From Idea to Working AI-Native MVP in Six Weeks.
We partner with ambitious early-stage founders to turn exploratory ideas or rough scripts into tested, reliable AI products. Hands-on architectural leadership and open-source toolkits—with zero equity taken and no upfront fee.
Designed for founders at two early stages
Whether you are starting from a verified insight or trying to stabilize a fragile hack, we meet you where you are.
Exploratory Idea → Functional Prototype
Who it is for: Founders who have spotted a clear, painful problem in their domain but need the technical AI blueprint to turn it into an actual working system.
What we achieve: We clarify the AI boundary, build the prompt and model routing pipelines, and produce a functional prototype you can demonstrate to prospective users or design partners.
Rough Prototype → Working MVP
Who it is for: Builders with an existing Python script, Streamlit demo, or Jupyter notebook that frequently hallucinates, costs too much, or breaks on edge cases.
What we achieve: We harden the system with evals, fast System 1 triage, retrieval guardrails, and spend caps—turning an unpredictable demo into an MVP ready for real users.
How we build together, week by week
Six focused weeks structured around rapid validation, concrete milestones, and real user feedback.
Intent, AI Boundaries & Architecture
From exploratory problem to clear AI system blueprint
Focus: Deconstruct what AI must decide versus what deterministic software handles.
Key Deliverables
- Problem–solution validation & AI differentiation mapping
- System 1 vs System 2 division (fast classification vs deep reasoning)
- Model & tooling selection (OpenAI, Claude, Gemini, or fast typed models like Jev)
- Technical architecture brief and API data contract
Core Workflow & Harness Build
Turning the concept into an end-to-end working prototype
Focus: Assemble the working pipeline using our open-source tools and battle-tested patterns.
Key Deliverables
- End-to-end working pipeline: prompt templates, context retrieval & RAG
- Tool-calling harness and state machines for agentic steps
- Synthetic test fixture setup to measure accuracy against baseline queries
- Functional prototype demo ready for internal walkthrough
Guardrails, Real Users & Working MVP
From fragile prototype to reliable, testable MVP
Focus: Lock down spend, handle edge cases gracefully, and put the first real users on it.
Key Deliverables
- Hard spend caps, rate limits, timeout budgets, and kill switch
- Evaluations and automated verification steps before results reach users
- First 5–10 real user test runs with telemetry tracking failure traces
- Clean v1 repository handoff with prioritized post-MVP technical roadmap
Accelerated by our internal open-source tools
You don’t start from a blank canvas. Bootcamp startups get plug-and-play access to the same open tools we develop and publish in the open:
Jev Playground
Sub-200ms typed decisions and fast System 1 triage cascades to route tasks without wasting expensive LLM tokens.
View tool detailsAI Engineering Cookbook
Proven prompts, agent skills, and review guardrails so code generation and agent loops stay reliable.
View cookbookHybrid Search RAG
Semantic retrieval merged with exact keyword matching so AI answers from your domain data instead of guessing.
View RAG toolRadical focus: what we build vs what we skip
Premature optimization is fatal for early AI products. We stay ruthlessly focused on proving value.
- Help you map and build the core AI loop with senior technical guidance
- Provide plug-and-play access to our open-source tools (Jev Playground, Cookbook, RAG)
- Build essential safety harnesses: spend caps, evals, failure fallbacks, and monitoring
- Review and co-architect your code directly, unblocking technical dead-ends
- Help you put initial test users on the product to validate real willingness-to-use
- Premature scalability, multi-region Kubernetes clusters, or microservices overkill
- Building disposable landing page mockups without real working AI underneath
- Enterprise compliance gymnastics before finding problem-solution fit
- Taking any equity, cap table stakes, or intellectual property rights
Most accelerator models take 7–10% of your equity before you’ve even proved product-market fit. We don’t want your equity, and we don’t want to bill early-stage founders who are bootstrapping.
Instead, working with selected early-stage teams gives us a frontline testing ground for our open-source tools, builds lasting relationships with the next wave of AI founders, and creates unmatched case studies. If your company takes off and later needs our monthly embedded Forward Deployed CTO service, great. If you don’t, you keep 100% of your product with our blessings.
What we look for in applicants
Frequently asked questions about the bootcamp
Everything you need to know about the 6-week program, eligibility, and the build process.
Ready to build your AI-native MVP?
Book an intro discovery call with our CTO. We’ll discuss your idea, technical feasibility, and whether the 6-week bootcamp is the right fit for your team.
Free 30-minute Google Meet · Zero obligation · Direct with a senior engineering lead