Design partner opportunity
Training Workbench
Help us test whether another person can run a local training job from start to finish, recover after an interruption and check the results.
Your starting point
Would this help?
This is a fit when
- A partner that needs one reproducible local training/evaluation workflow
- A team willing to test portability and operator independence rather than buy a generic platform
When another approach is a better fit
- A managed general-purpose training platform
- Indefinite tuning, unsupported data rights, or a requirement for a production model outcome
What we’re planning
Proposed outcomes.
- 01Reproducible environment and source/data/model identities
- 02Tokenizer, cache, training, exact-resume, and held-out evaluation records
- 03Generation/reload checks and normalized evidence pack
- 04Operator runbook, intervention log, and witnessed second-operator result
Where this stands
Built so far. What comes next.
A second operator must complete the full bounded 14-stage workflow on a fresh workstation using approved open or synthetic data, with interruption/resume and portable artifacts.
Existing basis
- A registered 14-stage data, tokenizer, training, evaluation, evidence, and release workflow
- Source identities, recovery, evidence, and clean-room control surfaces
- Substantial internal training/workbench implementation
Evidence still needed
- Full 14-stage fresh-workstation execution
- Second-operator completion with founder interventions measured
- End-to-end artifact portability and customer-operability evidence
Working together / 8–16 weeks after gate
How we’ll work together.
Agree the training job a second person should be able to run. Co-development waits until the independent-operator check is ready to run.
The project steps in detail
- 01Discovery and environment qualification.
- 02Freeze the workflow, identities, rights, operator, and acceptance path.
- 03Run the workflow and recovery checks under controlled observation.
- 04Repeat with a second operator on a fresh target.
- 05Accept, remediate, redesign, or stop.
What we need before work starts
Before starting
- One lawful dataset/right set and bounded model/profile
- A supported target workstation and named operator cohort
- A frozen acceptance protocol, holdout, and compute ceiling
- Permission to preserve failures and reproducibility evidence
Scope and handover
What we agree before starting.
We agree the work in a signed statement of work before starting. This page explains the offer; the signed agreement sets the commitment.
How you accept the handover
- A fresh target workstation completes the scoped data-to-evidence path from source identities.
- A second operator completes the workflow using the runbook and records founder interventions.
- Interruption/resume, evaluation, artifact hashes, portability, and limitations pass the signed matrix.
- Any optional benchmark, gateway, or deployment step is accepted only if separately scoped.
What this work covers
Co-development only after the independent-operator gate is ready to run.
One registered data-to-evidence workflow, environment, operator cohort, model/profile, rights set, and acceptance protocol. Not a general training platform.
A minimal fresh-clone documentation/schema/contract check is not evidence of a complete customer data-to-training workflow.
Offer source and review record
Talk to us
What’s getting in the way?
Tell us what keeps going wrong and what you need to do once it’s sorted. We’ll come back with what we think could help.