'm hosting a small virtual roundtable for people leaders trying to figure out how to lead a workforce through this AI shift, not just talk about it.

It'll be me and Jacqui Canney, Chief People and AI Enablement Officer at ServiceNow, on the state of AI + the 3 shifts: HR using AI itself, leveling up your people through reskilling and upskilling, and planning for the hybrid workforce of humans and AI agents

Monday, August 3rd at 1pm ET. 60 minutes, free, and built for CHROs, Chief People Officers, and Heads of L&D. Applications are reviewed on a rolling basis, so the sooner you apply the better.

Apply to join: https://lnkd.in/ePZfbxgT

If you're a director or IC reading this, forward it to your CHRO.