Chase Roberts

This 👇… 💥!

@venturetwins this product is so legit

Truly blown away by a new AI image model launching this week ✨ Finally, you can generate photos that actually look like you! It's so much better than everything I've tried - from LoRAs to NB Pro. Onboarding some early testers. DM or comment if you want access 👀

@netcapgirl @eriktorenberg @a16z Just when you think the team can't get any stronger... excited to have you!

i’ve spent enough time on the internet to know it’s the most important place in the world. it’s not separate from real life anymore. it is real life. i’m joining @eriktorenberg on the @a16z new media team to help shape the narrative arc of the future

🚨 New: Excited to announce we @a16z are leading @deeptuneai’s Series A. RL environments are becoming both the bottleneck and the unlock for training the next generation of frontier AI models. The shift is clear: from static datasets to dynamic, engineered environments where models learn to write code, perform knowledge-work tasks, and fully control computers end-to-end. Deeptune is building this layer from the ground up and is already driving progress with top AI labs. Learn more about Deeptune and @timlupo:

@JenniferHli Very excited for this team. They’ve had such a huge impact on the Python ecosystem.

Astral has built some of the most beloved open source projects. It truly changed how developers are using and seeing Python. Many people told me, they love Python again because Uv , Ruff and Ty. I've enjoyed every moment partnering with Charlie & team since leading the series B (which we’ve never announced). Charlie is one of the kindest soul I know. When it comes to building, he pours everything in, and won’t settle until reaching perfection. You’ll be such an amazing leader wherever you go. OpenAI is very lucky to have you. Excited to see this team bring their developer obsession to Codex. Congrats @astral_sh @charliermarsh!

@seema_amble The stats blew my mind

@MarianaMinerals this is so legit

Mariana Stealth 2 is now Mariana Copper One! We’re excited to launch the world’s only autonomy-first mine and refinery. This is an important step toward rebuilding critical mineral supply chains. Huge credit to our team, this is just the beginning. marianaminerals.com/news/copper-one

@martin_casado They lost me at Fremont. “Happiness” in the East Bay is getting to San Francisco in <30 mins.<

0. Woodside

@justmazer @bhorowitz @speedrun 10/10

a verbatim essay I wrote in 2013 - good recruiter bad recruiter - before ever knowing anything about a16z or @bhorowitz - crazy full circle that I now lead talent for @speedrun THE ORIGINAL My recruiter-focused take on the famous Good Product Manager/Bad Product Manager by Ben Horowitz. Good recruiters have intimate knowledge of the domain in which their company competes, the human resource market that serves that domain, and the talent bar across the competing businesses in that space. Good recruiters know salary guidelines for the big players and small players alike. Good recruiters know the level of talent available from particular companies; this informs their targeting approach and tells them to avoid certain talent pools. Good recruiters understand the organizational structure of businesses within their domain; they utilize this knowledge to avoid searching for candidates based on title, which is fully respective of employer. Good recruiters are in-tune with their hiring managers and the business they support. Good recruiters understand what drives hiring decisions and optimize toward candidates that will produce results. Bad recruiters never take time to understand the team, their current projects, where the need has come from, or what opportunity the position represents for the long term. Good recruiters are truly interested in their business and how the teams they represent do their jobs; they understand the underlying technology (IE, they read esoteric explanations of the difference between SQL and NoSQL DB types, or seek to understand the differences between affiliate, CRM and direct marketing (and many more types)) and the day to day function of different contributors throughout the organization. Bad recruiters have no interest in, and make no attempt to learn about, the business, as they incorrectly deem themselves imposters to the machinations outside of recruiting. Bad recruiters blanket across all companies in their contacting approach, hoping a numbers game yields results. Bad recruiters search by title, but take no time to understand how incongruous certain roles, even with similar titles, might be throughout the space. Bad recruiters, as a result of their lack of compensation knowledge, engage with candidates, at the behest of their stakeholders (hiring managers), who are very likely to reject offers. Bad recruiters blame their inability to produce on hiring managers with unrealistic expectations and on the compensation norms of the company for which they work. Good recruiters understand that even with the best domain knowledge, recruiting is still a numbers game. Good recruiters seek to contact a minimum of 25 new candidates on average per day. Bad recruiters become complacent when they have a burgeoning pipeline and misunderstand the feast and famine cycle of recruiting. Good recruiters find a templated approach, thus reducing contact time, that still manages to make candidates feel catered to; and do this while achieving response rates exceeding 25%. Bad recruiters send a blanket email to thousands of candidates, yielding dismal response rates below 15% and exasperating an already perturbed audience. Good recruiters know that their first call with a candidate is integral to success and placement; as such, they value generating a commanding narrative of the company they represent, it’s opportunity in the space, and how that opportunity extends to a potential candidate. Bad recruiters jump straight into the pitch they’ve generated. Good recruiters force candidates, even those cultivated by cold contact, to speak to their aspirations, goals and motivators before starting in on a pitch. Good recruiters utilize information provided by candidates to cater to candidates’ interests throughout the entire interview process. Bad recruiters don’t ask questions; they just attempt to sell. Good recruiters understand that gaining the attention of a candidate is only the very beginning of a long road riddled with potential quagmires; they do not cross any requisition off the list until they have a butt-in-seat. Good recruiters advise hiring managers to act on real opportunities when they arise, even if they are at the beginning of a search or if some other early-phase candidate seems marginally better than another that has concluded all phases of interviews (1 in the hand, 2 in the bush). Good recruiters employ their knowledge of the talent economy to illustrate the trade off entailed by hiring a candidate that requires minimal training vs. the reality of waiting 3–6 more months for a particular candidate that checks every single box. Bad recruiters are assertive with hiring teams and hiring managers before gaining credibility. Bad recruiters forget that their goals are often perceived as perverse by the hiring teams they support. Good recruiters know they are looked upon with leery eyes, and take time to gain credibility; then they begin leveraging that credibility by setting expectations and gently pressuring hiring managers to make tough decisions. Good recruiters, despite having leverage and credibility, quickly jettison candidates that fail to meet the expectations of the hiring team; they do this even if the pedigree of that candidate is highly desirable. Good recruiters rarely “back” candidates. Bad recruiters pitch candidates to hiring managers as aggressively as they pitch opportunities to those candidates. Good recruiters set and manage expectations of hiring managers and leadership teams; they either A.) push back when an ask is unreasonable (too many candidates, too little time) or B.) ask for additional resources. Bad recruiters say they can produce against the ask and only later come back to ask forgiveness for their failure. Good recruiters force planning exercises if no other method for planning exists; they meet regularly with leadership to understand quarterly hiring goals and to prioritize current needs. Good recruiters provide clear guidance on the difficulty of certain searches, how that will impact time to fill, and allow the leadership team to make tradeoffs on prioritization (1 exec in 3 months, or 12 mid-level resources in the same time). Bad recruiters do exactly what they are told, often suffering disastrous outcomes both for themselves and the business. Good recruiters set and enforce SLA’s on feedback for candidates, and shepherd processes as quickly as possible. Bad recruiters allow themselves to become hamstrung by laggard or indecisive hiring managers. Good recruiters know they are competing with other opportunities, and that delaying process only generates more headwinds against any particular process. Good recruiters seek to maximize the impact of all three hiring channels; referral, applicant and cold outreach. Bad recruiters attempt to double down on particular channels. Good recruiters do not marry to any particular tool or tactic; they remain versatile and try different techniques. Bad recruiters forget or abstain to innovate. Good recruiters, though, don’t wander too deep into the forest of innovation; they continue to employ tried and true techniques for most of their time while experimenting with a minority of their time. Good recruiters provide clear perspective on the nexus of inputs that drive the success of talent acquisition. Specifically, they illuminate how talent supply, interview process, compensation and skills expectation can drastically impact results. Good recruiters say with authority: “if you want to maintain a high quality bar, utilize a lengthy and arduous interview process, pay below norm, and hire for low availability talent (engineers), then you will hire very slowly and likely require a larger recruiting team.” Bad recruiters fail to understand this nexus, and thus fail to inform leadership teams of the impact of such process decisions on their hiring

$NVDA stock price over the last 10 yrs

Created with ⁦@AskPerplexity⁩

@walls_jason1 LFG!

Yesterday Mark Cuban reposted my work, DM'd me, and told me to keep telling my story. So here it is. I'm a Master Electrician. IBEW Local 369. 15 years pulling wire in Kentucky. Zero coding background. I didn't go to Stanford. I went to trade school. Every week I'd show up to a home where someone just bought a Tesla or a Rivian. And every time, someone had already told them they needed a $3,000-$5,000 panel upgrade to install a charger. 70% of the time? They didn't need it. The math is in the NEC — Section 220.82. Load calculations. But nobody was doing them for homeowners. Electricians upsell. Dealers don't know. And the homeowner just pays. I got angry enough to build something about it. I found @claudeai. No coding experience. I just started talking to it like I'd explain a job to an apprentice. "Here's how load calcs work. Here's the NEC code. Now help me build a tool that does this." 6 months later — @ChargeRight is live. Real software. Stripe payments. PDF reports. NEC 220.82 calculations automated. $12.99 instead of a $500 truck roll. I'm still pulling wire. I still take service calls. I wake up at 5:05 AM for work. But something shifted. Yesterday @vivilinsv published my story as Claude Builder Spotlight #1. Mark Cuban saw it. The Claude community showed up. And for the first time, I felt like this thing I built in my kitchen might actually matter. I'm not a tech founder. I'm a dad who wants to coach little league and be home for dinner. I just happened to build something that helps people. If you're in the trades and thinking about using AI — do it. The barrier isn't technical skill. It's believing you're allowed to try. EVchargeright.com

@Tesla my FSD plowed over some small plastic road humps and popped two of my tires. Made for a very long afternoon and cost over $1k to repair. Can I get a credit or something?

@sarahdingwang @RJScaringe @Rivian This is the future of industrial automation

Very few founders have built and scaled a vertically integrated hardware company in the modern era. @RJScaringe is one of them. At Mind, he’s building the robotics partner @Rivian wanted but couldn’t find. We believe robotics is just starting to enter its compounding phase. The teams that integrate intelligence, hardware, and deployment into a coherent industrial platform will define the next generation of enduring companies. Real world deployment is not the final step; it forces clarity in every step, from research to reliability. Mind is setting out to build that platform. We are incredibly excited to partner with RJ and the entire Mind team. @DavidGeorge83 @RaghuRaghuram @jamiedsully @espricewright @JacobZietek @appenz

@sarahdingwang @assaf_rappaport woo! happy for this team

.@assaf_rappaport, Yinon Costica, Ami Luttwak, and Roy Reznik are in a league of their own. The way they care for their customers, team, and investors is unparalleled. (and I still think they’re underrated) It’s no surprise this team built a platform people genuinely love, even in one of the most skeptical industries in tech. One CISO told us they’d quit if Wiz were removed. Generational run. And it’s just the beginning as they join @GoogleCloud to combine powerful environmental context, frontier AI research, and multi-cloud DNA to secure AI end to end. Congrats on this exciting new era. @a16z is honored to have been a part of the last one. @justin_kahl @zanelackey

Well said. This got me thinking about the compounding effect of aggregated human intelligence. The whole is often greater than the sum of its parts. Some of humanity’s most complex inventions, like oil refineries, rocket launch systems, and semiconductor fabs, only exist because human beings learned how to coordinate knowledge at scale. Compute can amplify that process, but scaling compute alone appears to run into diminishing returns faster than scaling organized human effort.

@TheRestHistory the Samuel Johnson episodes for the members club have ads! 😔

@Amank1412 Sick. Where are they pulling the data feeds?

Someone built an open source F1 replay timing tool that lets you watch races on delay without spoilers while still seeing live timing, telemetry, and pit-stop predictions. It can even sync with your TV using a photo of the timing tower.

Who put the interns in charge of the graphics at F1 TV? *stop count not working *tire graphic bleeding into the next visual element @F1 @AppleTV

@katiekirsch @a16z @liangsays @eriktorenberg @humford new media for the win! let's gooo

the @a16z new media fellowship is back for round 2! 🎉 apps are live now to join the new, second cohort: a16z.fillout.com/t/2dqvGNMYi9us you know what to do 👀 cc @liangsays @eriktorenberg @humford

@NASAAdmin @a16z let's go! its this kind of ambition that accelerates the future

Yesterday, I had the privilege of speaking at the @a16z American Dynamism Summit with the builders, operators, and investors helping shape the next era of exploration. NASA has a clear mandate under President Trump’s national space policy: Return American astronauts to the Moon by the end of 2028, build an enduring presence there, and ensure American leadership in the most important strategic domain. Achieving that requires focus and disciplined execution. In the weeks ahead, the Artemis II crew will travel around the Moon. It is the next step toward returning humans to the lunar surface and building a lasting presence there. To reach that goal, we’ve recently made some changes to the Artemis program: Increasing launch cadence, standardizing hardware, and adding missions that allow us to test systems, reduce risk, and build confidence before landing. This is the same approach that carried the United States from Mercury to Gemini to Apollo. In the 1960s we launched often, learned from every mission, and improved with each step forward. That is how you build real capability in deep space. Yesterday, I also announced NASA Force, a new initiative with @USOPM to bring exceptional engineering and technical talent into NASA and help rebuild the core competencies that make missions like this possible. We want to open the search far and wide to attract the best of the best and incentivize them to leverage their skills to maintain American superiority in space. NASA changed the world in 1969 by concentrating the nation’s best talent on the hardest problems imaginable. We are doing it again.