Krishna Gade

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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YC has done a good job supporting ambitious deeptech projects. Seeds sowed over many years are starting to sprout in meaningful ways. Biggest support to founders (esp those building in the physical world) isn’t money - it’s the right advice, network, and peer support.

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The smartest YC founders I know are NOT raising VC money. Here are FIVE unique things they're doing instead: 1) Firing their least technical co-founder. 2) Importing/exporting used Herman Miller chairs. 3) Selling their YC office hours on Craigslist. 4) Auctioning screenshots of their Stripe dashboard as art. 5) Using Central to eliminate nonsense HR/finance work and focusing on profitability - centralhq.com What else am I missing?

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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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Ok, time for a rant. 90% of "AI Startups" aren't even AI. I've seen founders that use LLMs or have a chatbot somewhere on their site and call it an "AI startup". I've seen people who vibe code or use Cursor/Lovable and then say they have an "AI startup". I've seen people continue to build ChatGPT/Claude/Llama wrappers and call it an "AI startup". If you haven't build a custom model or used meaningful proprietary data then you aren't an AI startup, you're AI Enabled. AND THAT'S FINE. You don't have to be an AI company to solve a problem. So many companies and VCs are going to have poor performance because they have little differentiation and have claimed to build/invest in "AI Companies" and we will soon learn they are not really "AI".

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personalization at scale = laziness at scale? this is what Anshul Gupta from Actively AI dropped on our podcast and it hit HARD what's happening in your inbox right now? - "congrats on your funding! btw want some debt financing?" - "saw you visited our site, here's our demo link!" this is NOT personalization! it's thin-logic automation pretending to be human the problem? those signal platforms are just triggering sequences based on basic events: funding announcement = trigger sequence A website visit = trigger sequence B job posting = trigger sequence C Anshul got it right: this approach is DEAD what's working instead? the best humans go DEEP: 1- actual research on the business and challenges 2- conversations with team members 3- hypothesis based on real signals (not just events) the truly innovative teams aren't doing "personalization at scale" they're doing RELEVANCE at scale - and they can command premium pricing for that that's the difference between "hey {first_name}" and actually understanding what keeps you up at night are you still doing personalization? or have you evolved to relevance (and outcomes)? check out the full convo with Anshul in our podcast Agent Talk wherever you listen to podcasts

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Got a YC interview? I’ve been through it—and helped others prep. Here’s what the partners are actually evaluating you on ↓ We were interviewed by Garry Tan and Surbhi Sarna in 2023. No smiles. No nods. Incredible poker faces. We thought we blew it. Somehow got in. 9 things to keep in mind: [ 1 ] Can you teach your interviewer something new? They’ve seen every AI-powered [X] pitch by now. [ 2 ] Pre-revenue? Do you have a unique insight—or a credible plan to get one? [ 3 ] Can you show real progress since you applied? [ 4 ] Can your team actually build what you're pitching? [ 5 ] Other early-stage startups aren’t your competition. Post-PMF incumbents are. Most startups die from suicide, not murder. [ 6 ] Got a backup idea? Be ready to pitch it if they ask. [ 7 ] What they're really asking themselves is: If we give this founder $500k and 3 months to learn from the best, can they make something work? [ 8 ] Don’t memorize a script. YC partners are pro bullshit detectors. Founders are just amateurs bullshitters. [ 9 ] They also have great poker faces. Don’t read into it. Focus on clarity and conviction. Good luck if you’re interviewing. And if you’ve done it before—what else would you add?

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YC has quietly built a parallel tech ecosystem. Not just a network - an entire operating system for startups. Think about it: A YC founder can build their entire stack using only YC companies. Infrastructure, analytics, payment processing, marketing tools - it's all there. At friend-and-family prices. When you launch a product to the YC network, you get something priceless: A group of technical founders who actually understand what you're building. They become your first users, your debuggers, your evangelists. This is why PostHog is now used by 65% of new YC companies. This is why Brex dominated fintech... and why each YC batch makes the next one stronger. A true compounding advantage.

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