“Ahmad worked with me for many years developing products ... an outstanding talent with amazing discipline. I endorse him for any professional assignment.”
Ahmad Hamzawi
Menlo Park, California, United States
3K followers
500+ connections
3K followers
500+ connections
About
Ahmad Hamzawi is a tech industry veteran with 30 years of experience, having worked in…
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English
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French
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Arabic
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4 people have recommended Ahmad
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Derek Kerton
We chose a good subject for our march Autotech Council meeting, and after this year's CES, it seems even more obvious. Our meeting on the AI Defined Vehicle will show how it's a natural next step after the Software Defined Vehicle phase that we've been in Tesla launched the Model S in 2012. Now, most carmakers have SDVs. It's time to layer on the AI in user-facing roles, and in invisible functions managing the vehicle.
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Gokul Rajaram
Excited to share my conversation with Marc Baselga and Ben Erez on the Supra Insider podcast. We went deep on one of the biggest shifts happening in product leadership right now: why many experienced PMs and product execs are returning to individual contributor (IC) roles in the AI era, and why that’s not a step back, but a strategic leap forward. Other topics we discussed: -- Why the leverage equation has changed—and how managing AI agents now rivals managing people -- The critical importance of hands-on credibility in AI-native companies -- Why great PMs in the future will blend product, design, analytics, and frontend execution -- What it takes to deliver real customer outcomes (not just launch features) -- How to evaluate breakout companies—and what founders often get wrong when hiring product leaders I also shared my thoughts on: -- Joining the right company: mission, trajectory, talent density, and founder courage -- Crushing it as a “super IC”: the power of speed, ownership, and infectious energy -- Transitioning from product leader to GM or founder with the right mindset If you’re navigating your next chapter in product (or just trying to stay sharp in the AI-native world), I hope you’ll find this useful. Episode links: Spotify: https://lnkd.in/gK48PFWK Apple: https://lnkd.in/gmT265BY YouTube: https://lnkd.in/gtr4RAKd Substack: https://lnkd.in/gM38FSWc
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Allen Lieberman
Shardul Shah's post on our Series A captures something important about how we build product at 7AI. He wrote: "Its multi-agent architecture learns each environment's unique context, enabling faster, more accurate, and more consistent investigations than humans or rule-based systems." That's the product vision in one sentence. Not a one-size-fits-all solution. A platform that learns your environment, your context, your tools, and delivers outcomes specific to you. Shardul called 7AI potentially "the defining agentic security company of this new era." That's the standard our team is building toward. Every day.
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Gerard R.
The Triple Wall: Why LLMs Cannot Escape The Memory, Bandwidth and Capital Ceilings By Peter Kafka “LLMs are great, they’re useful, we should invest in them — a lot of people are going to use them,” said Yann LeCun, who’s still an AI researcher at Meta for the moment, speaking at an event in Brooklyn Sunday night. “They are not a path to human-level intelligence. They’re just not. Right now, they are sucking the air out of the room anywhere they go — and so there’s basically no resources [left] for anything else. And so for the next revolution, we need to take a step back and figure out what’s missing from the current approaches.” ~ Yann LeCun https://lnkd.in/giQSpDZ9
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Haroon Choudery
Elie Schoppik has spent his career at the intersection of education and engineering. He built early ed-tech tools that helped people actually retain knowledge, founded a Bay Area coding bootcamp that trained thousands of developers through practice and feedback, and now leads Technical Education at Anthropic. Despite all that experience, Elie says most teams are using AI wrong: they’re treating it like an all-knowing oracle instead of a tutor. This is why Elie designs prompts, examples, and workflows that treat AI as a teacher, instead of a shortcut. In our conversation, we discuss: • Why relying on AI for “fast answers” erodes judgment and verification • How to turn prompts into guided lessons • Why context engineering is the most underrated skill in 2025 • Practical exercises any team can run tomorrow to raise AI fluency • What leaders should steal from Anthropic’s approach to technical education Episode is live now — full conversation linked in the comments.
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Vishal Banthia
This is a great experiment by the Anthropic team, showcasing the "true autonomous" capabilities of LLMs. By "true autonomous," I mean that Anthropic (I believe) purposefully did not bombard the LLM with numerous tools in areas where LLMs are weak. For example, LLMs are not good in math, and performance would have been much better if they hd provided a tool like "calculate_profitability." This might have prevented the $100 opportunity miss. In AI agent development, tools bridge the gap where LLMs are not "deterministic." This is currently the MOAT in the GenAI app business: the better your tools, the more deterministic results you can provide. Only till LLMs can write their own tools on the fly and execute them where they know they are weak and using deterministic softwares (tools) to fill these gaps. https://lnkd.in/gMk3VRJv
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