Use AI Or Lose

The operational alpha layer for deep-tech founders. $29 one-time — five workflows of named guides for every non-engineering function. No subscriptions.

You are a PhD founder building a humanoid robot. A materials scientist authoring the next solid-state battery. A chip designer at a sub-100-person semiconductor startup. You understand AI deeply enough to build it. What you don't do, almost universally, is use it for business.

That gap is the most expensive thing in deep tech right now.

Your competitors at the consumer SaaS startup down the street are running ten-person sales teams that produce the output of a hundred-person sales team because they are using AI for cold outreach, ICP refinement, vertical research, and competitive intelligence. They are doing patent searches in two hours that used to take their lawyers a week. They are writing fundraising decks with AI co-authors that get the deck right on the third draft instead of the eighteenth.

You are running your sales team at one tenth the cadence the same AI would let you run at. You are paying patent counsel $1,200 an hour for prior-art searches AI does in fifteen minutes. You are letting your fundraising deck take six weeks to land because it gets one editor pass per week.

The reason for the gap is cultural, not technical. Deep-tech founders treat AI as a thing they build, not a thing they use. The model that is winning right now: AI is the substrate the entire business runs on, and the engineering team is one of fifteen functions that AI accelerates.

DeepTechTools is the operational alpha layer for deep-tech founders. Five workflows. One package. The named guides ship June 15, 2026; tools and updates ship across the rest of the year.

The $29 Package — five workflows, named guides, lifetime access

$29 one-time. Pay once. Owned forever. No subscription, no recurring billing, no upsell wall. Money-back inside 30 days post-purchase if it doesn't pay for itself.

Five workflows. Each is a coherent strategy for one non-engineering function — IP, sales, data, fundraising, science. The Guide (60-page workbook) opens with the framework; the named guides ship across 2026 and arrive in your inbox as each lands.

Workflow 1 — IP Strategy & Patent Research
Prior-art search · FTO triage · standards thinking · attorney-handoff briefs

Replace the $5K-15K associate-hour search with a 90-minute Claude session that surfaces the prior art that matters, flags FTO concerns, and produces the brief your patent attorney can act on. Counsel is for opinion letters and litigation; AI is for everything upstream.

Named guides in this workflow:

Workflow 2 — Vertical Sales & Buyer Mapping
Buyer maps · decision-maker ID · cold-email register · standards-body engagement

Find the right buyer at the right account faster than your competitors, with the right framing for the vertical. The deep-tech sales motion runs on relationships and credibility — AI multiplies how many credibility-building moves you can make per quarter, without diluting the bar.

Named guides in this workflow:

Workflow 3 — Data Strategy & Monetization
Data classification · privacy classes · licensing rate cards · the ban list

Operational data is most deep-tech founders' second-most-valuable asset and the one they monetize least. Workflow output: a complete data inventory classified by type, granularity, and privacy class; a buyer map for your data; a licensing term sheet; the ban list of fields you can't safely sell no matter who offers.

Named guides in this workflow:

Workflow 4 — Fundraising & Cap Table Operations
Investor matching · deck generation · cap-table modeling · term-sheet analysis · board prep

Compress the 16-week deep-tech raise into 8 weeks. Workflow output: a filtered investor list with warm-intro paths; a deck right on draft three; cap-table scenarios run live in the partner meeting; term-sheet analysis catching the clauses you'd otherwise miss; board-prep templates for the four standard agendas (operating, fundraising, M&A, crisis).

Named guides in this workflow:

Workflow 5 — Literature Review & Hypothesis Generation
Lit synthesis · hypothesis ranking · experimental design · standards engagement

Run literature review at the speed of conversation, not the speed of postdocs. Workflow output: a publication-quality "background and prior art" section in 4 hours instead of 2 weeks; ranked hypotheses with citations to adjacent prior work; experimental designs that match what your domain's reviewers expect.

Named guides in this workflow:

$29 one-time · pre-order open · buy-link sends June 15, 2026
The Package: five workflows + The Guide + Monday Briefing

Pre-order via the Monday Briefing list. The day The Guide ships (June 15, 2026) we email you the $29 buy-link. No payment until then.

Pricing

Two ways in. Free Monday Briefing. $29 Package. No subscriptions.

Free
Monday Briefing — no login, no email gate beyond the briefing list itself

Weekly briefing with one new artifact, one tool update, and one founder-relevant signal from the deep-tech operating environment. Live now. Subscribe via the pre-order form above.

The Package · $29 one-time
Lifetime access — five workflows + The Guide + every named guide as it ships through 2026

Full description in the Package section above. Pay once, owned forever, no recurring billing. Money-back 30 days. Buy-link sends the day The Guide ships, June 15, 2026 — pre-order by joining the briefing list.

Enterprise · inquire
Custom research · white-label artifacts · portfolio access for VC and accelerator firms

For deep-tech companies running 50+ people, VC firms wanting portfolio-wide alpha, federal programs supporting deep-tech ecosystems (Manufacturing USA institutes, MEP centers, accelerator-affiliated funds). cv@ashibaresearch.com — engagements $25K+.

Creators, podcast hosts, and operators with a deep-tech-adjacent audience: comp access available. We give you the package free and a referral link; you keep 100% of revenue from sales it drives. Email cv@ashibaresearch.com.

About

DeepTechTools is built by Cooper Veit at Ashiba Research, an applied research lab in New York. DTT is one of five Ashiba programs, alongside Kernel Contracts (silicon-level AI verification), ProbSpec (industrial-data conformance for brownfield interop), Prime Standard (approval-boundary research applied to outbound trust claims), and Ashiba Alignment (heterogeneous-substrate alignment research).

The lab posture: small on purpose, calibrated to questions that have a clock, ships in hours, not quarters. DTT is the operator-facing layer — the alpha working deep-tech founders need to run their businesses at AI cadence rather than 2015 cadence. Workflows, not prompts. The site is the alpha.

DeepTechTools reflects years of hard-won lessons from academic research, Cooper's experience as a deep tech VC and tech scout for Japanese corporations, an associate at the top IP consulting shop, and founding/sole GTM at an AI startup called Garden that sold for $150M. Every sleepless night and desperate anagnorisis crystallized, distilled, and weaponized as pure alpha for your work.