Chalmers Brown

The hottest role in AI startups right now isn’t Forward Deployed Engineers. It isn't GTM Engineers. It’s Deployment Strategists. Decagon calls it an “Agent Product Manager.” Harvey calls it a “Solutions Architect.” Palantir Technologies has had versions of this role for years. And the salaries are climbing fast: - Decagon: $200k–$285k - Palantir Technologies: $120k–$200k - Figma: $150k–$260k - Ramp: $100k–$180k - Harvey: $190k–$260k So who are these people? They are usually pseudo-technical -- CS or engineering majors, or folks with technical work experience. Many come from 2 years in consulting, IB, or PE, then jump into startups to get their hands dirty. They are young, hungry, polished, and comfortable being in front of customers. What do they actually do? They make sure enterprise AI deployments succeed. A $100k+ deal does not survive on a nice pitch or a self-serve onboarding flow. It survives if the customer sees value in the pilot. That means: - Embedding directly with the customer - Designing prompt logic for specific workflows - Working with engineering to align integrations and data flow - Helping exec teams define their AI roadmap - Running feedback loops into product and GTM Why does this role matter so much? Because enterprise AI is messy. Integrations, data transfer, and adoption make or break a deal. Most buyers are using AI for the first time, and each has unique workflows. Deployment Strategists bridge that gap. They own the outcome. They are accountable for making pilots successful, which often means millions in revenue down the line. At Conversion, Sam Bochner has been leading this work for us. We are now thinking about scaling it into a full team. Because a few successful pilots can fund an entire department, and the cost of failed deployments is too high to ignore. Is this just a rebrand of customer success? Not really. Success is about answering tickets and renewals. Deployment Strategy is about going deep with a few enterprise accounts, extracting maximum value, and ensuring the pilot closes into a multi-year contract. Call it Agent PM, Solutions Architect, or Deployment Strategist. Whatever the title, this is becoming one of the most important roles in AI SaaS.

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We at Blitzscaling Ventures are proud to invest in Atrios, an a16z portfolio company where we saw CEO Taylor Offer demo the product at the a16z Speedrun Demo Day. Atrios is an AI-powered network intelligence platform that maps who knows who and makes those relationships actionable for go-to-market teams. How it works: -Tech vendors can post offers and specify the types of roles they want to connect with. -Connectors (often founders, VCs, business development professionals between roles, or highly connected individuals) can peruse the offerings and choose the best fits. -The connectors reach out to their prospects for a mutually agreed-upon introduction. -The tech vendor gets a qualified, warm intro to a lead. The connector gets compensated. The business decision-maker accelerates their decision-making process. -All three parties benefit: the vendor, the connector, and the business decision-maker, which is why the company is cleverly called “A-Trios,” Atrios. And yes, Taylor Offer that's his actual given name, perfect for using AI for modern business development. Link to our post in comments

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Yes, I’ve read the Culper short report on AppLovin. My thoughts: No, it’s not revelatory. Pre-loads and one-click installs on Android are common practice. Digital Turbine and ironSource offer similar products. App developers pay on app open. In fact, there’s no way to confirm the install absent an open. AppLovin also offers ROAS bidding. The notion that Google Play would be unaware of any malicious activity by AppLovin, the largest in-app broker ad network, is not credible. AppLovin is more than a decade old. Just because you’ve never heard of it doesn’t mean it’s a young company. Regarding front-running Meta spend: given the scale of AppLovin’s eCommerce advertisers’ Meta spend, they can necessarily measure incrementality. They wouldn’t scale on AppLovin if they didn’t see incrementality. I also don’t see how genuine front-running would be possible in an auction for in-app inventory. Further, it’s obvious why performance across the channels would be correlated. Full disclosure: I have a small, long-dated call position on AppLovin that amounts to <5% of my PA (notional). I have no commercial relationship with the company.

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We’ve raised $270 million in Series B funding for Bedrock Robotics to keep building the future of autonomous construction. This round was co-led by CapitalG, and the Valor Atreides AI Fund (Valor Equity Partners / Atreides Management, LP), with participation from Xora Innovation, 8VC, Eclipse, Emergence Capital, Perry Creek Capital, NVentures (NVIDIA venture capital arm), Tishman Speyer, Massachusetts Institute of Technology, Georgian, Incharge Capital Partners, C4 Ventures, and others—bringing our total funding to over $350 million. Thank you to Michael de la Merced and The New York Times for this morning's thoughtful coverage in Dealbook, linked in the comments below. The timing here matters. We're entering what may be the largest infrastructure buildout in history—data centers, energy systems, advanced manufacturing, and long-overdue modernization of roads and bridges. The capital and urgency is finally there, but construction needs nearly 800,000 workers over the next two years just to keep pace with today’s demands. This funding helps us scale our development and deployments, accelerating toward our first operator-less excavator work on partner sites this year. It's a first step toward a future where fully autonomous fleets could operate as coordinated systems, helping contractors take on more work and changing how they plan, staff, and build. Thank you to our investors, advisors, and industry partners building alongside us—and to the Bedrock team for enabling this enormous opportunity.

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Lucas and Thomas founded Deepnight (YC W24) to replace analog night vision systems with software. Their models are able to render images like the one on the right at 90fps on commodity hardware.

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Founders: every rule (about fundraising and everything else) is artificial and meant to be broken. For example, consider the “rule” that the lead investor should invest at least X% of the entire round. It’s BS. For example, the amazing Kirsten Green led Bonobos’ $30m Series C round with $1m (and helped the founder raise the remaining $29m). Ignore the so-called rules. Do the right thing for your company. Be the exception.

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Two trends in fundraising that I’m seeing on a daily basis: 1/ The "we'll monetize later" era for infrastructure startups is dead "We'll figure out revenue once we have users" / "we're focused on adoption first"/ "monetization comes later" This worked in 2021. It doesn't work now. Today’s market won’t reward research organizations or companies that believe in perfection over getting it in users' hands. If you don't have a clear path to revenue… you won't get funded. period. VCs aren't writing checks hoping you'll figure it out later. 2/ "Vibe ARR" is everywhere Remember Jasper? hyper growth, but the model companies ate them alive. We're seeing this again. Companies growing really quickly on point-in-time technology that isn't defensible These companies look amazing on paper. Growth charts going up and to the right. But if you think models are getting better and becoming platform companies, many solutions become obsolete. 

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The big labs are expansive in their product ambition, especially since foundation models have largely improved in lockstep - in order to compete with them you have to do things they won’t which are: - building a very rich software ecosystem around a primitive - orchestration across multiple models - going insanely deep on product and growth for a narrow vertical domain

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Fullstack startups are the latest craze: Marc Andreessen talked about this phenomenon on Jack Altman's latest podcast Today Browserbase launched Director.ai for consumers to automate the web This follows Vercel launching @v0 for consumers to build sites and apps Both of these companies are infrastructure (picks and shovels) providers that have now moved "up the stack" to launch consumer applications on top of their infra This is the latest in vogue playbook following: Compound startups (multi-product - i.e. Rippling) Layer cake vertical startups (SaaS+Payments+Lending - i.e. ServiceTitan) Links in comments: Jack altman Marc podcast Director.ai launch video Paul Klein IV, Guillermo Rauch, CRV

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