00_COMMAND — The Master Layer¶

Brother, here it is. Thirteen months. One transformation. Everything you need lives inside this fortress. This file is the front door.

Preface — What You Asked For¶

You said: “please help your son man.”

So this whole fortress is written in that register: mentor + best friend + guide + the person who cares whether you actually get there, not just whether the plan looks good on paper. The seed doc you brought me is the 366-line 8-phase roadmap in artifacts/sat-4-jul-2026/. This directory (13_MONTH_ROADMAP/) is what that seed became after a 7-subagent research swarm verified every claim, elevated 2025–2026 realities the seed couldn’t have known (FlashAttention-4, vLLM V1, Dynamo 1.0, MI325X production stories, rotation-based quantization, rollout-infrastructure as a niche), and wrote 130+ markdown files across 14 subdirectories.

You will not read all of it in one sitting. You are not supposed to. It is a fortress, not a book. You walk it phase by phase, month by month, as the calendar hits each section.

What This Is (and What It Is Not)¶

This is:

A 13-month, viking-disciplined transformation from Applied ML at Zoho to full-stack inference engineer.
A structured curriculum grounded in eight production-portfolio artifacts (the “portfolio ladder” in ../12_portfolio/), not in credentials or courses.
A mentor’s honest opinion of what actually matters and what is noise, verified against community sentiment, GitHub source, live papers, and 2026 production war stories.
A plan that respects the fact that you have a full-time Zoho job, a family, a body, and a life outside the terminal.

This is not:

A certification track. Nobody in this field hires on certificates.
A tutorial index. Tutorials are Layer 7 marketing; source code and benchmarks are Layer 1 truth.
A guarantee. The reward comes from doing the work, not from possessing the plan.
A prison. The reset protocol in ../99_pre_mortem/09_summary_and_reset_protocol.md exists precisely because plans meet reality.

The Constitution — The Three Numbers¶

Everything in this fortress compiles down to these three sentences. Learn to feel them.

Arithmetic Intensity = FLOPs / Bytes moved. Every GPU has a ridge point. An H100 sits around 295 FLOPs/byte (989 TFLOPs BF16 / 3.35 TB/s HBM3). B200 pushes higher. Operations below the ridge are memory-bound; above it, compute-bound. This is the entire performance story.
Decode is memory-bound. Generating one token = streaming every parameter + KV cache through memory to do a small amount of arithmetic. This is why batch size, quantization, and KV-cache management dominate decode throughput. It is why a 4090’s bandwidth matters more than its TFLOPs for local inference.
Prefill is compute-bound (at non-trivial prompt lengths). Prefill is big GEMMs with high arithmetic intensity. The asymmetry between prefill and decode is the origin of chunked prefill, disaggregated serving, and half the modern scheduling literature.

If you deeply understand why these three are true, you already know more than 90% of people writing “LLM inference optimization” blog posts. Every phase in this fortress elaborates one of these three principles.

The Phase Map¶

Phase	Months	Focus	Vertical Directory
P0	M1 (M0.5 start)	Systems, C++, math foundations	`../01_foundations/`
P1	M1–M3	Transformers from scratch (own every line)	`../02_transformers/`
P2	M3–M6	GPU architecture, CUDA, Triton, SGEMM ladder	`../03_gpu_kernels/`
P3	M5–M7	FlashAttention lineage, write FA2 in Triton	`../04_attention/`
P4	M7–M9	Inference engines: vLLM, SGLang, mini-engine capstone	`../05_engines/`
P5	M8–M10	Quantization bake-off, Marlin gap analysis	`../06_quantization/`
P6	M9–M12	Distributed serving + training + rollout infra	`../07_distributed/`
P7	M10–M13	Production, on-prem, reference architecture	`../08_production/`

Overlap is intentional. Kernels start before transformers finish. Engines start before kernels are polished. The overlap is where compound learning happens.

The Eight Portfolio Rungs (North-Star Artifacts)¶

You are not judged on what you know. You are judged on what you have publicly shipped. Every hour of learning must land in one of these eight rungs. Detail in 03_north_star_artifacts.md and ../12_portfolio/.

Rung	Artifact	Month Gate	Vertical Source
R1	CPU tiled matmul writeup with cache-effect measurements	M2	Phase 0
R2	SGEMM ladder repo hitting ~80% of cuBLAS + Nsight evidence	M4–M5	Phase 2
R3	Triton FlashAttention-2 with numerics + benchmarks	M6–M7	Phase 3
R4	Quantization bake-off (8B model, 5 formats, quality × speed)	M8	Phase 5
R5	Mini inference engine (continuous batching + paged KV) vs vLLM	M9	Phase 4
R6	First merged PR to vLLM / SGLang / FlashInfer / llama.cpp	M9–M10	Phase 4 → community
R7	Enterprise reference architecture doc with measured SLOs	M11–M12	Phase 7
R8	Sustained contribution area in a major engine (the job-offer tier)	M12–M13+	Phase 4/6/7

Non-negotiable hard gate: By end of M9, R5 shipped and R6 merged. Everything else can slip and be recovered. These two determine whether M11–M13 is study-conversion or another lap of learning.

The Fortress Tour¶

Fourteen subdirectories. Walk them in order the first time. After that, jump by month.

Directory	Purpose	Files
`00_command/` (you are here)	Master layer: month plan, sprints, KPIs, pitch	8
`01_foundations/`	CS:APP, C++, Python perf, numerics math	6
`02_transformers/`	Karpathy path, nanochat, from-scratch inference, arithmetic notebook	7
`03_gpu_kernels/`	PMPP, GPU MODE, SGEMM ladder, Triton, CUTLASS, Nsight	10
`04_attention/`	Online softmax, FlashAttention 1→4 lineage, fusion, Triton FA2	8
`05_engines/`	Orca, PagedAttention, RadixAttention, spec decoding, mini-engine capstone, vLLM/SGLang source map	15
`06_quantization/`	GPTQ, AWQ, FP8, NVFP4/MXFP4, rotation methods, GGUF, Marlin/Machete	15
`07_distributed/`	5D parallelism, NCCL, DistServe/Mooncake, DeepSeek-V3, rollout infra	19
`08_production/`	vLLM/SGLang prod, K8s for GPUs, autoscaling, on-prem, reference architecture, Zoho leverage plan	15
`09_papers/`	The ~40-paper canon, ordered, with reading schedule	7
`10_communities/`	GPU MODE, r/LocalLLaMA, engine repos, blog canon, X follows, YouTube	8
`11_hardware/`	Own vs rent, 2026 GPU landscape, Apple silicon, budget scenarios	6
`12_portfolio/`	The 8 rungs, one file each, with acceptance criteria	9
`13_discipline/`	Sprint cadence, lab notebook, benchmark hygiene, reading code, teach-to-learn, failure modes, motivation, health, study conversion	10
`99_pre_mortem/`	8 failure modes + reset protocol	10

Total: ~130 markdown files. You will not read all of it upfront. You walk it phase by phase.

How to Read the Fortress (Onboarding Sequence)¶

Week 1:

This file (you’re doing it).
01_month_by_month.md — see the full arc.
../13_discipline/README.md — set the tone.
../99_pre_mortem/README.md — see the failure modes now, before they surface.
../11_hardware/README.md — buy or don’t buy the 3090 decision.

Week 2: 6. ../01_foundations/README.md — start Phase 0. 7. 04_weekly_rhythm.md — install the schedule. 8. ../13_discipline/02_lab_notebook.md — start the notebook on day one.

Every Sunday evening: 05_kpi_dashboard.md — the retro template.

Every quarter end: 06_zoho_alignment.md — is your Zoho work aligning with the roadmap? Time to renegotiate?

When something goes wrong: ../99_pre_mortem/09_summary_and_reset_protocol.md. Not before.

The Discipline Doctrine (One-Line Summary)¶

“Learn to predict the number before you measure it, at every layer from a warp to a fleet.”

That is the whole meta-skill. Every phase-exit criterion demands it. Every lab-notebook entry expects it. Full doctrine: ../13_discipline/.

The Pre-Mortem Constitution¶

The eight failure modes named in ../99_pre_mortem/ — from industry-moves-faster to family-health-life — are not obstacles to work around. They are load-bearing acknowledgments. Especially file 08, the unspeakable one:

The roadmap serves you. You do not serve the roadmap.

If any file in this fortress ever asks you to sacrifice your body, your parents, your relationships, or your sanity to hit an artificial 13-month deadline — that file is wrong, and you have permission to ignore it. Reset protocol: ../99_pre_mortem/09.

The M13 Pitch¶

The sentence you will say in your first-round study at month 13:

“I build agentic services on top of LLMs AND the inference/rollout infrastructure that serves them — I understand every layer from the HTTP request to the tensor core, including the multi-node fabric between them.”

Full variants in 07_thirteen_month_pitch.md.

Closing Note¶

Fourteen months from now, you’ll open this file again. If everything went well, you’ll smile because most of what’s here landed. If some things went sideways, you’ll smile because the fortress warned you and you adjusted. Either way, you will be someone who understands the stack from HTTP to HBM — and that is not many people.

I’m proud of you for starting. That’s the hardest part.

Now go read 01_month_by_month.md.

— your mentor, best friend, guide.

Master fortress: You are at the root. Return here anytime.