Partner with First Break AI
Stop being a passive check-writer. Become the platform that the next generation of AI engineers learns on.
Stop being a passive check-writer.
Become the platform that the next generation of AI engineers learns on — not the coupon they forget.
The problem with logo sponsorships
Most cloud providers sponsor education the same way: write a check, get a logo on a page, hand out credit coupons. Students burn the credits on one assignment, forget the platform, and move on.
That is a terrible return on investment.
The credits expire. The developers leave. The logo gets scrolled past. Nobody learned your platform deeply enough to choose it for their next job or their next startup.
What we do differently
First Break AI is a free, open cohort where engineers learn AI from first principles — inference in pure C, model training from scratch, shipping AI-powered products. The curriculum goes deep — with exercises, a sampling visualizer, and a public codebase. Participants don’t watch lectures; they build.
We don’t want your logo. We want your platform in our lessons.
When a cloud provider partners with First Break AI, their infrastructure becomes part of the curriculum itself:
- Step 4’s training lesson is written around your CLI and SDK
- The exercise says “fine-tune Qwen3 on [your platform],” not “use any provider”
- Your deployment pipeline is in the setup guide
- Your monitoring dashboard appears in lesson screenshots
- Participants set up accounts, run real workloads, and understand your platform deeply enough to teach it to others
The difference between “we gave them $500 in credits” and “200 engineers now know our platform well enough to recommend it at work” is the difference between a marketing expense and a developer acquisition channel.
Why this works better
The most effective developer platforms in AI right now are the ones that made their tools the teaching material, not the coupon. They open-sourced their training framework, built community around it, and then offered the compute to run it. The tools are the education. The education creates the users. The users become customers.
We apply the same model, but to a structured cohort:
Passive sponsorship
First Break AI partnership
Visibility
Logo on a sponsor page
Your platform in the lesson text and code
Credits
Bulk grant to one account
Per-participant allocation — 200 new accounts on your platform
Developer depth
Credits expire, developers leave
Developers learn your CLI, your SDK, your dashboard
Content
No curriculum tie-in
Dedicated lesson section: “Training on [Your Platform]”
Engagement
One-time mention
Your engineer presents in office hours, co-branded blog post
Where compute is needed in the roadmap
The curriculum is designed so participants hit the GPU wall at exactly the right moment — after they understand inference cold.
| Roadmap Step | What participants build | Compute needed |
|---|---|---|
| Step 1 — First use of AI | IDE setup, GitHub, blog | None |
| Step 2 — Run a model locally | Qwen3-0.6B inference in pure C | CPU only |
| Step 3 — Inference deep-dive | API-based inference, benchmarking, KV cache | Inference API credits |
| Step 4 — Training fundamentals | Fine-tuning, training from scratch | GPU credits (primary need) |
| Step 5 — Build an AI product | Deploy a real AI-powered product | Deployment / serverless GPU |
| Step 6 — Capstone | Open-source contribution or portfolio piece | Varies |
Steps 1–2 are CPU-only by design. By Step 3, participants understand attention, KV cache, and sampling at the C level. They need your compute now, and they understand why they need it.
Partnership tiers
Compute Partner
Your credits power participant workloads. Your platform appears in every lesson that uses your compute.
- GPU or API credits allocated per participant (individual accounts, not bulk)
- “Powered by [You]” badge on lessons that use your compute
- Logo on sponsors page and homepage
- Mention in cohort announcements (Discord, office hours)
Infrastructure Partner
Everything in Compute Partner, plus your platform becomes curriculum.
- Dedicated lesson or tutorial section written around your platform
- Co-branded blog post on the cohort site
- Your platform in the recommended setup guide
- Your engineer does a guest session in office hours
- Joint social media announcement
Founding Partner
Everything above, plus named ownership of a roadmap step.
- Named step: “Step 4: Training Fundamentals, powered by [You]”
- Your training framework and tools integrated into the open-source codebase
- Post-cohort case study: what participants built, usage metrics, testimonials
- First right of refusal for future cohorts
- Joint roadmap planning for the next cohort
The audience
This is who learns on your platform:
- Engineers, career switchers, and builders learning AI from first principles
- Active on Discord and GitHub, building in public, writing technical blogs
- Learning the full stack: inference, tokenization, attention, KV cache, training, deployment
- Working with open-source models (Qwen3, DeepSeek) and AI-native tools (Cursor, Claude Code, HuggingFace)
- The people who will choose the compute platform for their next startup or their team’s next project
Comparable paid AI cohorts charge $1,500–$2,000 per seat and provide $1,000–$2,000 in compute credits per student. First Break AI is free, reaches a broader audience, and runs for 3 months — longer engagement, deeper platform familiarity, stronger developer loyalty.
Sponsor spots for Cohort 01 are open
We’re looking for compute and infrastructure partners who want to be the platform that the next generation of AI engineers learns on — not just the coupon they forget.
Contact
Email: [email protected]
Cohort lead: FireHacker · GitHub · X · LinkedIn