Engin Erdogan

Is @bitcoin new money or incentive for giving to massively distributed processing power? Either way, it proposes a new economy: bitcoin.org

And here it is ❤️

Mezo token goes live on Coinbase! This one hits different 🥹 Over 2 years of hard work and relentless building… Incredibly proud to see the baby finally meet the market. Huge milestone for the team and the community. Go $MEZO!

The ticker is MEZO!

sequoia put out a blog post called "services is the new software" look at this map of over $1T in services being replaced by AI agents

Assets added to the roadmap today: Mezo (MEZO) coinbase.com/blog/increasin…

@chrysb @garrytan 👀

introducing AlphaClaw Apex 🐺 a native Mac app for managing multiple OpenClaw VPS instances from one dashboard. some of you are already setting up OpenClaw for clients as a service. Apex is built for you. deploy to Hetzner VPS in one click. monitor all your instances. manage configs, updates, spend, and health from a single UI. no SSH needed. everything you know from AlphaClaw, now across a fleet: 📅 Google Workspace OAuth & pubsub wizard ⏱️ Cron calendar view and cost-saving insights 🖥️ Remote node setup wizard 🔄 Auto-backup to GitHub 📊 Token usage & cost analytics built in 🧱 Prompt hardening reduces agent drift 🩺 Drift Doctor analyzes your prompts and workspace for drift 💬 Telegram multi-topic workspace setup wizard 📂 Full file browser, editor, and terminal no SSH needed 🐕 Per-instance watchdog and crash recovery 🛠️ Manage env vars from the UI 🔑 Manage model keys & OAuth visually 🪝 Webhook creator & inspector with replay & debug ⬆️ One-click updates, no redeploy needed 📦 Import existing setup from GitHub if you're thinking about offering managed OpenClaw as a service, this is the ops layer you've been missing.

The New Product Economics: Manage product like a balance sheet. Not just faster shipping or better specs. Clarity should compound faster than debt. x.com/erdogan/status…

@sachinrekhi Start thinking your product board like a balance sheet. Quantify your bets compared to debt. Be the center of gravity for clarity on collective intent and real time learning.

Question: Given that all PMs will eventually have access to the same AI tools, how do I differentiate myself as a product manager? I get this question a lot. And I don't love the shallow answer going around that "all that matters is taste." Taste is definitely important, but here's my far more concrete playbook for differentiating as a PM in the age of AI: 1. Stay at the frontier of AI fluency - I think too many people are dismissing this one saying that "everyone is going to have access to the same tools." But I'm a year and a half into this and I can tell you the gap is only widening on folks who can wield AI well in their job vs those that can't. And I don't see that changing anytime soon. So the people best positioned are the ones that know how to use AI effectively to produce great output, which is no easy task. 2. Taste / high standards / judgment - This is the one everyone talks about and I agree it's important. For example, I recently showed off 13 AI PM skills I built in Claude Code. What I didn't show was the 16 others that I tried to build but ultimately threw away because the output didn't meet my bar. I'm seeing lots of other people ship these skills and just accept the low quality output coming out of them. This is a mistake. The first battle is knowing what great product work looks like. The second battle is continuing to hold yourself to that standard. Don't ship slop. 3. Domain expertise - As the functional aspects of the role become more commoditized, I do think domain expertise in a given field becomes even more important. I don't think it's a fluke that a cardiologist beat experienced software developers in Anthropic's recent vibe coding contest. It's because his deep knowledge in the domain allowed him to come up with such a compelling solution to the post-visit patient problem that he deeply understood. Only a domain expert could do that. 4. Product strategy - AI is terrible at product strategy. I've tried every which way and it never comes up with a compelling, differentiated product strategy that has any chance of winning the market. I think that's going to be the case for awhile. So it's a great area to continue to build your muscle. 5. Design - The advancements coming out of Gemini, etc is impressive, but I still can't get AI to match the world-class designers I've worked with in my career. Especially on interaction design, not just visual design. Learning these skills is still valuable.

in a world of agents, the product role is going to split into two jobs: - one that organizes humans (stakeholders, design, eng) - one that organizes agents (prompts, evals, workflows, etc) Both will be in pursuit of offering the right products to customers, but how you get there will dramatically change. What happens to the typical product rituals? Instead of PRDs, OKRs, standups, product reviews, we'll need the equivalent for agents. Couple wild ideas here... instead of standups: the equivalent is that agents will report back to us based on run logs and anomaly flags. no one needs to say what they did yesterday, the system already did thousands of things. the question is where it broke, where it surprised you, and where it got better. Show us the patterns, the trends, the edge cases - particularly the ones the agents didn't fix automatically. the daily ritual becomes reviewing deltas, scanning failures, and deciding which ones matter. less reporting, more triage instead of OKRs: we’ll need adversarial agents that continuously monitor/grade the system and detect patterns, scoring outcomes on an hourly or daily basis. Rather than setting a quarterly goal of "increase X by 5%" and revisiting slowly -- instead, management will be able to monitor success in real-time and detect trends/patterns towards overall goals instead of PRDs: we won't need waterfall. Prototyping will rule the day, and we’ll need a living agentic loop that mediates customer feedback/ratings and what's being prioritized and built. you don’t hand it to eng, you deploy it into the agent loop. if it’s wrong, it fails visibly and you can revert. if it’s right, it produces the right output instead of product reviews: we'll need simulation systems to examine agent behavior in different scenarios. In an agentic world where UI shifts from buttons/menus to agents automatically doing things, you'll want to examine their behavior before you deploy. You rewind decisions, fork alternate paths, and see how different prompts or constraints would have changed outcomes. the review becomes interactive. less storytelling, more counterfactuals. The PM sits in the middle of this split. On the human side, still aligning taste, risk tolerance, and strategy across people. On the agent side, shaping the actual behavior of the system through prompts, evals, and feedback loops. one side is persuasion. The other is instrumentation. the best ones will collapse the gap, translating intent directly into systems that act on it. the fascinating part is that the agentic loop will run 10000x faster than the human one, and of course, you can "hire" them faster. Thus the “organizing humans” half starts to feel slow and lower impact unless it directly improves the agent loop. Eventually the PM will shift towards agents and maybe ignore the human coordination altogether...

The big question in this state of transition is where surplus productivity actually goes absent a “new factory.” Right now, much of it goes into debt. AI doesn’t just make companies faster. It makes it easier to initiate more code, features, experiments, and decisions than organizations can fully absorb. That surplus doesn’t disappear. It accumulates as debt. Wrote about this from the product lens here: linkedin.com/posts/enginerd…

We are entering an era where human-maxxing will be rewarded. Given infinite AI appslop marketed by AI adslop, the way to win is: - be human. your marketing is you and a camera. - app pain point is something personal to you - landing page is not fucking purple

This is one of the most useful tools I've come across for working with my agents. I just ask "research xyz. deploy it on gui.new. use frontend design skill". Instant shareable link, expires in 24 hours.

Anthropic dropped a 33 page cheat sheet for using Claude to build and design anything. resources.anthropic.com/hubfs/The-Comp…

40% workforce reduction. Stock up sharply. AI is being priced as operating leverage. Now we’ll see which teams can turn that leverage into real throughput.

Very apt framing. For the time being, the hunger for legitimacy & scale leads to mimicking the old, and favors “hybrids” - power concentrates on liquidity dispatchers eg custodians, staking hubs, vault providers etc. Risk for big bags is still managed w legal contracts, and it will be a true leap when cap preservation strats are truly fused w smart contracts

PMs using AI “now I don’t have to wait on designers for mockups!” Designers using AI “now I don’t have to wait on developers for code!” Developers using AI “now I don’t have to wait on PMs for requirements !”

@karrisaarinen Taste is a by product of craft and mastery, not an inert skill. Every major societal shift -> evolving crafts and def of mastery -> new aesthetics

Issues, requirements, specs, stories, prds, ords, prompts. Whatever term is in fashion, double down on properly articulating your very human intent