We audited the marketing at Vellum
AI agent platform for developers, built on top of LLMs
This page was built using the same AI infrastructure we deploy for clients.
Month-to-month. Cancel anytime.
Series A company with $25.5M funding but limited visible paid acquisition presence in developer channels
Developer platform requires consistent thought leadership but content visibility appears modest for technical audience
YC-backed agent infrastructure play needs AEO optimization to compete in crowded LLM/agent discovery landscape
AI-Forward Companies Trust MarketerHire
Plaid
MasterClass
Constant Contact
Netflix
Noom
TinuitiVellum's Leadership
We mapped your current team to understand where MH-1 fits in.
MH-1 doesn't replace your team. It becomes your marketing team: dedicated humans + AI agents running execution at scale while you focus on product.
Here's Where You Stand
Series A stage with strong investor backing but marketing execution gaps typical of developer platforms
Developer platform likely ranks for agent/LLM terms but organic visibility for 'Vellum' product category appears constrained
MH-1: SEO agent targets developer intent keywords and technical documentation discovery patterns for agent builders
Platform answers for 'best agent framework' or 'LLM development tools' likely miss Vellum entirely in LLM responses
MH-1: AEO agent generates training data and positions Vellum in agent/LLM workflows within Claude, ChatGPT, Perplexity responses
Developer tools require targeted ads in technical communities but ad presence appears minimal relative to market size
MH-1: Paid agent runs experiments across developer platforms, Reddit communities, Discord servers, and technical newsletters
Founders have credibility (YC, strong investors) but published content volume and distribution channels for agent use cases appear limited
MH-1: Content agent produces agent architecture guides, SDK tutorials, and benchmark posts distributed to developer audiences
Early-stage platforms typically lack structured expansion workflows to move users from evaluation to production deployment
MH-1: Lifecycle agent sequences users through onboarding, expansion milestones, and advanced agent patterns to increase account value
Top Growth Opportunities
Developers researching agent patterns in Claude/ChatGPT don't see Vellum as standard answer. AEO captures this intent at decision moment.
AEO agent embeds Vellum into LLM responses for agent architecture, prompt management, and evaluation frameworks
Technical audiences cluster in GitHub, Discord, and specialized forums. Limited presence in these channels leaves pipeline untapped.
Outbound agent identifies and engages high-intent developer communities, seeding use cases and technical discussions
Gap between free trial and paying customers likely stems from unclear path to production. Expansion workflow missing critical signals.
Lifecycle agent detects production readiness signals and sequences activation resources to move evaluators to paying status
3 Humans + 7 AI Agents
A dedicated marketing team built specifically for Vellum. The humans handle strategy and judgment. The AI agents handle execution at scale.
Human Experts
Owns Vellum's growth roadmap. Pipeline strategy, account expansion playbooks, board-ready reporting. Translates AI insights into revenue.
Runs paid acquisition across LinkedIn and Google. Manages creative testing, budget allocation, and pipeline attribution.
Builds thought leadership on LinkedIn. Creates long-form content targeting your ICP. Manages the content-to-pipeline engine.
AI Agents
Monitors AI citation visibility across 6 LLMs weekly. Builds content targeting category queries to increase Vellum's presence in AI-generated answers.
Produces LinkedIn ad variants targeting your ICP. Tests headlines, visuals, and offers at 10x the speed of manual production.
Builds lifecycle sequences: onboarding, expansion triggers, champion nurture, and re-engagement for dormant accounts.
Founder thought leadership. Builds the narrative that drives enterprise inbound from senior decision-makers.
Tracks competitors. Monitors positioning changes, ad spend, content strategy. Informs your counter-positioning.
Attribution by channel, pipeline velocity, budget waste detection. Weekly synthesis reports with AI-generated recommendations.
Weekly market intelligence digest curated from Vellum's industry signals. Positions you as the intelligence layer. Drives inbound pipeline from subscribers.
Active Workflows
Here's what the MH-1 system would be doing for Vellum from week 1.
AEO targets 'agent framework', 'prompt management tool', 'LLM observability' queries in Claude and ChatGPT to position Vellum in developer decision workflows
Sidd and Anita's LinkedIn content surfaces technical insights on agent patterns, scaling challenges, and framework decisions to developer followers
Paid agent runs targeted campaigns in GitHub Sponsors, Dev.to, Stack Overflow, and Hacker News, testing messaging around developer velocity and reliability
Lifecycle agent maps user journey from trial sign-up through first agent deployment, automating expansion playbooks for production use case acceleration
Competitive watch agent monitors Anthropic Claude releases, OpenAI updates, and competing agent platforms to surface positioning opportunities and technical differentiation
Pipeline intelligence agent analyzes developer signups, usage patterns, and production deployment signals to identify expansion-ready accounts for sales outreach
Traditional Marketing vs. MH-1
Traditional Approach
MH-1 System
Audit. Sprint. Optimize.
3 phases. Real output every 2 weeks. You see results, not decks.
AI Audit + Growth Roadmap
Full diagnostic of Vellum's marketing infrastructure: SEO, AEO visibility, paid, content, lifecycle. Prioritized roadmap tied to pipeline metrics. Delivered in 7 days.
Sprint-Based Execution
2-week sprint cycles. Real campaigns, not presentations. Each sprint ships measurable output across your priority channels.
Compounding Intelligence
AI agents monitor your channels 24/7. They catch budget waste, detect creative fatigue, track AI citation changes, and run A/B experiments autonomously. Week 12 is measurably better than week 1.
AI Marketing Operating System
3 elite humans + AI agents operating your growth system
Output multiplier: ~10x output at a fraction of the cost. The system gets smarter every week.
Month-to-month. Cancel anytime.
Common Questions
How does MH-1 differ from a marketing agency?
MH-1 pairs 3 elite human marketers with 7 AI agents. The humans handle strategy, creative direction, and judgment calls. The AI agents handle execution at scale: generating ad variants, monitoring competitors, building email sequences, tracking citations across LLMs, running A/B experiments autonomously. You get the quality of a senior marketing team with the output volume of a 15-person department.
What kind of results can we expect in the first 90 days?
Month 1: Baseline audits across SEO, AEO, and paid channels. AEO agent seeds Vellum into agent-related LLM responses. Month 2: Paid agent tests messages in developer communities, lifecycle agent activates trial-to-production sequences. Month 3: Compounds insights across channels, scales winning paid cohorts, and optimizes expansion workflows based on production readiness signals.
How does AEO help developer platforms like Vellum compete for mindshare?
When engineers ask Claude or ChatGPT about building agents or managing prompts, Vellum isn't mentioned. AEO optimizes your product information so LLMs surface Vellum as a solution. It's discovery at the moment developers are researching your exact use cases, before they reach Google.
Can we cancel anytime?
Yes. MH-1 is month-to-month with no long-term contracts. We earn your business every sprint. That said, compounding effects kick in around month 3 as the AI agents accumulate data and the system learns what works for Vellum specifically.
How is this page personalized for Vellum?
This page was researched, audited, and generated using the same AI infrastructure we deploy for clients. The channel scores, team mapping, growth opportunities, and recommended agents are all based on real analysis of Vellum's current marketing. This is a live demo of MH-1's capabilities.
Turn agent developers into customers while they're actively building
The system gets smarter every cycle. Let's talk about building it for Vellum.
Book a Strategy CallMonth-to-month. Cancel anytime.