unchecked-io/HANDOFF-2026-04-20.md

Handoff — 2026-04-20

What Was Decided This Session

• Commercialization path: Licensing first, IP sale after traction. Wyoming LLC before any contract.
• Language strategy: Rust is source of truth. C++ generated via Whetstone + manual library substitution as enterprise deliverable. Both versions is a deliberate differentiator.
• Primary buyers: GPU cloud providers and LLM inference companies (CoreWeave, Lambda Labs, Together AI, Fireworks AI, Modal). Not PyTorch/Meta.
• Hugging Face is a secondary buyer worth a conversation — they own the tokenizers crate this code already uses.
• NVIDIA contact: Approach after H100 benchmark. Send Nsight trace + one paragraph. Not before.
• NM funding: Apply for NMSBA (Sandia/LANL hardware access). Skip money grants for now.
• Outsourcing: Friend's software business for non-core work. 60-70% of contract value for defined scope. IP assignment clause required in writing first.

Documents Created This Session

File	Purpose
ROADMAP.md	Full technical development plan, Phases 1–5
docs/talk-10min.md	10-minute presentation structure for Wednesday
docs/commercialization-strategy.md	Pricing, B2B sales process, structure, outsourcing
HANDOFF-2026-04-20.md	This file

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This Week — Time-Sensitive (in order)

Before Wednesday

• Fix Phase 1.1 — dynamic buffer allocation (src/llm.rs, PinnedBatcher::new)
• Fix Phase 1.2 — buffer isolation / DLPack overwrite bug
• Fix Phase 1.3 — thread-safe engine pool (TokenizerEngine takes &mut self)
• Fix Phase 1.4 — padding for variable-length sequences

Wednesday

• Rent H100 on Lambda Labs (~$2 for 30 min)
• Run benchmark_gpu.py under nsys profile --stats=true python benchmark_gpu.py
• Capture Nsight .nsys-rep file and download it
• Note the speedup number — this is the headline for the talk

Wednesday/Thursday

• Update docs/talk-10min.md Slide 6 with the H100 result
• Open Nsight Systems GUI locally, load the .nsys-rep file, screenshot the timeline showing both pipelines

Thursday (if someone gives you a contact after the talk)

• Do not show GPU source code without NDA signed first
• First call is discovery — ask about their infrastructure before pitching
• Pricing range if pushed: $50K–$150K annually depending on scale

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Next Session Priorities (after this week)

1. H100 setup script — a single paste-into-terminal script for the cloud instance (was going to write this, ran out of session). Needs: Rust install, maturin build with --features gpu, nsys profile run, output capture.
2. Phase 1 fixes — if not completed before Wednesday, finish these
3. vLLM integration — Phase 2.1, this is the demo that sells the concept
4. NM anonymous LLC — straightforward to form locally, no member names in public filings, no annual report requirement
5. C++ version scoping — after Phase 1 is solid, assess Whetstone transpilation of llm.rs

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Key Technical Context for Next Session

• Repo is cloned at /home/bill/Documents/unchecked-io/, currently on gpu-zero branch
• GPU feature is compiled with maturin develop --release --features gpu
• The four Phase 1 bugs are documented in detail in ROADMAP.md Phase 1 section
• src/llm.rs is the file to fix — PinnedBatcher struct, batch_encode_to_gpu method
• src/lib.rs TokenizerEngine wraps PinnedBatcher and is the Python-facing class
• chrono-tz is pinned at =0.10.4 — do not change this, it was hard-won
• gpu-zero branch is private; main branch is open source Apache 2.0