How can companies win scarce AI talent against better-funded competitors?

Harry Stebbings · Sep 12, 2025

B2B AI hiring will be the single biggest problem in 2025 and 2026, and companies that aren't OpenAI, Cursor, Anthropic or Meta have little chance of competing for AI talent even with an exciting vision, because they lack the budget.

Meta is paying $10M for an AI engineer, so vision without budget doesn't win candidates.

59:14 20VC: Why AI SDRs are BS and Do Not Work | How to Use AI in Your Sales Team and Process to Win Today | What Skills Do All New Reps Need to Have in an AI First World with Amit Bendov, CEO @ Gong

Chad Peets · May 23, 2026 · hedged

The 'come here to be developed' recruiting pitch is harder to land today than it has ever been, and gets harder as frontier labs raise offers

Ten years ago you could sell joining a John McMahon company for training; now candidates answer that they can make five times the money at Anthropic

Scope: difficulty scales with the size of competing offers

27:04 20Sales: The $100M CRO Bubble: Why Anthropic Are Causing a Comp Crisis | Why You Should Never Hire From Salesforce or Service Now | How to Hire, Train and Forecase in a World of AI with Chad Peets and Chris Degnan

Harry Stebbings · May 23, 2026

Traditional SaaS companies also can't compete on career development, because they can't offer the learning trajectory of being at the coalface at Anthropic

46:02 20Sales: The $100M CRO Bubble: Why Anthropic Are Causing a Comp Crisis | Why You Should Never Hire From Salesforce or Service Now | How to Hire, Train and Forecase in a World of AI with Chad Peets and Chris Degnan

Clem Delangue · May 12, 2023 · hedged

The biggest challenge for AI-first startups right now is hiring the hybrid science-plus-engineering profile and assembling the right cofounders and early team.

There is intense competition for these people and companies have raised so much money that salaries for the really good people are insane.

Scope: 'probably right now'

25:16 20VC: Why The Future of AI Is Open Not Closed, Why We Are Years Away From AI Being Autonomous, Why AI Founders Do Not Need to Move to the Valley & Why Founders Should Not Meet Investors in Between Rounds with Clem Delangue @ Hugging Face

Clem Delangue · May 12, 2023 · hedged

The hardest role to hire for is machine learning engineers who can build new AI architectures and train state-of-the-art models — perhaps only 50 to 100 people in the world have done it

Very few people have that track record, making supply extremely short, though more people who have never done it before will be able to do it now

Scope: headcount estimate is his own approximation; expects the pool to grow

44:12 20VC: Why The Future of AI Is Open Not Closed, Why We Are Years Away From AI Being Autonomous, Why AI Founders Do Not Need to Move to the Valley & Why Founders Should Not Meet Investors in Between Rounds with Clem Delangue @ Hugging Face

Harry Stebbings · Jun 22, 2026 · hedged

The best talent will choose employers offering the most expansive frontier models and biggest token budgets, making model access effectively an employee benefit

19:28 20VC: Nikesh Arora on the Frontier Model Problem: Breadth vs Depth | The Future of Token Costs | Memory Becoming the Moat | Where Value Accrues: Infra, Models, or Apps? | Why Enterprise AI is Not Ready & Systems of Record vs Systems of Intelligence

Mike Mignano · Jul 6, 2026

The best developers will choose startups over incumbents, and mission-driven startups in particular will now win talent in a way they haven't needed to for the past few years

Incumbents constrain model budgets; and with so much capital sloshing around the ecosystem recently, companies haven't needed to be mission driven — now they will and it will work to their favour

24:50 20VC: Why Now is the Time for the Application Layer | Why OpenAI & Anthropic Won't Win the App Layer | Why Startups Should be TokenMaxxing | Why VCs Should Reduce Weighting on Price & Ownership in an Age of AI with Mike Mignano, USV

Mati Staniszewski · Sep 8, 2025

ElevenLabs can retain top researchers against hundred-million-dollar offers because the equity upside is just getting started, the gap from research to production is near-immediate rather than blocked by corporate red tape, and a small elite team learning from each other is something big labs can't guarantee

big companies optimise for a lot of people rather than necessarily the right people, and their internal process slows research reaching production

16:14 20VC: ElevenLabs Hits $200M ARR: The Untold Story of Europe's Fastest Growing AI Startup | The Real Cost of AI from Talent to Data Centres | How US VCs are in a Different League to Europeans | The Future of Foundation Models with Mati Staniszewski

Brendan Foody · Sep 15, 2025

Startups can compete for top AI talent against nine-figure cash offers by pairing mission with rapidly appreciating equity, which builds a base of missionaries rather than mercenaries

Purpose includes the economic upside tied to the mission; startups can't pay $100M liquid but equity grants appreciating quickly let people capture that upside

Scope: still need to reach parity on economics

42:11 20VC: Mercor: From $1M to $500M in 17 Months: The Fastest Growing Company in the World | How to Think About Margins and Revenue Sustainability in AI | Why Evaluation Benchmarks in AI are BS Today with Brendan Foody

Jonathan Ross · Feb 17, 2025

Groq deliberately never offers the highest salary, hiring on mission and equity upside instead

Winning a bidding war means the person leaves for the next higher offer — there's no loyalty or belief in the mission; mission-oriented people are far easier to manage and don't complain about perks

47:53 20VC: NVIDIA vs Groq: The Future of Training vs Inference | Meta, Google, and Microsoft's Data Center Investments: Who Wins | Data, Compute, Models: The Core Bottlenecks in AI & Where Value Will Distribute with Jonathan Ross, Founder @ Groq

Chad Peets · May 23, 2026

Traditional SaaS companies cannot compete financially with Anthropic for sales talent and shouldn't try to counter their offers

What Anthropic pays is so far above the rest of the market that countering is not viable

45:48 20Sales: The $100M CRO Bubble: Why Anthropic Are Causing a Comp Crisis | Why You Should Never Hire From Salesforce or Service Now | How to Hire, Train and Forecase in a World of AI with Chad Peets and Chris Degnan

Amit Bendov · Sep 12, 2025

Gong will not pay $5M for AI engineers because it is an AI application company, not a foundation model company, and isn't competing in the same talent market as labs like Cursor.

Gong uses AI rather than building foundation models; the goal is for every Gong engineer to become excellent at AI, not to win a frontier-lab comp war.

59:36 20VC: Why AI SDRs are BS and Do Not Work | How to Use AI in Your Sales Team and Process to Win Today | What Skills Do All New Reps Need to Have in an AI First World with Amit Bendov, CEO @ Gong

Jesse Zhang · Sep 19, 2025

Startups like Decagon don't really compete for talent with Anthropic, Meta or Cursor, because people who want to work at large companies are a different population from those who want an early-stage company; the real challenge is the sheer number of companies hiring

Candidate self-selection means the pools barely overlap; so the job is being clear about your unique advantage rather than matching cash

Scope: hiring is still a big challenge overall

31:58 20VC: Why 90% of Founders Build Startups Wrong | Why AI Growth Rates are Sustainable & Remote Work is BS and the AI Talent War | Competing with Brett Taylor and Sierra: Who Wins the Customer Service War with Jesse Zhang, Decagon

Joelle Pineau · Nov 3, 2025

AI talent is expensive but deserves to be compensated fairly; someone who joins primarily for the money is rarely the right hire

53:17 Pay fairly but screen out money first candidates

Shiv Rao · May 16, 2026

The AI talent market is as hard as everyone says, but mission-driven 'meaning' companies at scale can still win candidates who are already financially independent.

Purpose releases oxytocin for candidates — saving clinicians' time, making healthcare deflationary, and saving lives gives post-money people a reason to give their best years.

37:57 Mission wins financially independent candidates

Brendan Foody · Sep 15, 2025

Current AI talent economics exceed what the speaker imagined a couple of years ago, which amplifies the importance of having a strong purpose rather than just paying people well, since many companies can pay well.

Lots of companies can pay people well, so compensation alone no longer differentiates

41:42 Purpose differentiates when pay parity is achievable by many

Adam Foroughi · Apr 27, 2026

Whether compute is the deciding factor for attracting researchers depends on the space: it matters for large language models, but recommendation system work is not compute-bound, and even in LLMs Anthropic is producing the best models and products without investing the most in compute.

Anthropic got there through good culture, good people and tight focus on what they were going after; recommendation researchers are bound by curiosity and application of techniques rather than compute.

54:49 Compute access matters only in some research areas

Matan Grinberg · Jun 13, 2026 · hedged

Being a highly opinionated organization lets you recruit strong AI talent who aren't trying to maximize their market compensation

People who like the opinionated stances the company takes self-select and don't chase the maximum dollars available in the market

25:44 Opinionated identity self selects talent who do not chase max pay

Harry Stebbings · Jun 20, 2026

Flexport is at a talent-acquisition disadvantage because it competes for engineers against OpenAI, Anthropic and other AI companies that are more attractive to candidates

As good a business as Flexport is, it is not as 'sexy' as the hottest AI companies

36:03 Ai lab prestige outdraws non ai companies

Alexander Embiricos · Feb 21, 2026

The war for talent is incredibly fierce, and even a company with a brand as strong as OpenAI has to put enormous effort into closing candidates

You don't just get whoever you want for free, even with a strong brand

49:00 Even the strongest brand must work hard to close candidates