Why we released codex-strict-profile for larger codebases
An experimental public Codex profile for teams that need more verification, broader code reading, and clearer risk boundaries on medium and large codebases.
ReadPredictable embedded delivery
Flexible staffing that ships, not thrashes
We embed engineers and small delivery pods into your repos and workflows, increasing capacity while keeping quality, security, and communication disciplined.
A structured onboarding and governance loop (backlog, acceptance criteria, reviews, tests, verification, written decisions) makes delivery predictable and maintainable.
Free online consultation
We clarify goals, constraints, and success metrics so the work stays coherent.
Project pipeline
We map delivery into stages with quality gates, scope boundaries, and clear ownership.
Statement of work (SoW)
You get a fixed, accountable plan with deliverables, milestones, and a pricing model that makes sense.
Embedded engineers
Delivery pods
Structured onboarding
Code review discipline
QA gates
Security-aware
Async-first cadence
Continuity and handoffs
Structured onboarding
We align access, environments, standards, and a definition of done so the engineer can ship end-to-end with minimal friction.
Quality and governance loop
Work stays in one backlog with clear acceptance criteria, reviews, and verification. The goal is higher throughput with fewer regressions.
Continuity over churn
We keep knowledge in the system through documentation, ownership, and clean handoffs when scope changes or staffing scales down.
FEATURED INSIGHTS
Flexible Developer Staffing, without hype.
Decision tools, patterns, and delivery governance for teams planning a service investment.
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A practical guide, grounded in a ViaRah case study, to shipping portals, workflow apps, and dashboards quickly with Django + Vue, plus a gut-check on when Vue is worth it and a build checklist.
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Before You Fund Another AI Pilot, Fix the Operating Model
AI pilots look promising until handoffs, ownership, and approvals get messy. This guide shows leaders how to make AI automation safe to run at scale.
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