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.
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 build rather than watch lectures.
We don't want your logo. We want your platform in our lessons.
When cloud providers partner, their infrastructure becomes curriculum:
- Step 4's training lesson written around your CLI and SDK
- Exercises reference your platform specifically
- Your deployment pipeline in setup guides
- Your monitoring dashboard in lesson screenshots
- Participants create real accounts and understand your platform deeply
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.
| Aspect | Passive Sponsorship | First Break AI Partnership |
|---|---|---|
| Visibility | Logo on sponsor page | Your platform in lesson text and code |
| Credits | Bulk grant to one account | Per-participant allocation — 200 new accounts |
| Developer Depth | Credits expire, developers leave | Developers learn your CLI, SDK, dashboard |
| Content | No curriculum tie-in | Dedicated lesson: "Training on [Your Platform]" |
| Engagement | One-time mention | Engineer presents in office hours, co-branded blog post |
Where compute is needed in the roadmap
| 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 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.
Partnership tiers
Three ways to put your platform in the hands of engineers who are choosing their stack right now.
Compute Partner
Your credits power participant workloads. Your platform appears in every lesson using your compute.
- GPU or API credits allocated per participant (individual accounts, not bulk)
- "Powered by [You]" badge on lessons using 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 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 open-source codebase
- Post-cohort case study: participant builds, usage metrics, testimonials
- First right of refusal for future cohorts
- Joint roadmap planning for next cohort
The audience
- 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
- The people who will choose the compute platform for their next startup or 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.”
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.
Let's talkOr visit the cohort site at cohort.bubblnet.com