We’re hiring a Product Manager to lead SiliconMark—what I often describe as the “CARFAX for compute.” We started with GPUs because the same chip can deliver very different real-world performance depending on the system, networking, cooling and configuration. But our ambition is much larger: to build trusted benchmarks for every layer of the compute stack—from chips and clusters to infrastructure, models, tokens and the economic value ultimately delivered. SiliconMark is already one of our fastest-growing products. We’re looking for someone who can own this vision end to end: benchmark design, methodology, scoring, certification, customer experience and go-to-market. This is an opportunity to help define how the entire compute economy measures performance, quality and value—not just what people claim to offer, but what every layer of the stack actually delivers. Apply here: #Hiring# #ProductManagement# #GPU# #AIInfrastructure# #Compute#

@Shilllin One of the most important lessons of product management: What your users say they want is often very different what they actually want The author of the post above is in the top 1% of React-with-Video users. Since making that post, his volume has only accelerated.

25 awesome PM roles that are hiring right now: 1. @AnthropicAI — Product Manager, Business Technology ($385K – $460K) 2. @Stripe — Staff Product Manager, Connect ($214K – $322K) 3. @Google — Director, Product Management, Google Photos 4. @anduriltech — Staff Product Manager, Growth Platform ($191K – $253K) 5. @AnthropicAI — Product Manager, Safeguards Rare Harms ($305K – $385K) 6. @Cloudflare — Director of Product Management, Fintech 7. @thinkymachines — Product Manager - Post Training ($350K – $450K) 8. @joinHandshake — VP of Product, Handshake AI ($340K – $380K) 9. @CrusoeAI — Vice President, Product Management, Managed AI ($345K – $385K) 10. @Stripe — Staff Product Manager, AI ($214K – $322K) 11. @ClickHouseDB — Principal Product Manager, Partner Integrations ($210K – $310K) 12. @Rippling — Director of Product, IT 13. @SierraPlatform — Product Manager, Agent Development - Public Sector ($180K – $390K) 14. @chainguard_dev — Senior Product Manager (AI CICD) ($205K – $231K) 15. @anduriltech — Staff Product Manager, Manufacturing Software ($166K – $220K) 16. @CrusoeAI — Principal Product Manager, AI Infrastructure (Networking) ($285K – $335K) 17. @nvidia — Principal Product Manager - Laptop GPU and SoC 18. @databricks — Sr. Product Manager, Databricks Free Edition ($157K – $215K) 19. @CoreWeave — Staff Product Manager, Data Services ($188K – $275K) 20. @Polymarket — Staff Product Manager, Crypto ($250K – $400K) 21. @airwallex — Staff Product Manager, Agentic Payments ($175K – $250K) 22. @anduriltech — Staff Product Manager, Advanced Costing Systems ($191K – $253K) 23. @Google — Director, Product Management, Growth and Monetization, Google Maps 24. @Stripe — Staff Product Manager, Billing ($214K – $322K) 25. @airwallex — Staff Product Manager, AI Growth ($190K – $270K) Browse all the roles:

When I talk to senior managers, increasingly hearing stories of the blurring of jobs inside organizations (we found this at our P&G study as well): coding, design, product management, all collapsing & overlapping as everyone uses AI We need new models for organizing work, fast.

SpaceXAI has built an entire Grok Bot Guides library showing how people are actually using AI agents as real teammates These are practical playbooks from people already running Grok Bot for: • Mobile app development • Product management • Design • Enterprise GTM • Managing multiple teams of agents And these are not just chatbot workflows Each Grok Bot can have its own role, memory, cloud computer, connected tools, recurring routines and learned skills, then hand work directly to other specialized bots One example runs a six-bot mobile game studio across analytics, creative, engineering, infrastructure and bug fixing Another has a PM running a Chief of Staff, engineering manager, five engineering agents, data analyst, product agent and recruiter There are even setups where entire projects get their own channel, roster of bots and Notion board, basically organizing AI agents like a human team This is probably one of the most useful resources SpaceXAI has published for understanding what working with a real team of AI agents actually looks like You can check out the entire library here:

Slackbot just leveled up. 🤖 ✨ Amy Bauer, Senior Director of Product Management, shares Big Mode: a dedicated surface for scaling your workflows, deeper research, analysis, and automation. Slackbot does the heavy lifting so you can focus on the work that only you can do.

AI in the enterprise has a messaging problem. The industry sold transformation and delivered meeting summaries. On this episode of Bit by Bit: Leadership Conversations, Tom Butler, Vice President of WW Commercial Portfolio and Product Management at @Lenovo, explains why enterprise AI adoption has stalled, and why the real shift is not about saving people time. It is about reshaping what they do with it. We get into workflow over personas, why “no one cares” about the NPU, and his AI Knights of the Round Table approach to spreading what actually works across an organization. 00:16 PC Market Meets AI 02:41 Rollercoaster Cycles And Refresh 05:05 Workflow First Buying Shift 06:37 Different Sectors Different Speeds 08:51 Storytelling Missteps And Value 10:32 Hybrid AI Edge Versus Cloud 14:39 Security Governance Reality Check 16:40 Culture Shift Outcomes Over Devices 21:15 Middle Management Friction 24:59 Rebuilding Trust With Transparency 30:09 IT Buying Gets More Surgical 33:27 Advice And AI Knights Playbook 37:23 Closing Thoughts And Thanks

Guerrilla Games co-founder Arjan Brussee, a longtime Epic Games veteran who previously served as global director of product management for Unreal Engine, is developing The Immense Engine. The new engine is made in the Netherlands as a European choice instead of Unreal Engine or Unity and follows all EU rules and keeps data inside Europe. The Immense Engine introduces new native AI integration from the outset. Brussee explains that AI agents can fundamentally change devs work with small teams making games faster It will be used for video games and also for 3D simulations in areas like defense and logistics The project, announced today via a Dutch podcast interview, is still in early development

As AI agents accelerate coding, what is the future of software engineering? Some trends are clear, such as the Product Management Bottleneck, referring to the idea that we are more constrained by deciding what to build rather than the actual building. But many implications, like AI’s impact on the job market, how software teams will be organized, and more, are still being sorted out. The theme of our AI Developer Conference on April 28-29 in San Francisco is The Future of Software Engineering. I look forward to speaking about this topic there, hearing from other speakers on this theme, and chatting with attendees about it. We’re shaping the future, and I hope you will join me there! It is currently trendy in some technology and policy circles to forecast massive job losses due to AI. Even if they have not yet materialized, these losses certainly must be just over the horizon! I have a contrarian view that the AI jobpocalypse — the notion that AI will lead to massive unemployment, perhaps even rioting in the streets — won’t be nearly as bad as dire forecasts by pundits, especially pundits who are trying to paint a picture of how powerful their AI technology is. Among professions, AI is accelerating software engineering most, given the rise of coding agents. According to a new report by Citadel Research, software engineering job postings are rising rapidly. So if software engineering is a harbinger of the impact AI will have on other professions, this expansion of software engineering jobs is encouraging. Yes, fresh college graduates are having a hard time finding jobs. And yes, there have been layoffs that CEOs have attributed to AI, even if a large fraction of this was “AI washing,” where businesses choose to attribute layoffs to AI, even though AI has not changed their internal operations much yet. And yes, there is a subset of job roles, such as call center operator, that are more heavily impacted. Many people are feeling significant job insecurity, and I feel for everyone struggling with employment, whether or not the cause is AI-related. And many other factors, such as over-hiring during the pandemic and high interest rates, have contributed to the slowdown in the labor market, and the notion that AI is leading to unemployment is oversimplified. In software engineering, I see a lot of exciting work ahead to adapt our workflows. It is already clear that: (i) As AI makes coding easier, a lot more people will be doing it. (ii) Writing code by hand and even reading (generated) code is not that important, because we can ask an LLM about the code and operate at a higher level than the raw syntax (although how high we can or should go is rapidly changing). (iii) There will be a lot more custom applications, because now it’s economical to write software for smaller and smaller audiences. (iv) Deciding what to build, more than the actual building, is becoming a bottleneck. (v) The cost of paying down technical debt is decreasing (since AI can refactor for you). At the same time, there are also a lot of open questions for our profession, such as: - In the future, what will be the key skills of a senior software engineer? And for junior levels, what should be the new Computer Science curriculum? - If everyone can build features, what skills, strategies, or resources create competitive advantage for individuals and for businesses? - What are the new building blocks (libraries, SDKs, etc.) of software? How do we organize coding agents to create software? - What should a software team look like? For example, how many engineers, product managers, designers, and so on. What tooling do we need to manage their workflow? - How do AI agents change the workflow of machine learning engineers and data scientists? For example, how can we use agents to accelerate exploring data, identifying hypotheses, and testing them? I’m excited to explore these and other questions about the future of software engineering at AI Dev. I expect this to be an exciting event. Please join us! [Original text: The Batch newsletter.]