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Learn the job, not the syllabus.

Real pull requests to review. Your own courses and textbooks, woven into one path instead of scattered across five tabs. Built for embedded systems engineering — the approach works for any hands-on discipline.

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Bring your own AI key · GitHub token · storage — nothing shared

ring_buffer.c
planted bug
14 uint8_t rb_push(ring_t *rb, uint8_t byte) {
15- if (rb->head == rb->tail) return 0;
15+ if (rb_full(rb)) return 0;
16 rb->buf[rb->head] = byte;
17 rb->head = (rb->head + 1) % rb->size;

You: The full-vs-empty check still uses head == tail. The bug moved behind rb_full().

Model review: Confirmed. rb_full() needs a count field, not only head and tail.

Review verdict: Smaller diff, same bug. The implementation changed; the invariant did not.

Open this PR in the demo
Roadmapphases · weeks · locksWeekly loopread · practice · project · reportMastery gapsold misses stay visibleLabs + studiocheck-offs · diagnosis

The work Atlas trains

Software work is splitting: pre-AI skills for specifying, verifying, and operating systems on one side; prompting and assembling libraries on the other.Atlas trains the first group, with AI present as a tool to inspect, question, and use.

  1. Deterministic reasoning

    State the input, invariant, and reachable paths so the same program behavior can be proved again.

    Open the gap →

  2. Debugging from first principles

    Use gdb/lldb, strace, perf, valgrind, and core dumps to explain failure before asking for a fix.

    Open the studio →

  3. The machine under the framework

    Read caches, memory order, ABIs, compiler output, and kernel behavior beneath the API.

    Open the labs →

  4. Systems that last

    Change brownfield code only after tracing implicit contracts and what the change can break.

    Read it in the guide →

  5. Explicit resource control

    Budget bytes, cycles, latency, and deadlines on machines with no spare accelerator.

    Open the lab constraint →

  6. Language and runtime security

    Review overflow, use-after-free, wraparound, TOCTOU, and side channels as code paths, not checkboxes.

    Open the PR review →

  7. Boring maintainable code

    Keep interfaces small, names exact, and comments focused on why; delete the rest.

    Open the PR review →
Read the full job in the guide

What using Atlas looks like

The app is a working school surface, not a content library.

You add sources, Atlas turns them into scheduled work, then grades proof from assignments, labs, and pull-request reviews.

My Materials

1. Bring sources in

Making Embedded Systemsverified · Phase 1
RTOS course18/24 transcribed
STM32 referencebuilt-in tutorial

Dashboard

2. Do the week

Read2 sections
Practice3 open
Project reportdue Fri

Grades + PR

3. Prove it

You review firstring_buffer.c
Model reviewsame PR
Gap drill1 blocker

It opens a real pull request — with a bug in it, on purpose.

Instead of a quiz, it opens an actual PR on your own GitHub repo with a deliberate flaw tied to what you just learned. You review it like a teammate would — then it posts its own review back onto the same PR, so you compare notes on the real thing, not a simulation of it.

01

It opens the PR

A real diff, on your repo, with one planted issue — never a clean PR.

02

You review it first

Leave comments and flag the issue the way you'd review a teammate's work.

03

It posts its own review

The model's review lands on the same PR, right next to yours, to compare.

Stop learning across twelve open tabs.

Course platforms want you locked into their content. This weaves whatever you already have into one path instead.

Bring the material you already have

A Udemy course you bought and never finished. A YouTube playlist. A PDF textbook. Import them instead of starting over on platform-only content — you choose what to pull from, and it gets woven into one path.

Understands what's on screen, not just what's said

Course video gets transcribed by combining the audio track with on-screen visual analysis — a schematic, a terminal, code — so it actually knows what the video is teaching, not just what was spoken.

Fills the gaps itself

Where a course or book leaves a hole, it generates supplementary reading to cover it. No re-watching a 40-minute video to find the three minutes you actually needed.

Same content. Two honest ways to move through it.

Structured, deadline-paced

Pathway

  • Scheduled weekly reports and projects
  • Exams gate progress phase to phase
  • Long-term spaced review built in

No calendar, prerequisite-ordered

Coding Fast Track

  • Reading → questions → tutorials → problems → mini-project
  • Gated by what you've finished, not a due date
  • Switch to Pathway anytime without losing progress

Switch modes any time in Settings — progress in each stays exactly where you left it.

Personalized engineering roadmap

Phases, weeks, and locks are visible before work starts.

Atlas plans the whole embedded path, then only generates the work you are ready to use. Topics connect to assignments, labs, exams, reading, courses, projects, and must-master requirements.

Roadmap

Generate and revise phase-level topics before a week is built. Topics carry locks, prerequisites, sources, labs, exams, projects, and mastery requirements.

Pathway

The whole journey stays visible: phases, weeks, unlocked work, blocked work, and the current week sitting in context.

Mode switch

Pathway and Coding Fast Track keep separate progress. Switch in Settings without losing progress.

Weekly loop + mastery grading

The week is the work surface, not a progress poster.

Each week runs from source reading through report. The next week stays locked until required evidence meets the rubric. Completion helps; mastery unlocks.

WEEK 2

Ring buffer full vs empty

mastery gate open
  1. 01Readdone
  2. 02Tutorialsdone
  3. 03Materialsdone
  4. 04Practicecurrent
  5. 05Homeworkopen
  6. 06Mini-projectopen
  7. 07Projectlocked
  8. 08Reportlocked
Open the current week

The professor, grader, and gap tracker share the same evidence.

AI work is visible when it happens. It proposes the plan, grades against rubrics, and turns weak answers into the next useful practice instead of hiding them in a score.

AI professor and grader

Atlas generates roadmaps, weekly work, rubrics, exams, reading plans, tutorials, feedback, and rechecks. It grades for mastery, not completion.

Knowledge gaps stay open

Weak answers become visible gaps. Older gaps can block later work until targeted practice closes them.

Rebut and re-evaluate

A strict grade is not a silent grade. You can rebut, preserve evidence, and ask for another pass when the evidence warrants it.

Open since week 1

full vs empty using only head/tail

Equal head and tail values cannot represent both an empty buffer and a full buffer without another invariant.

BLOCKS
UART interrupt-driven receive lab
NEXT EVIDENCE
Add a bounded count field, prove it never exceeds capacity, and cover overflow plus wraparound in tests.
Open the blocker

Labs spine

C, C++, Circuits, and Hardware unlock one at a time. Foundation labs come before major weekly graded work.

Problem Solving Studio

Record expected vs actual, preserve evidence, form a hypothesis, run the experiment, and verify the fix across software, embedded I/O, and hardware.

C SPINE

Next unlock

  1. C toolchain and tests91/100
  2. Pointers and ownership86/100
  3. Circular buffer invariantscurrent
  4. UART receive pathlocked
Open lab checkoffs

Scheduling is allowed to say no.

The planner uses the time you actually have. Catch-Up repairs a bad week. Quick Add makes room for sudden topics only after the workload still checks out.

Weekly Planner

Pack real study blocks with the work that actually fits, not a fantasy calendar.

Catch-Up

Rebalance overdue work without pretending the missed hours still exist.

Quick Add

Add sudden work-needed topics with a realism check before the schedule shifts.

Projects, portfolio, and ungraded tools

Evidence leaves the classroom in a usable shape.

Weekly work, labs, and side projects can become portfolio evidence. Sandboxes stay separate so experiments do not turn into graded work by accident.

Projects + portfolio builderIndependent projects sit outside the weekly cadence. Completed evidence becomes a private case-study draft: architecture, decisions, tests, and feedback.Practice, Playground, TerminalUngraded spaces stay ungraded. Use them to experiment without contaminating graded pathway evidence.Owner monitoringOwner tools cover usage, token spend, media processing health, users, primers, and database state. The learner dashboard stays for learning.

You own your data. Always.

This isn’t a sign-up-and-go SaaS. Every account connects its own credentials — there is no shared platform key anywhere, for anyone, including the person who built it.

AI provider key

Anthropic or OpenRouter — your own account, your own usage.

GitHub token

Scoped to one repo. Used to open and review real pull requests.

Storage bucket

R2, S3, Backblaze B2, Wasabi, DigitalOcean Spaces, or your own S3-compatible endpoint.

Try it without signing up.

The live demo is a shared, pre-filled sandbox — explore every feature before you connect a single key.

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