OPENWORKLOAD

INDEPENDENT AI INFRASTRUCTURE DECISION SPRINTS

AI infrastructure.
Decision sprints.

Independent senior technical judgment on one consequential decision, supported by evidence and tools. Starting with Enterprise Readiness for infrastructure startups.

Discuss your pending decision

A private, 15-minute fit conversation.

ONE DECISION. RELEVANT EVIDENCE.
01 / REQUIREMENTSCustomerWhat must hold
02 / CONSTRAINTSWorkloadWhat must run
THE EVIDENCE UNDERNEATH
DesignTestsTelemetry
Assumptions and evidence gaps made visible
Evidence → alternatives →A clear recommendation
A review framework, not live customer data.
Customer readiness. Capacity. Training. Inference.Start with readiness

Deep infrastructure experience.
Independent technical judgment.

Past experience planning billion-dollar-scale AI infrastructure, applied to the decision in front of you.

Workload context. Explicit assumptions. Practical recommendations.

FIRST SPECIALIZATION

Enterprise Readiness.

For infrastructure startups preparing for a demanding customer evaluation. Align the target workload, technical evidence, and operating requirements before making the commitment.

01

For infrastructure startups

Know what your next customer will need to see.

Can your infrastructure support the workload and operating requirements?

Translate a target customer’s requirements into a focused evidence review. Examine architecture and benchmark evidence, reliability and operating gaps, and the risks that matter to the pending customer decision.

Leave with a readiness recommendation, agreed acceptance tests, and a prioritized plan your team owns. Readiness is assessed against the target requirements, with evidence gaps made explicit.

  • Architecture & benchmarks
  • Reliability & operations
  • Customer requirements

The same sprint discipline applies to operator decisions. GPU procurement and capacity commitments, provider and workload placement, training scale and readiness across pretraining and RL, and inference economics. Review useful throughput, capacity opportunities, and constraints across GPU, storage, and network.

WHAT YOU BRING

A real decision.
The relevant evidence.

Start with the decision and the information you are authorized to share. We agree on evidence handling and any gaps before the review begins.

  • Decision, deadline, and owner. What must be decided, by when, and who is accountable.
  • Workload and constraints. Target customer requirements, scale, performance, cost, and reliability needs.
  • Architecture. The relevant system design, dependencies, and operating context.
  • Authorized evidence exports. Benchmark results or telemetry exports, with sensitive information removed.

Selective applications include investor technical diligence and cluster launch or acceptance reviews, with client-run tests and implementation. Bounded ongoing decision advisory is considered after a useful initial engagement.

START WITH THE DECISION IN FRONT OF YOU

What needs
a decision?

A customer evaluation. A capacity commitment. A training or inference decision you need to make with better evidence.

Request a private 15-minute conversation. Share the pending decision, its owner, and the deadline. We’ll establish whether a bounded decision sprint fits.

One decision.
A focused starting point.

Keep it high-level: decision, deadline, and constraints. No credentials, private datasets, or confidential logs. Your details are stored privately for this inquiry and follow-up, along with a network fingerprint for abuse prevention.