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Generated Oct 22, 2026
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growth playbook · Oct 22, 2026

coreweave.com (opens in a new tab)

CoreWeave growth playbook

Diagnosis

CoreWeave is growing fast (Q2 2026 revenue up 112%, about $104 billion backlog) and is now hiring to win the next markets: agentic AI, AI training infrastructure, physical AI, partner marketing, developer relations and market research that includes AI assistants as a channel.

Much of the proof those hires need already exists but is hard to find: 75 of 115 video pages have an empty transcript, only one of 17 written case studies is about agents, the Agentic AI page names no customer, and Physical AI stories live on wandb.ai.

This playbook unlocks that proof first, fixes small trust and speed issues, then builds decision guides, a measured self-serve path, account scoring from first-party signals, and big bets on reliability data and an open evaluation harness.

Growth Score

8/10

Biggest Opportunity

Turn the customer talks, W&B stories and benchmark numbers CoreWeave already has into written, findable proof for agents, training and physical AI.

Biggest Risk

Lambda, Nebius, Crusoe, Together AI and the hyperscalers all claim the "AI cloud", so without clear proof by use case, buyers compare on price per GPU hour.

01

Start here

The three moves to make first. Each one is written up in full below.

  1. 1

    Fill the 75 empty transcript tabs, starting with the customer agent talks, and turn them into written agent proof

    Export captions for the MasterClass, Cognition and LlamaIndex talks and paste them into their Transcript tabs.

    High impact First result in 2 weeks
  2. 2

    Bring the Physical AI customer stories home from wandb.ai

    Ask the Decart and NEURA account teams for approval to adapt their W&B stories.

    High impact First result in 1 month
  3. 3

    Put named agent builders on the Agentic AI page

    Pick the five strongest agent stories and check logo permissions.

    High impact First result in 2 weeks

02

Your idea portfolio

21 ideas, grouped by when to run them. Open any idea for how to run it: the steps, who to approach, copy you can use, and how to measure it.

  • 7 ideas are marked Unexpected: plays you are unlikely to have tried.

Every idea placed by the effort it takes against the impact it could have. Quick wins sit top left; select a number to open that idea. The filters below narrow the list by status, timing, category and what Programmable can build.

Effort vs impactEach number is an idea. Select one to open it.
Impact →
Quick wins · 4Big bets · 11Fill-ins · 4Reconsider · 2
Effort →

Showing 21 of 21 ideas

This week 6

Quick wins with a clear first action.

  • 01

    The new Director of Product Marketing, Agentic AI is asked to build a customer proof program for teams "deploying agents in production". CoreWeave already has that proof on its own site, but it is locked inside video. Of 115 video pages, 75 show a Transcript tab with nothing in it, including MasterClass on multi-agent AI, Cognition on training SWE-2 with RL, LlamaIndex on context for agents, Parallel Web Systems on reliable web agents, Grammarly on vLLM inference and Willow on voice AI. Meanwhile only one of the 17 written case studies (Cohere North) is about agents, and the Agentic AI page names no customer at all.

    High impactLow effort First result in 2 weeks Director of Product Marketing

    First action

    Export captions for the MasterClass, Cognition and LlamaIndex talks and paste them into their Transcript tabs.

    How to measure it

    Customer agent stories linked from the Agentic AI page

    Now
    –
    Target
    10
    By
    45 days

    Steps

    1. 1

      List the empty pages

      The 75 video pages with an empty Transcript tab, customer talks first.

      Web team lead 1 day

    2. 2

      Generate transcripts

      Auto-transcribe from the source video and correct names and terms.

      Content marketing manager 1 week

    3. 3

      Publish

      Fill each Transcript tab and add the text to the page for search.

      Web team lead 1 week

    4. 4

      Write summaries

      A one-page story for each customer talk with the numbers the speaker gave.

      Director of Product Marketing, Agentic AI 2 weeks

    5. 5

      Get approval

      Send each summary to the speaker's company to confirm it as a reference.

      Customer marketing lead 2 weeks

    6. 6

      Link the proof

      Agentic AI page, case-study hub, inference and RL product pages.

      Web team lead 2 days

    7. 7

      Hand to sales

      A one-line proof index by use case for first-call decks.

      Director of Product Marketing, Agentic AI 1 day

    8. 8

      Measure

      Organic entrances to video pages and clicks from the Agentic AI page.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    2 weeks
    Cost
    Transcription service and editing time
    Owner
    Director of Product Marketing, Agentic AI

    Smallest test

    Fill the transcripts for three customer agent talks and link them from the Agentic AI page.

    Why it works

    Generate and edit transcripts for the 75 empty pages, starting with the 15 customer talks. For each customer talk, publish a one-page written summary (the problem, the stack on CoreWeave, the numbers the speaker gave, a quote) and link it from the Agentic AI page, the case-study hub and the matching product pages. Ask each speaker's company to approve the summary so it can count as a reference story.

    Buyers, search engines and AI assistants read text, not video. Transcripts make the talks findable for the questions agent builders ask, and the summaries give sales and the Agentic AI page named proof within weeks instead of waiting for new case studies.

    Ready to use

    ChecklistTranscript and proof pass

    [ ] Export captions for the 15 customer talks
    [ ] Correct names (models, frameworks, products)
    [ ] Fill the Transcript tab and render it as page text
    [ ] One-page summary: problem, stack, numbers, quote
    [ ] Customer approval as a reference story
    [ ] Link from /solutions/agentic-ai and /case-studies
    [ ] Add VideoObject data with the transcript
    [ ] Repeat for the remaining 60 pages

    Risks and how to handle them

    • Talks contain claims a customer would not put in writing

      Publish only the approved summary; keep the raw transcript as given on stage.

    • Machine transcripts mangle model and product names

      Edit against a glossary of CoreWeave, NVIDIA and model names.

    Evidence

    • Your websiteVideo library (all 115 /resources/videos pages checked October 21, 2026): every page has a Transcript tab, but on 75 of them it is empty. Empty ones include customer talks such as "How Grammarly Scales Real-Time Inference with vLLM on CoreWeave", "How MasterClass Builds Multi-Agent AI That Learners Can Trust", "Training Cognition SWE-2: Asynchronous RL at Global Scale", "Building the Document Context Layer for AI Agents at LlamaIndex", "Beyond the Benchmark: How Parallel Web Systems Builds Reliable Web Agents", "Building the Voice OS at Willow", "Inside Pinterest's Machine Learning Platform", Nasdaq, IBM Granite 4.0 and You.com's Nemotron agentic search; the 40 filled ones include product demos such as the ARENA demo.Source
    • Your websiteCustomer stories: the sitemap lists 17 written case studies. The hub features Cohere ("North, Agentic AI for Enterprise"), OpenAI, IBM ("80%") and Mistral AI ("2.5x Faster Training"); Cohere is the only one about agents, and none is about robotics or autonomous vehicles. Several are older stories (NightCafe, Zeet, Odyssey's McDonald's metaverse experience, Bit192 GPT-NeoX-20B).Source
    • Your websiteAgentic AI solution page: H1 "Agentic AI that paves the path to superintelligence", sections on training, inference and observing agents, "Exemplary agent inference. Validated by NVIDIA." and 11 FAQs, but no customer story or named agent builder.Source
    • HiringDirector of Product Marketing, Agentic AI (open, posted June 17, 2026): position CoreWeave "as the premier infrastructure platform for agentic AI"; build "use-case playbooks" for "autonomous coding agents, multi-agent reasoning pipelines"; and "Build and scale a customer proof program featuring case studies and reference customers across AI labs, enterprises, and high-growth AI startups deploying agents in production"; plus thought leadership "white papers, technical blogs, benchmark reports, webinars".Source
    • HiringSenior Manager, Marketing Research & Intelligence (posted September 10, 2026): "Develop research and measurement frameworks for new / emerging audience and platform discovery channels, including Generative AI / LLMs"; size TAM and SAM; "Track market share against key competitors"; identify buyer groups by use case; and "push account targeting signals into marketing automation and CRM platforms"; success includes "identifying accounts and prospects that are ready to buy".Source
  • 02

    CoreWeave is hiring its first Physical AI communications owner to build "a repeatable pipeline of customer and partner stories". The Physical AI page already names five customers, but three of the cards (Decart, NEURA Robotics, Woven by Toyota) send visitors to wandb.ai and one to a news post. There is no robotics or autonomous-vehicle story in CoreWeave's own case-study library.

    High impactMedium effort First result in 1 month Senior Manager

    First action

    Ask the Decart and NEURA account teams for approval to adapt their W&B stories.

    How to measure it

    Physical AI case studies on coreweave.com

    Now
    –
    Target
    5
    By
    1 quarter

    Steps

    1. 1

      Inventory

      Five named customers and what each W&B or news page already says.

      Senior Manager, Physical AI Communications 2 days

    2. 2

      Interview

      Add the infrastructure side to each story.

      Senior Manager, Physical AI Communications 3 weeks

    3. 3

      Approve

      Customer and partner sign-off.

      Customer marketing lead 2 weeks

    4. 4

      Publish

      Case studies with a Physical AI filter.

      Web team lead 1 week

    5. 5

      Relink

      Physical AI page cards to the new pages.

      Web team lead 1 hour

    6. 6

      Pitch

      Use two stories in trade media outreach.

      Senior Manager, Physical AI Communications 1 month

    7. 7

      Measure

      Share of voice in robotics and AV coverage.

      Senior Manager, Physical AI Communications monthly

    First result
    1 month
    Cost
    Staff time only
    Owner
    Senior Manager, Physical AI Communications

    Smallest test

    Publish the Nissan story as a full case study first, since the facts are already public.

    Why it works

    Write CoreWeave case studies for the five named customers, covering the full stack (compute, storage, W&B tracking, Launchables where used), publish them under /resources/case-studies with a Physical AI filter, and keep the W&B pages as secondary links. Use them as the first stories in the new communications program and in the launch of Physical AI Launchables.

    Proof on your own domain builds your own search and AI-assistant visibility for "GPU cloud for robotics" questions, and keeps a visitor who is evaluating CoreWeave on CoreWeave.

    Risks and how to handle them

    • Customers already approved W&B wording only

      Start from the approved text and add only new, approved facts.

    Evidence

    • Your websitePhysical AI page: five customer cards (Decart, NEURA Robotics, PhysicsX, Woven by Toyota, Nissan "reduces physical vehicle tests by 17%"). Decart, NEURA and Toyota link to customer pages on wandb.ai, Nissan to a news post; none links to a CoreWeave case study.Source
    • HiringPhysical AI hiring: a Senior Manager, Physical AI Communications, the "first dedicated communications owner for CoreWeave's Physical AI business", to "Create a repeatable pipeline of customer and partner stories across robotics, autonomous systems, industrial applications, and scientific AI" and measure "share of voice"; and a Business Development Manager - Physical AI to own partnerships with "simulation ISVs, robotics platform companies, OEMs" and the NVIDIA Physical AI ecosystem (Isaac Sim, Isaac Lab, Cosmos, Omniverse, DRIVE), with "joint reference architectures".Source
    • Your websiteCustomer stories: the sitemap lists 17 written case studies. The hub features Cohere ("North, Agentic AI for Enterprise"), OpenAI, IBM ("80%") and Mistral AI ("2.5x Faster Training"); Cohere is the only one about agents, and none is about robotics or autonomous vehicles. Several are older stories (NightCafe, Zeet, Odyssey's McDonald's metaverse experience, Bit192 GPT-NeoX-20B).Source
    • Your websiteLaunches this week: Physical AI Launchables (ready-to-run Templates for Isaac Sim, CARLA, MuJoCo, AlpaSim and Cosmos, with agent skills) and the Zero Trust AI Framework; Fully Connected 2026 sessions are on the site.Source
  • 03

    The Agentic AI page explains the closed loop and quotes NVIDIA validation, but names no customer. CoreWeave already has public agent proof: Cohere North in writing, and talks from Cognition, MasterClass, LlamaIndex, Parallel Web Systems and You.com.

    High impactLow effort First result in 2 weeks Director of Product Marketing

    First action

    Pick the five strongest agent stories and check logo permissions.

    How to measure it

    Agentic AI page contact rate

    Now
    –
    Target
    +20%
    By
    60 days

    Steps

    1. 1

      Pick stories

      Five agent builders with public talks or cases.

      Director of Product Marketing, Agentic AI 1 day

    2. 2

      Check permissions

      Logo and quote use.

      Customer marketing lead 3 days

    3. 3

      Write lines

      One outcome per company.

      Director of Product Marketing, Agentic AI 1 day

    4. 4

      Build the strip

      Agentic AI, inference and RL pages.

      Web team lead 2 days

    5. 5

      Test

      Contact rate before and after.

      Senior Manager, Marketing Research & Intelligence 4 weeks

    6. 6

      Refresh

      Add new stories as they are approved.

      Director of Product Marketing, Agentic AI monthly

    First result
    2 weeks
    Cost
    $0
    Owner
    Director of Product Marketing, Agentic AI

    Smallest test

    Add the Cohere story and two talk links this week.

    Why it works

    Add a "Who runs agents on CoreWeave" strip near the top with five logos and one-line outcomes, each linking to a case study or the talk summary from idea 1, plus a short quote. Repeat the strip on the inference and RL pages.

    Agent builders choose infrastructure from peers; named companies doing the same work answer "who else does this here?" in seconds.

    Risks and how to handle them

    • Logo permission delays

      Launch with the customers already shown elsewhere on the site.

    Builds on

    Evidence

    • Your websiteAgentic AI solution page: H1 "Agentic AI that paves the path to superintelligence", sections on training, inference and observing agents, "Exemplary agent inference. Validated by NVIDIA." and 11 FAQs, but no customer story or named agent builder.Source
    • Your websiteVideo library (all 115 /resources/videos pages checked October 21, 2026): every page has a Transcript tab, but on 75 of them it is empty. Empty ones include customer talks such as "How Grammarly Scales Real-Time Inference with vLLM on CoreWeave", "How MasterClass Builds Multi-Agent AI That Learners Can Trust", "Training Cognition SWE-2: Asynchronous RL at Global Scale", "Building the Document Context Layer for AI Agents at LlamaIndex", "Beyond the Benchmark: How Parallel Web Systems Builds Reliable Web Agents", "Building the Voice OS at Willow", "Inside Pinterest's Machine Learning Platform", Nasdaq, IBM Granite 4.0 and You.com's Nemotron agentic search; the 40 filled ones include product demos such as the ARENA demo.Source
    • Your websiteCustomer stories: the sitemap lists 17 written case studies. The hub features Cohere ("North, Agentic AI for Enterprise"), OpenAI, IBM ("80%") and Mistral AI ("2.5x Faster Training"); Cohere is the only one about agents, and none is about robotics or autonomous vehicles. Several are older stories (NightCafe, Zeet, Odyssey's McDonald's metaverse experience, Bit192 GPT-NeoX-20B).Source
    • HiringDirector of Product Marketing, Agentic AI (open, posted June 17, 2026): position CoreWeave "as the premier infrastructure platform for agentic AI"; build "use-case playbooks" for "autonomous coding agents, multi-agent reasoning pipelines"; and "Build and scale a customer proof program featuring case studies and reference customers across AI labs, enterprises, and high-growth AI startups deploying agents in production"; plus thought leadership "white papers, technical blogs, benchmark reports, webinars".Source
  • 04

    On the pricing page, the table header says "Inference Single GPU Price", but every mobile card calls it "Inference Single CPU Price". The sitemap also lists /topics/test, a live page whose H1 is "Test" with no title, and /pricing/classic still sits next to /pricing. coreweave.com answers without redirecting to the www host the pages declare as canonical.

    Medium impactLow effort First result in 1 week Web team lead

    First action

    Change the mobile card label today.

    How to measure it

    Empty-title pages in the sitemap

    Now
    –
    Target
    0
    By
    2 weeks

    Steps

    1. 1

      Fix the label

      Mobile cards on /pricing.

      Web team lead 1 hour

    2. 2

      Unpublish the test page

      And drop it from the sitemap.

      Web team lead 1 hour

    3. 3

      Decide on classic pricing

      Redirect or label as legacy.

      Staff Product Manager, AI Inference 1 day

    4. 4

      Redirect the bare domain

      coreweave.com to www.

      Web team lead 1 hour

    5. 5

      Add a check

      Monthly crawl for empty titles and test pages.

      Web team lead 1 day

    6. 6

      Confirm in Search Console

      Removed and redirected URLs.

      Web team lead 2 weeks

    First result
    1 week
    Cost
    $0
    Owner
    Web team lead

    Smallest test

    Fix the label and unpublish the test page.

    Why it works

    Correct the mobile label, unpublish /topics/test and remove it from the sitemap, redirect /pricing/classic to /pricing (or mark it clearly as legacy with a link), and redirect coreweave.com to www.coreweave.com. Add a monthly check for empty titles and test pages.

    Engineers comparing GPU prices read labels literally, and a test page or two pricing pages in search results looks careless for a company selling reliability.

    Risks and how to handle them

    • Old links to classic pricing

      Redirect so they still land on current prices.

    Evidence

    • Your websitePricing page: on-demand NVIDIA GB200 NVL72 at $42.00 an hour, HGX B200 at $68.80 (spot $34.11), RTX PRO 6000 at $20.00; GB300 NVL72 and HGX B300 on-demand are "Contact sales". The table header says "Inference Single GPU Price", but the 12 mobile cards label the same figure "Inference Single CPU Price".Source
    • Your websiteSitemap (892 URLs): 244 blog posts, 190 resources, 68 Fully Connected sessions, 59 events, 23 topic explainers ("What is Slurm?", "What is vLLM?") plus /topics/test, a live page with the H1 "Test" and an empty title and description; /pricing/classic is still live next to /pricing; an "AI cloud comparison guide" ebook and an "AI cloud TCO pricing comparison" report. coreweave.com answers without redirecting to the canonical www host. The docs site publishes llms.txt and an MCP endpoint; www.coreweave.com/llms.txt is a 404.Source
  • 05

    Real Chrome visitors see the largest element after 2.76 s and a layout shift of 0.24, both above Google's "good" limits; on a lab mobile test the H1 text itself does not paint until 13.9 s and the score is 29. Text that late usually means the hero waits on fonts or a reveal script.

    Medium impactMedium effort First result in 1 month Web team lead

    First action

    Turn off the reveal animation on the hero H1 in a staging copy and re-test.

    How to measure it

    Site LCP p75 / CLS p75

    Now
    –
    Target
    under 2.5 s / under 0.1
    By
    1 quarter

    Steps

    1. 1

      Profile

      What delays the H1 and what shifts.

      Web team lead 2 days

    2. 2

      Hero first

      H1 without animation dependency.

      Web team lead 3 days

    3. 3

      Fonts

      Preload and fallback.

      Web team lead 1 day

    4. 4

      Reserve space

      Announcement bar and logo strips.

      Web team lead 2 days

    5. 5

      Defer the rest

      Menu and below-fold media.

      Web team lead 1 week

    6. 6

      Verify

      PageSpeed and Chrome field data.

      Web team lead 4 weeks

    First result
    1 month
    Cost
    Developer time
    Owner
    Web team lead

    Smallest test

    Ship the hero fix alone and compare lab LCP.

    Why it works

    Render the H1 and hero copy in the first HTML response without waiting for animation, preload the headline font with a fallback, reserve space for the announcement bar and logo strips, and lazy-load the mega-menu and below-fold media. Re-test the homepage, pricing and product pages.

    A faster first view keeps more paid and event traffic, and the improvement already under way (24% faster LCP) shows it is fixable.

    Risks and how to handle them

    • Design team wants the animation

      Keep it, but start it after the text has painted.

    Evidence

    • Google PageSpeedHomepage on mobile: performance 29 (desktop 33), lab Largest Contentful Paint 13.9 s with the H1 text as the LCP element. Real Chrome visitors (75th percentile, whole site): LCP 2.76 s and layout shift 0.24, both above Google's "good" limits (2.5 s, 0.1); interaction 95 ms is good. LCP has improved 24% over the period.Source
    • Your websiteHomepage: "The essential cloud for AI"; "The only AI cloud to earn SemiAnalysis' Platinum ClusterMAX rating three times", "9 of 10 leading foundation model providers rely on CoreWeave", "First NVIDIA Exemplar Cloud for training on NVIDIA GB200 NVL72", "Up to 98% effective training time", "Minutes to a human solving your issue". Forge is "free to build with any cloud, model, or framework". Menu programs: ARENA, Direct-to-Expert, Ventures, Academic Research, Zero Egress Migration.Source
  • 06

    The new research lead is asked to build measurement for "Generative AI / LLMs" as a discovery channel and to track share against competitors. Lambda, Nebius, Crusoe, Together AI and Runpod all claim the AI cloud. Nobody yet knows how often assistants name CoreWeave for training, inference, agents or robotics questions.

    High impactLow effort First result in 2 weeks Senior Manager

    First action

    Draft the 60 questions with sales and solutions architects.

    How to measure it

    Assistant share of voice, training questions

    Now
    –
    Target
    +10 points
    By
    2 quarters

    Steps

    1. 1

      Write questions

      60 by use case and persona.

      Senior Manager, Marketing Research & Intelligence 3 days

    2. 2

      Run the baseline

      Main assistants, logged answers and citations.

      Senior Manager, Marketing Research & Intelligence 1 week

    3. 3

      Score

      Share of voice by use case and rival.

      Senior Manager, Marketing Research & Intelligence 2 days

    4. 4

      Find gaps

      Questions where rivals win and the pages they cite.

      Senior Manager, Marketing Research & Intelligence 2 days

    5. 5

      Brief owners

      Gaps to product marketing and content.

      Senior Manager, Marketing Research & Intelligence 1 day

    6. 6

      Repeat

      Monthly, same questions.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    2 weeks
    Cost
    Analyst time
    Owner
    Senior Manager, Marketing Research & Intelligence

    Smallest test

    Run 15 training questions this week and log who is named.

    Why it works

    Write 60 buyer questions across the four use cases and three personas (research lead, platform engineer, CTO), run them monthly in the main assistants, and record which providers are named and which pages are cited. Report share of voice by use case and the pages that win, and feed gaps into ideas 1, 2 and 12.

    A baseline turns "AI visibility" into a number the team can move, and the cited pages show exactly what content to build.

    Risks and how to handle them

    • Answers vary run to run

      Run each question several times and use averages.

    Evidence

    • HiringSenior Manager, Marketing Research & Intelligence (posted September 10, 2026): "Develop research and measurement frameworks for new / emerging audience and platform discovery channels, including Generative AI / LLMs"; size TAM and SAM; "Track market share against key competitors"; identify buyer groups by use case; and "push account targeting signals into marketing automation and CRM platforms"; success includes "identifying accounts and prospects that are ready to buy".Source
    • Competitor researchRivals' own homepages: Lambda, "Supercomputers for training and inference"; Nebius, "The Ultimate AI Cloud"; Crusoe, "The AI factory company"; Together AI, "the AI Native Cloud"; Runpod, "The AI Developer Cloud". Hyperscalers (AWS, Google Cloud, Azure) sell GPU capacity alongside everything else.Source
    • Your websiteSitemap (892 URLs): 244 blog posts, 190 resources, 68 Fully Connected sessions, 59 events, 23 topic explainers ("What is Slurm?", "What is vLLM?") plus /topics/test, a live page with the H1 "Test" and an empty title and description; /pricing/classic is still live next to /pricing; an "AI cloud comparison guide" ebook and an "AI cloud TCO pricing comparison" report. coreweave.com answers without redirecting to the canonical www host. The docs site publishes llms.txt and an MCP endpoint; www.coreweave.com/llms.txt is a 404.Source

This quarter 10

The core plays for the next three months.

  • 07

    The training PMM is hired to tie CKS, SUNK and SUNK Anywhere into one story and to explain where Ray, SkyPilot and Kueue fit. Today there are separate product pages and a "What is Slurm?" explainer, but no page that helps a platform team choose.

    High impactMedium effort First result in 1 quarter Senior Product Marketing Mana…

    First action

    Outline the guide with two solutions architects.

    How to measure it

    Guide-assisted training opportunities

    Now
    –
    Target
    30% of new ones
    By
    2 quarters

    Steps

    1. 1

      Outline

      Team types and decision points.

      Senior Product Marketing Manager, AI Training Infrastructure 1 week

    2. 2

      Gather numbers

      SUNK proof points with methods.

      Senior Product Marketing Manager, AI Training Infrastructure 2 weeks

    3. 3

      Write

      Guide with trade-offs.

      Senior Product Marketing Manager, AI Training Infrastructure 3 weeks

    4. 4

      Technical review

      Solutions architects and engineering.

      Senior Product Marketing Manager, AI Training Infrastructure 1 week

    5. 5

      Publish

      With an ARENA path.

      Web team lead 2 days

    6. 6

      Enable

      Field training and talk track.

      Senior Product Marketing Manager, AI Training Infrastructure 2 weeks

    7. 7

      Measure

      Use in opportunities and win rate.

      Senior Manager, Marketing Research & Intelligence quarterly

    First result
    1 quarter
    Cost
    Staff time only
    Owner
    Senior Product Marketing Manager, AI Training Infrastructure

    Smallest test

    Publish the SUNK vs plain Kubernetes section first.

    Why it works

    Publish a decision guide: which scheduler pattern fits which team (research cluster, mixed training and inference, multi-cloud), what each costs to operate, and where SUNK's published numbers (96% goodput, 97-98% ETTR, 10x MTTF) come from. Add an honest "when you do not need SUNK" section and a path to an ARENA test.

    Platform engineers trust guides that admit trade-offs, and this is the page sellers can send in training deals.

    Risks and how to handle them

    • Open-source communities see it as marketing

      Have engineers write the open-source sections and link to the projects.

    Evidence

    • HiringSenior Product Marketing Manager, AI Training Infrastructure (posted August 25, 2026): owns the narrative tying "CoreWeave Kubernetes Service, SUNK, and SUNK Anywhere into a coherent market story", the competitive framework "against alternative infrastructure approaches", where "Ray, SkyPilot, and Kueue fit", how the Weights & Biases integration "shapes researcher perception", and a customer evidence strategy that is "not a library of case studies"; measured on "deal velocity, contract value, competitive win rates".Source
    • Your websiteSUNK page proof points: "up to 96% training goodput, 97-98% effective training time (ETTR), 10x longer mean time to failure (MTTF), and demonstrated >50% model FLOPs utilization (MFU)". The blog celebrates "One Billion Runs" on Weights & Biases.Source
    • Your websiteSitemap (892 URLs): 244 blog posts, 190 resources, 68 Fully Connected sessions, 59 events, 23 topic explainers ("What is Slurm?", "What is vLLM?") plus /topics/test, a live page with the H1 "Test" and an empty title and description; /pricing/classic is still live next to /pricing; an "AI cloud comparison guide" ebook and an "AI cloud TCO pricing comparison" report. coreweave.com answers without redirecting to the canonical www host. The docs site publishes llms.txt and an MCP endpoint; www.coreweave.com/llms.txt is a 404.Source
    • Your websiteARENA: "Prove production readiness", a pass with "14 days free" and "Expanded inference credits"; founder stories from Axiom Math, Rime and Anam; "Not ready for ARENA? Start building free".Source
  • 08

    Weights & Biases has passed a billion runs, and the training PMM is asked how the W&B integration shapes researcher perception of CoreWeave. W&B already sees run length, GPU type and failures for teams that train elsewhere.

    High impactMedium effort First result in 2 quarters Senior Product Manager

    First action

    Prototype the panel for one public project.

    How to measure it

    W&B-sourced ARENA passes

    Now
    –
    Target
    100 a quarter
    By
    2 quarters

    Steps

    1. 1

      Define eligibility

      Long runs, opt-in workspaces.

      Senior Product Manager, W&B Models 2 weeks

    2. 2

      Privacy review

      Consent and data use.

      Legal 2 weeks

    3. 3

      Build the estimate

      Public prices and GPU mapping.

      Senior Product Manager, W&B Models 1 month

    4. 4

      Design the panel

      Informational, dismissible.

      Senior Product Manager, W&B Models 2 weeks

    5. 5

      Pilot

      A share of eligible workspaces.

      Senior Product Manager, W&B Models 1 month

    6. 6

      Measure

      ARENA passes and conversion.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    2 quarters
    Cost
    Product time
    Owner
    Senior Product Manager, W&B Models

    Smallest test

    Email ten W&B teams a manual estimate for one of their public runs.

    Why it works

    Add an opt-in "Run this on CoreWeave" panel in W&B for long runs: estimated time and cost on comparable CoreWeave GPUs using public prices, plus an ARENA pass offer. Keep it informational, respect workspace privacy settings, and never use run data for sales without consent.

    It reaches researchers at the exact moment a run is slow or fails, inside a tool they already trust.

    Risks and how to handle them

    • Users see it as an upsell

      Make it opt-in and useful even if they never switch.

    Evidence

    • Your websiteSUNK page proof points: "up to 96% training goodput, 97-98% effective training time (ETTR), 10x longer mean time to failure (MTTF), and demonstrated >50% model FLOPs utilization (MFU)". The blog celebrates "One Billion Runs" on Weights & Biases.Source
    • HiringSenior Product Marketing Manager, AI Training Infrastructure (posted August 25, 2026): owns the narrative tying "CoreWeave Kubernetes Service, SUNK, and SUNK Anywhere into a coherent market story", the competitive framework "against alternative infrastructure approaches", where "Ray, SkyPilot, and Kueue fit", how the Weights & Biases integration "shapes researcher perception", and a customer evidence strategy that is "not a library of case studies"; measured on "deal velocity, contract value, competitive win rates".Source
    • HiringStaff Product Manager, AI Inference (posted October 12, 2026): own the inference roadmap and go-to-market "including pricing strategies, positioning, messaging, and competitive differentiation", with inference engines "vllm, SGLang, TensorRT-llm, and llm-d". A Senior Product Manager, W&B Models (posted August 28) works on the experiment workflow researchers "live in" daily, as "autoresearch and agentic workflows are reshaping" it.Source
    • Your websitePricing page: on-demand NVIDIA GB200 NVL72 at $42.00 an hour, HGX B200 at $68.80 (spot $34.11), RTX PRO 6000 at $20.00; GB300 NVL72 and HGX B300 on-demand are "Contact sales". The table header says "Inference Single GPU Price", but the 12 mobile cards label the same figure "Inference Single CPU Price".Source
    • Your websiteARENA: "Prove production readiness", a pass with "14 days free" and "Expanded inference credits"; founder stories from Axiom Math, Rime and Anam; "Not ready for ARENA? Start building free".Source
  • 09

    The DevRel director owns onboarding and "time-to-first-value". Forge is free to start, Teams has a 30-day trial, ARENA gives 14 free days with extra inference credits, and infrastructure is sold through sales. These are separate doors with separate pages.

    High impactMedium effort First result in 1 quarter Director

    First action

    Measure today's conversion from Forge signup to ARENA pass.

    How to measure it

    Signup-to-ARENA rate

    Now
    –
    Target
    2x
    By
    2 quarters

    Steps

    1. 1

      Define steps

      Four milestones and events.

      Director, Developer Relations 1 week

    2. 2

      Instrument

      Track each step.

      Growth engineer 2 weeks

    3. 3

      Write tutorials

      First hour per use case.

      Director, Developer Relations 1 month

    4. 4

      Add prompts

      In-product next steps.

      Senior Product Manager, W&B Models 1 month

    5. 5

      Hand-off rules

      When sales joins.

      Demand generation lead 1 week

    6. 6

      Weekly report

      Conversion by step.

      Senior Manager, Marketing Research & Intelligence weekly

    First result
    1 quarter
    Cost
    Staff time only
    Owner
    Director, Developer Relations

    Smallest test

    Publish one first-hour tutorial and watch its conversion.

    Why it works

    Map the path as one funnel: Forge signup, first logged run or inference call, ARENA pass, production contract. Publish a "first hour" tutorial per use case, add in-product prompts at each step, and report conversion between steps every week.

    Self-serve builders become the startup and enterprise pipeline when each step leads clearly to the next.

    Risks and how to handle them

    • Sales and self-serve compete

      Agree hand-off rules by account size.

    Evidence

    • HiringDirector, Developer Relations (open since March 11, 2026, updated October 12): grow a community around "CoreWeave SaaS offerings, including tools from Weights & Biases, OpenPipe, and Marimo"; produce "onboarding guides, tutorials, demos, reference architectures" that "accelerate time-to-first-value"; "Own and continuously improve the developer onboarding experience"; track "onboarding conversion, product adoption, engagement, and retention".Source
    • Your websiteForge pricing: Free at $0 a month, Teams "Starts at $60/month" with a 30-day free trial, Enterprise, and "Free forever for academic research".Source
    • Your websiteARENA: "Prove production readiness", a pass with "14 days free" and "Expanded inference credits"; founder stories from Axiom Math, Rime and Anam; "Not ready for ARENA? Start building free".Source
    • Your websiteHomepage: "The essential cloud for AI"; "The only AI cloud to earn SemiAnalysis' Platinum ClusterMAX rating three times", "9 of 10 leading foundation model providers rely on CoreWeave", "First NVIDIA Exemplar Cloud for training on NVIDIA GB200 NVL72", "Up to 98% effective training time", "Minutes to a human solving your issue". Forge is "free to build with any cloud, model, or framework". Menu programs: ARENA, Direct-to-Expert, Ventures, Academic Research, Zero Egress Migration.Source
  • 10

    The partner marketing director is asked to make every partnership "legible" and to track partner-sourced pipeline. The Partner Network page groups partners by layer and highlights NVIDIA, CrowdStrike and VAST Data, but partner stories link to the same three customer examples.

    High impactMedium effort First result in 1 quarter Director

    First action

    Pick three partners with a ready customer story.

    How to measure it

    Partner-sourced opportunities

    Now
    –
    Target
    +30%
    By
    2 quarters

    Steps

    1. 1

      Pick partners

      Three with ready proof.

      Director, Partner Marketing 1 week

    2. 2

      Agree content

      Architecture, story, offer.

      Director, Partner Marketing 3 weeks

    3. 3

      Build pages

      With tracked links.

      Web team lead 2 weeks

    4. 4

      Enable sellers

      Both sides.

      Director, Partner Marketing 2 weeks

    5. 5

      Run webinars

      One per partner.

      Field marketing lead quarterly

    6. 6

      Report

      Sourced and influenced pipeline.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    1 quarter
    Cost
    Co-marketing budget
    Owner
    Director, Partner Marketing

    Smallest test

    Launch the VAST Data page first.

    Why it works

    Build a page per top partner (NVIDIA, VAST Data, CrowdStrike, top agent frameworks and model providers): the joint architecture, a co-branded customer story, a joint webinar and a partner-specific offer with a tracked link. Give partners the link for their own sellers.

    Partner pages turn partner traffic into measurable pipeline and give both sales teams one shared asset.

    Risks and how to handle them

    • Partners slow to approve

      Start with partners already featured on the site.

    Evidence

    • HiringDirector, Partner Marketing (posted July 31, 2026): joint go-to-market with "NVIDIA, leading model and agent framework providers, and Weights & Biases"; "better together" narratives; "co-branded case studies"; "Track and report on partner-sourced and partner-influenced pipeline"; lead partner presence at Fully Connected, NVIDIA GTC, NeurIPS and AI Engineer World's Fair.Source
    • Your websiteCustomer stories: the sitemap lists 17 written case studies. The hub features Cohere ("North, Agentic AI for Enterprise"), OpenAI, IBM ("80%") and Mistral AI ("2.5x Faster Training"); Cohere is the only one about agents, and none is about robotics or autonomous vehicles. Several are older stories (NightCafe, Zeet, Odyssey's McDonald's metaverse experience, Bit192 GPT-NeoX-20B).Source
    • Your websiteHomepage: "The essential cloud for AI"; "The only AI cloud to earn SemiAnalysis' Platinum ClusterMAX rating three times", "9 of 10 leading foundation model providers rely on CoreWeave", "First NVIDIA Exemplar Cloud for training on NVIDIA GB200 NVL72", "Up to 98% effective training time", "Minutes to a human solving your issue". Forge is "free to build with any cloud, model, or framework". Menu programs: ARENA, Direct-to-Expert, Ventures, Academic Research, Zero Egress Migration.Source
  • 11

    There are 68 Fully Connected session pages and a 2026 event with London and sponsor pages. Event audiences cool quickly once the event ends.

    Medium impactLow effort First result in 1 quarter Field marketing lead

    First action

    Recap the ten most-watched sessions.

    How to measure it

    ARENA passes from event follow-up

    Now
    –
    Target
    50 a quarter
    By
    2 quarters

    Steps

    1. 1

      Rank sessions

      By views.

      Field marketing lead 2 days

    2. 2

      Write recaps

      Top ten first.

      Content marketing manager 3 weeks

    3. 3

      Group tracks

      Four tracks.

      Field marketing lead 1 week

    4. 4

      Build sequences

      One per track.

      Demand generation lead 2 weeks

    5. 5

      Send

      Attendees and registrants.

      Demand generation lead 1 week

    6. 6

      Measure

      Passes and meetings.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    1 quarter
    Cost
    Writing time
    Owner
    Field marketing lead

    Smallest test

    Send one track follow-up to last year's attendees.

    Why it works

    Publish a written recap with key numbers for every session, group them into tracks (training, inference, agents, physical AI), and send attendees and registrants a track-based follow-up with the related tutorial and an ARENA invitation.

    Recaps keep the content earning search traffic, and track-based follow-up turns attendance into evaluations.

    Risks and how to handle them

    • Recaps misstate speakers

      Send recaps to speakers before publishing.

    Evidence

    • Your websiteSitemap (892 URLs): 244 blog posts, 190 resources, 68 Fully Connected sessions, 59 events, 23 topic explainers ("What is Slurm?", "What is vLLM?") plus /topics/test, a live page with the H1 "Test" and an empty title and description; /pricing/classic is still live next to /pricing; an "AI cloud comparison guide" ebook and an "AI cloud TCO pricing comparison" report. coreweave.com answers without redirecting to the canonical www host. The docs site publishes llms.txt and an MCP endpoint; www.coreweave.com/llms.txt is a 404.Source
    • HiringDirector, Partner Marketing (posted July 31, 2026): joint go-to-market with "NVIDIA, leading model and agent framework providers, and Weights & Biases"; "better together" narratives; "co-branded case studies"; "Track and report on partner-sourced and partner-influenced pipeline"; lead partner presence at Fully Connected, NVIDIA GTC, NeurIPS and AI Engineer World's Fair.Source
    • Your websiteARENA: "Prove production readiness", a pass with "14 days free" and "Expanded inference credits"; founder stories from Axiom Math, Rime and Anam; "Not ready for ARENA? Start building free".Source
  • 12

    The topic library has 23 explainers (GPU, Slurm, vLLM, RAG) for a company with 892 pages and four use cases. Assistant and search questions about RL post-training, goodput, inference cost per token or simulation compute have no CoreWeave explainer.

    Medium impactMedium effort First result in 1 quarter Senior Manager

    First action

    Pick the first ten explainers from the gap list.

    How to measure it

    Topic library traffic

    Now
    –
    Target
    3x
    By
    3 quarters

    Steps

    1. 1

      Pick topics

      From the gap list.

      Senior Manager, Marketing Research & Intelligence 1 week

    2. 2

      Brief writers

      Template and examples.

      Content marketing manager 1 week

    3. 3

      Write

      Ten a month.

      Content marketing manager monthly

    4. 4

      Engineer review

      Accuracy.

      Director, Developer Relations monthly

    5. 5

      Link

      To products and docs.

      Web team lead monthly

    6. 6

      Measure

      Traffic and assistant citations.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    1 quarter
    Cost
    Writing budget
    Owner
    Senior Manager, Marketing Research & Intelligence

    Smallest test

    Publish "What is training goodput?" first.

    Why it works

    Use the question set from idea 6 to choose 40 new explainers, write each with a clear answer in the first paragraph, a diagram and a link to the matching product, and refresh the featured list.

    Explainers are what assistants and search engines quote, and they are cheap to produce from existing engineering knowledge.

    Risks and how to handle them

    • Thin content

      One clear, expert answer per page.

    Builds on

    Evidence

    • Your websiteSitemap (892 URLs): 244 blog posts, 190 resources, 68 Fully Connected sessions, 59 events, 23 topic explainers ("What is Slurm?", "What is vLLM?") plus /topics/test, a live page with the H1 "Test" and an empty title and description; /pricing/classic is still live next to /pricing; an "AI cloud comparison guide" ebook and an "AI cloud TCO pricing comparison" report. coreweave.com answers without redirecting to the canonical www host. The docs site publishes llms.txt and an MCP endpoint; www.coreweave.com/llms.txt is a 404.Source
    • HiringSenior Manager, Marketing Research & Intelligence (posted September 10, 2026): "Develop research and measurement frameworks for new / emerging audience and platform discovery channels, including Generative AI / LLMs"; size TAM and SAM; "Track market share against key competitors"; identify buyer groups by use case; and "push account targeting signals into marketing automation and CRM platforms"; success includes "identifying accounts and prospects that are ready to buy".Source
  • 13

    The inference PM owns pricing strategy and competitive differentiation, and CoreWeave publishes GPU hour prices, serverless per-token inference and a TCO comparison report. Buyers still have to convert GPU hours into the unit they budget in.

    High impactMedium effort First result in 1 quarter Staff Product Manager

    First action

    Build a spreadsheet version for three popular open models.

    How to measure it

    Calculator leads

    Now
    –
    Target
    200 a quarter
    By
    2 quarters

    Steps

    1. 1

      Gather benchmarks

      Throughput per model and GPU.

      Staff Product Manager, AI Inference 2 weeks

    2. 2

      Set the math

      Serverless, dedicated, reserved.

      Staff Product Manager, AI Inference 1 week

    3. 3

      Build

      Web calculator.

      Web team lead 3 weeks

    4. 4

      Cite sources

      Per number.

      Staff Product Manager, AI Inference 1 week

    5. 5

      Lead capture

      Save and send.

      Demand generation lead 1 week

    6. 6

      Measure

      Leads and win rate.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    1 quarter
    Cost
    Developer time
    Owner
    Staff Product Manager, AI Inference

    Smallest test

    Share the spreadsheet with ten prospects.

    Why it works

    Build a calculator: pick a model, traffic and latency target, and see cost per million tokens on serverless, dedicated and reserved options, with the benchmark source for each number. Offer to save the result and send it to sales.

    Inference buyers compare on cost per token; showing the math wins the shortlist and creates qualified leads.

    Risks and how to handle them

    • Benchmarks age quickly

      Date every figure and update monthly.

    Evidence

    • HiringStaff Product Manager, AI Inference (posted October 12, 2026): own the inference roadmap and go-to-market "including pricing strategies, positioning, messaging, and competitive differentiation", with inference engines "vllm, SGLang, TensorRT-llm, and llm-d". A Senior Product Manager, W&B Models (posted August 28) works on the experiment workflow researchers "live in" daily, as "autoresearch and agentic workflows are reshaping" it.Source
    • Your websitePricing page: on-demand NVIDIA GB200 NVL72 at $42.00 an hour, HGX B200 at $68.80 (spot $34.11), RTX PRO 6000 at $20.00; GB300 NVL72 and HGX B300 on-demand are "Contact sales". The table header says "Inference Single GPU Price", but the 12 mobile cards label the same figure "Inference Single CPU Price".Source
    • Your websiteSitemap (892 URLs): 244 blog posts, 190 resources, 68 Fully Connected sessions, 59 events, 23 topic explainers ("What is Slurm?", "What is vLLM?") plus /topics/test, a live page with the H1 "Test" and an empty title and description; /pricing/classic is still live next to /pricing; an "AI cloud comparison guide" ebook and an "AI cloud TCO pricing comparison" report. coreweave.com answers without redirecting to the canonical www host. The docs site publishes llms.txt and an MCP endpoint; www.coreweave.com/llms.txt is a 404.Source
  • 14

    The research lead is asked to push "account targeting signals" into marketing automation and the CRM and to find accounts "ready to buy". CoreWeave has first-party signals most rivals lack: Forge signups, ARENA applications, event registrations and W&B team growth.

    High impactMedium effort First result in 1 quarter Senior Manager

    First action

    Join Forge signups and ARENA requests for last quarter by domain.

    How to measure it

    Opportunities from top-scored accounts

    Now
    –
    Target
    25% of new pipeline
    By
    2 quarters

    Steps

    1. 1

      List signals

      Sources and consent.

      Senior Manager, Marketing Research & Intelligence 1 week

    2. 2

      Join by company

      Domain matching.

      Marketing operations 2 weeks

    3. 3

      Score

      Weekly model.

      Senior Manager, Marketing Research & Intelligence 2 weeks

    4. 4

      Route

      Top accounts to sales with reasons.

      Marketing operations 1 week

    5. 5

      Feedback

      Sales rates each lead.

      Senior Manager, Marketing Research & Intelligence weekly

    6. 6

      Tune

      Weights by conversion.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    1 quarter
    Cost
    Analyst time
    Owner
    Senior Manager, Marketing Research & Intelligence

    Smallest test

    Hand sales the top 20 accounts from one month of signals.

    Why it works

    Join these signals by company, score each account weekly (team size, usage growth, use case, funding), and route the top accounts to sales with the reason. Use W&B data only where terms and consent allow.

    First-party intent is more accurate than bought intent data, and the reasons give sellers a relevant first message.

    Risks and how to handle them

    • Privacy concerns

      Use only consented, company-level signals.

    Evidence

    • HiringSenior Manager, Marketing Research & Intelligence (posted September 10, 2026): "Develop research and measurement frameworks for new / emerging audience and platform discovery channels, including Generative AI / LLMs"; size TAM and SAM; "Track market share against key competitors"; identify buyer groups by use case; and "push account targeting signals into marketing automation and CRM platforms"; success includes "identifying accounts and prospects that are ready to buy".Source
    • Your websiteForge pricing: Free at $0 a month, Teams "Starts at $60/month" with a 30-day free trial, Enterprise, and "Free forever for academic research".Source
    • Your websiteARENA: "Prove production readiness", a pass with "14 days free" and "Expanded inference credits"; founder stories from Axiom Math, Rime and Anam; "Not ready for ARENA? Start building free".Source
    • Your websiteSUNK page proof points: "up to 96% training goodput, 97-98% effective training time (ETTR), 10x longer mean time to failure (MTTF), and demonstrated >50% model FLOPs utilization (MFU)". The blog celebrates "One Billion Runs" on Weights & Biases.Source
  • 15

    Physical AI Launchables launched this week with Templates for Isaac Sim, CARLA, MuJoCo, AlpaSim and Cosmos. The Physical AI business development manager is hired to build joint reference architectures with simulation ISVs and the NVIDIA ecosystem.

    High impactMedium effort First result in 2 quarters Business Development Manager…

    First action

    Write the Isaac Sim Template page first.

    How to measure it

    Template runs started

    Now
    –
    Target
    500 a quarter
    By
    2 quarters

    Steps

    1. 1

      Pick Templates

      Five live ones.

      Business Development Manager - Physical AI 1 week

    2. 2

      Write pages

      With sample output.

      Director, Developer Relations 1 month

    3. 3

      Partner outreach

      Co-launch per tool.

      Business Development Manager - Physical AI 1 month

    4. 4

      Docs links

      In partner docs.

      Business Development Manager - Physical AI 1 quarter

    5. 5

      Announce

      Physical AI comms.

      Senior Manager, Physical AI Communications 1 month

    6. 6

      Measure

      Runs and conversions.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    2 quarters
    Cost
    Staff time only
    Owner
    Business Development Manager Physical AI

    Smallest test

    Post the CARLA Template in the CARLA community.

    Why it works

    Publish a page per Template (what it runs, GPU used, time to first result, sample output), co-launch each with its tool's community or vendor, and add a "run this Template" link to partner docs.

    Robotics engineers search by tool name; Template pages meet them there and give partners something concrete to share.

    Risks and how to handle them

    • Open-source projects decline vendor links

      Contribute examples to their repos instead.

    Evidence

    • Your websiteLaunches this week: Physical AI Launchables (ready-to-run Templates for Isaac Sim, CARLA, MuJoCo, AlpaSim and Cosmos, with agent skills) and the Zero Trust AI Framework; Fully Connected 2026 sessions are on the site.Source
    • HiringPhysical AI hiring: a Senior Manager, Physical AI Communications, the "first dedicated communications owner for CoreWeave's Physical AI business", to "Create a repeatable pipeline of customer and partner stories across robotics, autonomous systems, industrial applications, and scientific AI" and measure "share of voice"; and a Business Development Manager - Physical AI to own partnerships with "simulation ISVs, robotics platform companies, OEMs" and the NVIDIA Physical AI ecosystem (Isaac Sim, Isaac Lab, Cosmos, Omniverse, DRIVE), with "joint reference architectures".Source
    • Your websitePhysical AI page: five customer cards (Decart, NEURA Robotics, PhysicsX, Woven by Toyota, Nissan "reduces physical vehicle tests by 17%"). Decart, NEURA and Toyota link to customer pages on wandb.ai, Nissan to a news post; none links to a CoreWeave case study.Source
  • 16

    The training PMM is asked to build "feedback loops that surface deployment insight from Solutions Architects" without losing specificity. Proof today is mostly in talks and partner pages.

    High impactLow effort First result in 1 month Senior Product Marketing Mana…

    First action

    Send the first form to ten solutions architects.

    How to measure it

    New approved proof points

    Now
    –
    Target
    8 a month
    By
    2 quarters

    Steps

    1. 1

      Design form

      Five questions.

      Senior Product Marketing Manager, AI Training Infrastructure 2 days

    2. 2

      Launch

      Monthly to SAs.

      Senior Product Marketing Manager, AI Training Infrastructure monthly

    3. 3

      Triage

      Pick the best.

      Senior Product Marketing Manager, AI Training Infrastructure monthly

    4. 4

      Write

      Anonymized proof points.

      Senior Product Marketing Manager, AI Training Infrastructure monthly

    5. 5

      Approve

      Named stories.

      Customer marketing lead monthly

    6. 6

      Distribute

      Decks and pages.

      Senior Product Marketing Manager, AI Training Infrastructure monthly

    First result
    1 month
    Cost
    $0
    Owner
    Senior Product Marketing Manager, AI Training Infrastructure

    Smallest test

    Collect five proof points this month.

    Why it works

    Run a 15-minute monthly form for solutions architects: workload, before and after numbers, quote, and whether the customer might go public. Turn the best into anonymized proof points within a week and named stories when approved.

    Field engineers see the results first; a light routine turns them into assets while they are fresh.

    Risks and how to handle them

    • Busy SAs skip it

      Keep it to five minutes and share how their input was used.

    Evidence

    • HiringSenior Product Marketing Manager, AI Training Infrastructure (posted August 25, 2026): owns the narrative tying "CoreWeave Kubernetes Service, SUNK, and SUNK Anywhere into a coherent market story", the competitive framework "against alternative infrastructure approaches", where "Ray, SkyPilot, and Kueue fit", how the Weights & Biases integration "shapes researcher perception", and a customer evidence strategy that is "not a library of case studies"; measured on "deal velocity, contract value, competitive win rates".Source
    • Your websiteCustomer stories: the sitemap lists 17 written case studies. The hub features Cohere ("North, Agentic AI for Enterprise"), OpenAI, IBM ("80%") and Mistral AI ("2.5x Faster Training"); Cohere is the only one about agents, and none is about robotics or autonomous vehicles. Several are older stories (NightCafe, Zeet, Odyssey's McDonald's metaverse experience, Bit192 GPT-NeoX-20B).Source
    • HiringDirector of Product Marketing, Agentic AI (open, posted June 17, 2026): position CoreWeave "as the premier infrastructure platform for agentic AI"; build "use-case playbooks" for "autonomous coding agents, multi-agent reasoning pipelines"; and "Build and scale a customer proof program featuring case studies and reference customers across AI labs, enterprises, and high-growth AI startups deploying agents in production"; plus thought leadership "white papers, technical blogs, benchmark reports, webinars".Source

Big bets 3

Larger plays that can change the trajectory.

  • 17

    CoreWeave publishes ETTR and MTTF numbers for SUNK and runs webinars on stragglers, stalls and failed runs. It sees more large-scale training than almost anyone, and 9 of 10 leading foundation model providers rely on it.

    High impactHigh effort First result in 3 quarters Senior Product Marketing Mana…

    First action

    Pick five reliability metrics that can be aggregated safely.

    How to measure it

    Report downloads

    Now
    –
    Target
    10,000
    By
    1 year

    Steps

    1. 1

      Pick metrics

      Safe to aggregate.

      Senior Product Marketing Manager, AI Training Infrastructure 2 weeks

    2. 2

      Customer terms

      Confirm data use.

      Legal 1 month

    3. 3

      Analyze

      Fleet data.

      Applied ML team 2 months

    4. 4

      Write

      Report and summary.

      Senior Product Marketing Manager, AI Training Infrastructure 1 month

    5. 5

      Launch

      Event and press.

      Senior Manager, Physical AI Communications 1 month

    6. 6

      Repeat

      Yearly.

      Senior Product Marketing Manager, AI Training Infrastructure yearly

    First result
    3 quarters
    Cost
    Analyst time
    Owner
    Senior Product Marketing Manager, AI Training Infrastructure

    Smallest test

    Publish one chart on restart causes.

    Why it works

    Publish a yearly, aggregated report: failure causes, time lost to restarts, goodput by cluster size and what improved it, with the method explained. Launch it at Fully Connected and NeurIPS.

    Original data earns press, analyst citations and assistant answers, and makes reliability CoreWeave's category.

    Risks and how to handle them

    • Customer confidentiality

      Aggregate and suppress small groups.

    Evidence

    • Your websiteSUNK page proof points: "up to 96% training goodput, 97-98% effective training time (ETTR), 10x longer mean time to failure (MTTF), and demonstrated >50% model FLOPs utilization (MFU)". The blog celebrates "One Billion Runs" on Weights & Biases.Source
    • Your websiteHomepage: "The essential cloud for AI"; "The only AI cloud to earn SemiAnalysis' Platinum ClusterMAX rating three times", "9 of 10 leading foundation model providers rely on CoreWeave", "First NVIDIA Exemplar Cloud for training on NVIDIA GB200 NVL72", "Up to 98% effective training time", "Minutes to a human solving your issue". Forge is "free to build with any cloud, model, or framework". Menu programs: ARENA, Direct-to-Expert, Ventures, Academic Research, Zero Egress Migration.Source
    • HiringSenior Product Marketing Manager, AI Training Infrastructure (posted August 25, 2026): owns the narrative tying "CoreWeave Kubernetes Service, SUNK, and SUNK Anywhere into a coherent market story", the competitive framework "against alternative infrastructure approaches", where "Ray, SkyPilot, and Kueue fit", how the Weights & Biases integration "shapes researcher perception", and a customer evidence strategy that is "not a library of case studies"; measured on "deal velocity, contract value, competitive win rates".Source
    • HiringSenior Manager, Marketing Research & Intelligence (posted September 10, 2026): "Develop research and measurement frameworks for new / emerging audience and platform discovery channels, including Generative AI / LLMs"; size TAM and SAM; "Track market share against key competitors"; identify buyer groups by use case; and "push account targeting signals into marketing automation and CRM platforms"; success includes "identifying accounts and prospects that are ready to buy".Source
  • 18

    ARENA is a guided evaluation that produces performance and cost evidence. Buyers compare Lambda, Nebius, Crusoe, Together AI and hyperscalers anyway, usually with ad hoc scripts.

    High impactHigh effort First result in 3 quarters Director

    First action

    Decide which ARENA workloads can be open-sourced.

    How to measure it

    Harness users

    Now
    –
    Target
    1,000 teams
    By
    1 year

    Steps

    1. 1

      Scope

      Workloads and metrics.

      Director, Developer Relations 1 month

    2. 2

      Clean up code

      For release.

      Developer experience engineers 2 months

    3. 3

      Legal review

      License.

      Legal 1 month

    4. 4

      Release

      With docs.

      Director, Developer Relations 1 month

    5. 5

      Community

      Hackathon and results.

      Director, Developer Relations quarterly

    6. 6

      Measure

      Users and ARENA passes.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    3 quarters
    Cost
    Engineering time
    Owner
    Director, Developer Relations

    Smallest test

    Release one workload with its scripts.

    Why it works

    Release the harness (workloads, metrics, reporting) as open source, invite other clouds and the community to run it, and publish CoreWeave's own results. Run a hackathon around it.

    Owning the standard method for comparing AI clouds puts CoreWeave in every evaluation, and its published results already lead.

    Risks and how to handle them

    • Rivals tune for the benchmark

      Use real workloads and publish the method.

    Evidence

    • Your websiteARENA: "Prove production readiness", a pass with "14 days free" and "Expanded inference credits"; founder stories from Axiom Math, Rime and Anam; "Not ready for ARENA? Start building free".Source
    • Competitor researchRivals' own homepages: Lambda, "Supercomputers for training and inference"; Nebius, "The Ultimate AI Cloud"; Crusoe, "The AI factory company"; Together AI, "the AI Native Cloud"; Runpod, "The AI Developer Cloud". Hyperscalers (AWS, Google Cloud, Azure) sell GPU capacity alongside everything else.Source
    • Your websiteBuilder page: CoreWeave Hacks hackathons, VAST Builders Challenges in San Francisco, New York and London, build notes (ARIA, Agent Reinforcement Trainer), Discord, X and LinkedIn. npm: @coreweave/cwsandbox has about 1,082 weekly downloads; Forge Agent Lens packages exist for Codex, Claude Code and OpenClaw.Source
    • Your websiteHomepage: "The essential cloud for AI"; "The only AI cloud to earn SemiAnalysis' Platinum ClusterMAX rating three times", "9 of 10 leading foundation model providers rely on CoreWeave", "First NVIDIA Exemplar Cloud for training on NVIDIA GB200 NVL72", "Up to 98% effective training time", "Minutes to a human solving your issue". Forge is "free to build with any cloud, model, or framework". Menu programs: ARENA, Direct-to-Expert, Ventures, Academic Research, Zero Egress Migration.Source
  • 19

    The agentic PMM and partner marketing director are both asked to define CoreWeave's role in the agentic stack with framework and model providers. The Agentic AI page explains the loop but offers no buildable reference.

    High impactHigh effort First result in 3 quarters Director of Product Marketing

    First action

    Pick the first partner and use case.

    How to measure it

    Deployments from references

    Now
    –
    Target
    300
    By
    3 quarters

    Steps

    1. 1

      Pick partners

      Three frameworks or model providers.

      Director, Partner Marketing 1 month

    2. 2

      Build

      Working code.

      Director, Developer Relations 2 months

    3. 3

      Measure

      Cost and latency.

      Staff Product Manager, AI Inference 1 month

    4. 4

      Publish

      Docs and repo.

      Director, Developer Relations 1 month

    5. 5

      Co-launch

      With partners.

      Director, Partner Marketing 1 month

    6. 6

      Track

      Deployments.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    3 quarters
    Cost
    Engineering time
    Owner
    Director of Product Marketing, Agentic AI

    Smallest test

    Publish the coding-agent reference first.

    Why it works

    Publish three reference architectures (coding agent, research, voice agent) built with named partners, with code, cost and latency numbers, sandboxes and RL post-training. Co-launch with each partner.

    Builders adopt working examples; partners promote what makes their framework look good.

    Risks and how to handle them

    • Frameworks change fast

      Maintain with partners and version each architecture.

    Evidence

    • HiringDirector of Product Marketing, Agentic AI (open, posted June 17, 2026): position CoreWeave "as the premier infrastructure platform for agentic AI"; build "use-case playbooks" for "autonomous coding agents, multi-agent reasoning pipelines"; and "Build and scale a customer proof program featuring case studies and reference customers across AI labs, enterprises, and high-growth AI startups deploying agents in production"; plus thought leadership "white papers, technical blogs, benchmark reports, webinars".Source
    • HiringDirector, Partner Marketing (posted July 31, 2026): joint go-to-market with "NVIDIA, leading model and agent framework providers, and Weights & Biases"; "better together" narratives; "co-branded case studies"; "Track and report on partner-sourced and partner-influenced pipeline"; lead partner presence at Fully Connected, NVIDIA GTC, NeurIPS and AI Engineer World's Fair.Source
    • Your websiteAgentic AI solution page: H1 "Agentic AI that paves the path to superintelligence", sections on training, inference and observing agents, "Exemplary agent inference. Validated by NVIDIA." and 11 FAQs, but no customer story or named agent builder.Source
    • Your websiteBuilder page: CoreWeave Hacks hackathons, VAST Builders Challenges in San Francisco, New York and London, build notes (ARIA, Agent Reinforcement Trainer), Discord, X and LinkedIn. npm: @coreweave/cwsandbox has about 1,082 weekly downloads; Forge Agent Lens packages exist for Codex, Claude Code and OpenClaw.Source

Wildcards 2

Unexpected experiments, each with a cheap way to test it.

  • 20

    CoreWeave's docs already offer llms.txt and an MCP endpoint, and it ships Agent Lens packages for Codex and Claude Code. The marketing site, where pricing, products and proof live, has no llms.txt.

    Medium impactLow effort First result in 1 month Director

    First action

    Draft llms.txt from the top 40 pages.

    How to measure it

    Cited marketing pages

    Now
    –
    Target
    +20%
    By
    2 quarters

    Steps

    1. 1

      Draft

      Top 40 pages.

      Director, Developer Relations 2 days

    2. 2

      Publish

      llms.txt on www.

      Web team lead 1 day

    3. 3

      Agent guide

      Sign up, price, launch.

      Director, Developer Relations 2 weeks

    4. 4

      Test

      With coding agents.

      Director, Developer Relations 1 week

    5. 5

      Promote

      Build notes and Discord.

      Director, Developer Relations 1 week

    6. 6

      Measure

      Citations via idea 6.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    1 month
    Cost
    $0
    Owner
    Director, Developer Relations

    Smallest test

    Publish a first llms.txt this week.

    Why it works

    Add llms.txt to www.coreweave.com pointing to pricing, product pages, case studies and topic explainers, and document how a coding agent can sign up, check prices and launch a Template.

    Engineers increasingly ask coding agents to compare and provision clouds; a clear agent path makes CoreWeave the easy answer.

    Risks and how to handle them

    • Little immediate traffic

      Treat it as a low-cost bet tracked monthly.

    Evidence

    • Your websiteSitemap (892 URLs): 244 blog posts, 190 resources, 68 Fully Connected sessions, 59 events, 23 topic explainers ("What is Slurm?", "What is vLLM?") plus /topics/test, a live page with the H1 "Test" and an empty title and description; /pricing/classic is still live next to /pricing; an "AI cloud comparison guide" ebook and an "AI cloud TCO pricing comparison" report. coreweave.com answers without redirecting to the canonical www host. The docs site publishes llms.txt and an MCP endpoint; www.coreweave.com/llms.txt is a 404.Source
    • Your websiteBuilder page: CoreWeave Hacks hackathons, VAST Builders Challenges in San Francisco, New York and London, build notes (ARIA, Agent Reinforcement Trainer), Discord, X and LinkedIn. npm: @coreweave/cwsandbox has about 1,082 weekly downloads; Forge Agent Lens packages exist for Codex, Claude Code and OpenClaw.Source
    • Your websiteLaunches this week: Physical AI Launchables (ready-to-run Templates for Isaac Sim, CARLA, MuJoCo, AlpaSim and Cosmos, with agent skills) and the Zero Trust AI Framework; Fully Connected 2026 sessions are on the site.Source
  • 21

    Forge is free forever for academic research and CoreWeave runs an Academic Research program. Papers that thank CoreWeave for compute are independent proof that no case study can match.

    Medium impactLow effort First result in 1 month Customer marketing lead

    First action

    Search paper acknowledgements for CoreWeave.

    How to measure it

    Academic applications

    Now
    –
    Target
    +30%
    By
    2 quarters

    Steps

    1. 1

      Search papers

      Acknowledgements.

      Customer marketing lead 2 weeks

    2. 2

      Build page

      By field.

      Web team lead 1 week

    3. 3

      Acknowledgement line

      For members.

      Director, Developer Relations 1 day

    4. 4

      Invite authors

      Short talks.

      Director, Developer Relations monthly

    5. 5

      Promote

      Academic channels.

      Director, Developer Relations monthly

    6. 6

      Measure

      Applications.

      Senior Manager, Marketing Research & Intelligence monthly

    First result
    1 month
    Cost
    $0
    Owner
    Customer marketing lead

    Smallest test

    List ten papers this month.

    Why it works

    Collect papers that acknowledge CoreWeave or W&B, list them by field with links, and invite authors to short talks. Give program members a ready acknowledgement line.

    Researchers trust other researchers, and today's students run tomorrow's labs.

    Risks and how to handle them

    • Few papers found

      Start with W&B citations, which are common.

    Evidence

    • Your websiteForge pricing: Free at $0 a month, Teams "Starts at $60/month" with a 30-day free trial, Enterprise, and "Free forever for academic research".Source
    • Your websiteHomepage: "The essential cloud for AI"; "The only AI cloud to earn SemiAnalysis' Platinum ClusterMAX rating three times", "9 of 10 leading foundation model providers rely on CoreWeave", "First NVIDIA Exemplar Cloud for training on NVIDIA GB200 NVL72", "Up to 98% effective training time", "Minutes to a human solving your issue". Forge is "free to build with any cloud, model, or framework". Menu programs: ARENA, Direct-to-Expert, Ventures, Academic Research, Zero Egress Migration.Source

03

How Programmable can help

Where an idea in this playbook is something Programmable builds or runs, it's listed here with what we'd do. Everything else is yours to run.

ProgrammableDigital

Show it, don't just describe it

These ideas need something to show: a demo, a video, an animation, graphics or a deck. Digital turns screenshots or the site into all of them, in the company's own brand.

Make a demo (opens programmable.digital in a new tab)
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See every playbook and website review

Independent research. Programmable wrote this playbook from public sources, as they stood on October 22, 2026, and cites them throughout. CoreWeave did not commission, review or endorse it, and Programmable is not affiliated with CoreWeave. Company and product names are trademarks of their owners, used only to identify them. The ideas are suggestions and opinion, not professional, legal or financial advice, and not statements about how CoreWeave runs its business.

Something wrong, or do you represent CoreWeave? Email [email protected] and we will correct it or take it down.

30/60/90 roadmap

What to focus on in each month, and the ideas that carry it.

  1. Days 1 to 307 ideas

    Transcripts and agent proof, Physical AI stories, named builders on the Agentic AI page, pricing and test-page fixes, homepage speed and an AI-assistant baseline.

  2. Days 31 to 6011 ideas

    Training decision guide, W&B estimates, the Forge-to-ARENA path, partner pages, event recaps, topic explainers, inference calculator, account scoring, Template pages and the SA proof harvest.

  3. Days 61 to 903 ideas

    Start the big bets: the reliability report, the open evaluation harness and agent reference architectures.

The research behind the plan

3 research areas, each summarised in a few lines. Open any of them for the full detail.

Customers

What customers say

Customers value fast access to the newest NVIDIA GPUs at cluster scale. The most cited problem: failed or stalled training runs.

  • Training reliability and performance
  • Inference cost and latency at scale
  • In their words: “goodput”

Market

Competitive landscape

5 competitors compared: Lambda, Nebius, Crusoe, Together AI and 1 more.

  • Gap to exploit: Written, use-case proof for agent and physical AI builders
  • Lambda: Smaller software layer than Forge
  • Nebius: Fewer frontier-lab references

Hiring signals

CoreWeave's open marketing roles show where it wants to win next.

  • Director of Product Marketing, Agentic AI: Customer proof for teams deploying agents. Ideas 1, 3, 19.
  • Senior Product Marketing Manager, AI Training Infrastructure: SUNK, CKS and the open-source landscape; win rates. Ideas 7, 16, 17.
  • Senior Manager, Marketing Research & Intelligence: LLMs as a discovery channel; account signals. Ideas 6, 12, 14.

From the team that wrote this playbook

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  • ProgrammableCommunityForums with labelled AI members, never empty (opens programmable.community in a new tab)
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