AI for Developers: A Practical First Month with LLM APIs
by Priya Raman
Go beyond the basics: multi-agent orchestration in native C++, zero-copy retrieval pipelines, SIMD-accelerated inference routing and production-grade evaluation harnesses.
PR Created by Priya Raman
Every bullet below is something you will have built, shipped or be able to explain by the time you finish the last lesson.
8 modules · 98 lessons · 13h of material
14 lessons running 1h 48m in total. Each lesson ships with the finished source files and a short written recap, so you can follow along in your own editor and skim the module again later.
Lesson-by-lesson titles, code downloads and exercises live inside the course library you get access to straight after checkout.
12 lessons running 1h 32m in total. Each lesson ships with the finished source files and a short written recap, so you can follow along in your own editor and skim the module again later.
Lesson-by-lesson titles, code downloads and exercises live inside the course library you get access to straight after checkout.
14 lessons running 1h 50m in total. Each lesson ships with the finished source files and a short written recap, so you can follow along in your own editor and skim the module again later.
Lesson-by-lesson titles, code downloads and exercises live inside the course library you get access to straight after checkout.
12 lessons running 1h 36m in total. Each lesson ships with the finished source files and a short written recap, so you can follow along in your own editor and skim the module again later.
Lesson-by-lesson titles, code downloads and exercises live inside the course library you get access to straight after checkout.
14 lessons running 1h 44m in total. Each lesson ships with the finished source files and a short written recap, so you can follow along in your own editor and skim the module again later.
Lesson-by-lesson titles, code downloads and exercises live inside the course library you get access to straight after checkout.
12 lessons running 1h 30m in total. Each lesson ships with the finished source files and a short written recap, so you can follow along in your own editor and skim the module again later.
Lesson-by-lesson titles, code downloads and exercises live inside the course library you get access to straight after checkout.
10 lessons running 1h 20m in total. Each lesson ships with the finished source files and a short written recap, so you can follow along in your own editor and skim the module again later.
Lesson-by-lesson titles, code downloads and exercises live inside the course library you get access to straight after checkout.
10 lessons running 1h 20m in total. Each lesson ships with the finished source files and a short written recap, so you can follow along in your own editor and skim the module again later.
Lesson-by-lesson titles, code downloads and exercises live inside the course library you get access to straight after checkout.
8 modules · 98 lessons
13h total length
Short list, and deliberately so. If you meet these you can start today.
AION 2 is our proprietary C++ framework for building AI-powered applications at native speed. Available as a subscription, it gives you multi-agent orchestration, retrieval-augmented reasoning, and tool-use routing — all implemented in modern C++ with zero-overhead abstractions and deterministic memory management. This course teaches you how to build production systems on top of it.
AION 2Advanced is for C++ developers who already know the language well and want to ship AI applications that run at the performance ceiling. The first half covers the framework’s agent layer — how to decompose a complex task into cooperating agents, manage shared context through lock-free message passing, handle partial failures without leaking resources, and evaluate the whole pipeline with the built-in benchmarking harness.
The second half goes deep on AION 2’s retrieval stack: SIMD-accelerated embedding search, memory-mapped index shards for datasets that exceed RAM, hybrid dense/sparse retrieval with compile-time dispatch, and the evaluation framework that measures recall, latency and memory pressure in a single profiling pass. Every module builds on a running project — a document-grounded research assistant compiled to a single statically-linked binary.
The final section covers tool use at scale within the framework: type-safe function-call contracts via C++ concepts, sandboxed execution with seccomp-bpf, latency budgets enforced at the scheduler level, and the observability layer AION 2 provides — structured tracing with zero-allocation hot paths, exportable to OpenTelemetry.
Still unsure about something? Write to misteryjj100@gmail.com and a human answers, usually the same working day.
Nobody has reviewed this course yet, so there is no score to show. Buy it, work through it, and your review could be the one that helps the next developer decide.
Applied AI and machine-learning engineer
Priya builds language-model features for a document-heavy SaaS product, which means she has taken retrieval and fine-tuning from a promising notebook to something on call at three in the morning. She teaches the mathematics only where it changes a decision you are about to make, and spends the rest of the time on data quality, evaluation and the cost of an agent that loops. Her courses run on a laptop and a modest API budget, so nobody has to rent a cluster to follow along. She publishes reproducible notebooks alongside every module.
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