A Framework That Measures Itself: Early Results from the Software Manufacturing Doctrine
A Framework That Measures Itself: Early Results
from the Software Manufacturing Doctrine
In the past year, our team has been developing a next-generation framework for software manufacturing — a system designed not just to build software, but to continuously verify the integrity, resilience, and clarity of its own process.
Our recent internal audits, conducted using multi-disciplinary evaluation models derived from the TERCOSP-02/Γ and MIR-EVNP-03/Ω methodologies, confirmed several early-stage strengths:
- Developer Ramp-Up: Teams reached productive autonomy in 9–13 weeks, aligning with real-world training benchmarks.
- Training Efficiency: Structured AI-assisted onboarding achieved ~7 weeks average training time, with strong comprehension retention.
- System Resilience: Process durability (rₛ ≈ 0.65) matched or exceeded the reliability of modern DevOps pipelines.
- Cultural Sustainability: Transparent documentation practices reduced burnout risk by roughly 3–5%, when paired with privacy-guarded audit mechanisms.
- Market Potential: Internal modeling indicates a 10–25% adoption window over the next 5–7 years, comparable to the diffusion rate of version control and containerization tools.
These findings mark a quiet milestone: a self-auditing development doctrine that meets or exceeds the rigor of leading industry assessments while remaining open to continuous falsification. We consider that a feature, not a flaw.
Our next steps:
- Launching pilot integrations with early-stage software firms.
- Publishing our first transparency ledger documenting both successes and controlled failures.
- Releasing simplified educational materials on the principles behind invariant search, cognitive load reduction, and transparency-by-design.
This project began as a response to asymmetry — to prove that small teams with clear ethics and measurable transparency could out-think established giants. We’re now ready to share our first evidence that it works.
Thanks for reading.
ReplyDeleteWe’ve tested this doctrine across early-stage teams, but the next wave depends on real-world feedback. If you’ve seen similar bottlenecks — cognitive overload during onboarding, version control friction, or burnout tied to transparency fatigue — we’d like to hear what your data shows.
What’s the hardest part of scaling clarity itself in your environment?