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August cohort applications are closed.

Hear about the next cohort
Antern / AI-Native Engineering Sprint

Study deeply.
Build rigorously.

AI engineering, from first principles
to systems that work in the world.

An engineering sprint for working professionals. Study the foundations, build and evaluate AI systems, and develop the judgment to defend your engineering decisions.

Explore the curriculum Inside the program
Antern / A way of thinking
Understanding is an iterative process Question assumptions, build from first principles, test against reality, and learn from evidence. Each iteration leads to better questions. QUESTION BUILD TEST LEARN the assumption an idea against reality evidence Understanding is earned.
Fig. 01 Better questions. Deeper understanding.
Our philosophy
Our approach

Understand the idea.
Test it against reality.

Read the paper. Reconstruct the reasoning. Build the system. Find where it fails.

We bring research and engineering practice together, with evaluation, production constraints, and clear technical communication at every step.

The Antern approach
From the notebook

Engineering studies

All studies
Role Transition

Paths into AI engineering.

The sprint is calibrated against the skill mix expected by frontier AI labs, FDE teams, AI product teams, infrastructure labs, and seed-to-Series-B AI-native startups.

Applied AI Engineer

Product-facing AI systems, workflow automation, LLM apps, and domain-specific AI tools.

Forward Deployed Engineer

Ambiguous customer problems, end-to-end deployment, stakeholder communication, and production ownership.

Agent Engineer

Planning loops, tool use, memory, orchestration, recovery, evaluation, and human-in-the-loop workflows.

AI SWE

AI-native software engineering, code agents, review systems, developer tools, and rapid product iteration.

AI Infrastructure Engineer

Inference systems, serving, evaluation infra, observability, cost control, and reliability.

AI Product Engineer

AI workflows packaged into usable products with deployment, UX, feedback loops, and business context.

Research Engineer

Paper reading, reproduction, experiments, benchmarks, failure analysis, and research-to-system translation.

AI Startup Engineer

Seed to Series B environments where shipping, taste, product judgment, and distribution matter.

Hiring Signal

The capabilities we develop.

The curriculum is designed around the overlap: software engineering, systems, ML depth, agentic workflows, evaluation, product judgment, communication, taste, and shipping.

Applied AI labs

Software engineering, systems, ML/LLM fundamentals, agent engineering, evaluation, reliability, research thinking, communication, product judgment, originality, and taste.

Research-heavy AI teams

Reasoning depth, research thinking, writing clarity, alignment awareness, intellectual curiosity, and careful technical judgment.

FDE-style roles

Ambiguity tolerance, end-to-end systems thinking, customer communication, product judgment, deployment, and the ability to turn vague business pain into a working system.

AI coding product teams

SWE skill, product taste, AI-native workflow, fast iteration, shipping velocity, and the loop from idea to prototype to user feedback.

AI startup engineer

Shipping ability, product engineering, AI/LLM knowledge, full-stack ability, communication, taste, open-source contribution, and distribution ability.

The Vault

Explore the program.

A closer look at what you will study, how you will work, and the evidence behind the program.

01

Curriculum

The public curriculum map shows the architecture of the cohort. The complete week-by-week syllabus, exact projects, and topic-level breakdown are shared through the Antern counsellor flow.

 Explore ↗ 02

Live Builds

The sprint is implementation-first. Participants build AI systems live, document architectural decisions, evaluate failure modes, and turn the work into proof-of-work that can survive technical scrutiny.

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Outcomes

Antern keeps outcomes evidence in a counsellor-mediated vault with masked participant identities, outreach activity, positive conversations, and meetings. The data is presented as pipeline activity, not as a job, salary, or offer guarantee.

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Teaching Method

Antern teaches participants to feel the problem before learning the solution, reconstruct why ideas were invented, build systems, challenge AI output, explain decisions, and verify work under ambiguity.

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Evaluation

Evaluation is process-aware: participants are assessed on reasoning, verification, business consequence, failure detection, and ability to defend technical decisions, not only on whether they produced a polished artifact.

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Positioning

Professionals learn to choose a domain, build credible proof-of-work, explain technical decisions, publish learning, run outreach, and communicate their value in terms founders and engineering teams understand.

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Research

Antern research combines first principles, historical context, academic papers, industry validation, open-source implementations, production constraints, experiments, and feedback from real users and businesses.

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Outreach Engine

Outreach Engineering combines ICP selection, lead sourcing, AI-assisted research, campaign design, follow-ups, CRM tracking, campaign debugging, and positioning so professionals can create opportunity instead of waiting for it.

 Explore ↗ 09

Instructor & Network

Ayush Singh teaches AI engineering through research, implementation, business reality, and operator-level judgment. The network layer comes from Antern, SecondBrain Labs, public teaching, business operations, and counsellor-mediated introductions.

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Enroll

The sprint is for working professionals who already know Python, have some mathematical maturity, use AI natively, and want to transition into serious AI engineering depth.

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Official admissions partner

Admissions, officially handled by Topmate.

Topmate Verified partner / Antern

Topmate is Antern's official and only admissions partner. Its team handles all admission counselling and enrolment activities for the AI-Native Engineering Sprint.

Anyone contacting you about admission should be verified before you share personal information, make a payment, or confirm your enrolment.

How to verify a counsellor
  1. 01

    Ask for a written acknowledgement from the counsellor's official email address.

  2. 02

    Confirm that the sender's email ends exactly in @topmate.io.

  3. 03

    If you have any doubt, email team@antern.co before proceeding.

Please stay alert: names and identities can be copied. Antern cannot accept responsibility for transactions or communication with an unverified person. Always complete the email verification above.