Bian-Ford's MavGit — I JUST WANT TO Blind-DRIVE Software for MavPLC Automation (Let Ordinary People Drive!) — NueraPump presents Bian-Ford's MavGit — I JUST WANT TO DRIVE: a thesis on converting inexpensive synthetic intelligence into usable, maintainable, and broadly accessible software for automation. Its central distinction is that expert amplification does not establish mass adoption. Machines producing most source code demonstrate a change in implementation capacity, not necessarily equivalent improvements in complete delivery, ordinary user independence, affordable recovery, or household welfare. Software productivity must therefore be examined through model capability, production organization, service responsibility, sustained use, and the distribution of benefits. Success at one layer cannot substitute for evidence at another. The historical analogy concerns complementary reconstruction rather than technological hero worship. Water, steam, and electricity altered industrial constraints, but inherited locations, transmission arrangements, equipment, logistics, and responsibilities could delay their exploitation. Independent electric drives expanded opportunities to arrange machines around production processes. Ford combined precision, interchangeability, material movement, and coordinated operations; subsequent cellular and island arrangements illustrate further possibilities for reorganizing tasks and resources. These examples do not establish an inevitable sequence of universal manufacturing generations. Their transferable principle is to reconsider existing couplings when technologies and requirements change, removing unnecessary dependencies while preserving necessary coordination. Yesterday's breakthrough can become tomorrow's constraint. The same reasoning applies to software. Replacing programmers with agents inside unchanged approval chains, fragile interfaces, inaccessible data, and unclear maintenance responsibilities can accelerate intermediate production without increasing accepted business outcomes. Generated code waiting for integration, validation, deployment, or repair becomes work in process. A fixed workload example illustrates the limitation: accelerating coding one hundredfold yields approximately 1.42 times overall speed when coding originally occupies thirty percent of the process and everything else remains unchanged. This is an explanatory assumption, not an industry estimate. Constraints can migrate upstream, downstream, or across the organization as improvements proceed. The proposed software Ford moment consequently requires more than rapid construction. An ordinary person must express a business purpose, receive a working system, request meaningful changes, encounter failures, obtain recovery, and return weeks later without acquiring implementation expertise. Normal operating knowledge remains necessary; programming, database administration, dependency repair, and architectural diagnosis should not become conditions of continued use. Maverick's reported experience across approximately fifteen programming languages, networking, algorithms, architecture, and encryption is explicitly recognized as potentially hidden expert input. Not typing code does not prove that engineering judgment has disappeared. MavGit is defined as MavIntent plus MavPi. MavIntent separates business sovereignty from technical responsibility. Users articulate purposes, preferences, prohibitions, and recognizable outcomes; the service clarifies consequential ambiguities and compiles these intentions into bounded contracts covering behavior, interfaces, permissions, state, verification, and recovery. Users need not anticipate every failure. Defaults, examples, previews, and targeted questions should reveal meaningful choices without transferring specification engineering back to them. Contracts declare their coverage, assumptions, external dependencies, unresolved uncertainties, and escalation paths instead of claiming exhaustive knowledge. Interface design belongs within this responsibility. A user requesting convenient editing, preserved drafts, and protection against accidental deletion should not have to prescribe button placement or form architecture. MavPi governs bounded changes through testing, observation, loss identification, repair, rejection, rollback, and promotion. Current Stable provides a sufficient operational starting point without requiring repeated reconstruction of conversational history, while retaining necessary evidence, dependencies, permissions, and recovery information. Code rollback cannot reverse payments, messages, inventory movements, or altered records automatically. Restoration may require reconciliation, compensation, or accountable professional intervention. Local computation and portable state containers can reduce unnecessary central traffic, but relocating work does not eliminate its resource cost. File counts likewise cannot substitute for measurements of understanding burden, change propagation, isolation, and recoverability. Five management frameworks guide application: Porter's value chain examines complete delivery; architectural innovation examines recomposed relationships; Christensen's disruptive innovation directs attention toward underserved needs; jobs to be done anchors design in actual purposes; and the service profit chain connects equipped support teams, reliable service, trust, and sustainable operations. These frameworks organize questions rather than certify results. The accompanying song translates them into a journey from industrial excitement through congestion, expert pride, ordinary user failure, repair, economic doubt, and conditional hope. Repeated driving refrains provide retrieval cues, not evidence of immediate permanent memory. Validation begins with a proposed trial involving eight consenting adults without relevant engineering backgrounds over twenty eight days. Tasks cover creation, change, expired authentication, interrupted connections, duplicate submissions, conflicting actions, repair, and return after an upgrade. Existing features, configuration, and newly generated behavior are reported separately. Product completion and standard service assistance may satisfy the driving criterion; forced technical work and hidden expert rescue must be disclosed. Withdrawals, failures, disputes, and all support effort remain visible. A suggested seven of eight threshold is a pilot management choice, not statistical proof or universal adoption. Evaluation records technical burden minutes, complete human effort per comparable accepted task, provider recovery costs, waiting, incident frequency, unresolved damage, and repeated failure. Customer affordability and provider sustainability require separate accounts; subscription payments cannot be counted twice when estimating combined resource consumption. Reusable repairs must demonstrate reduced dependence on exceptional individuals without concealing deteriorating quality or costly outliers. Cross domain replication measures additional adaptation rather than demanding identical implementations everywhere. The framework shares Q-Meter's discipline of verified outcomes per irreversible human time while distinguishing business improvement from independent human learning. Educational capability still requires appropriate cold start, retention, and transfer assessment. State change alone is not progress; declared value mappings and constraints establish direction. Q describes the chosen rate, while declining Q can mean slower improvement rather than regression. Finally, inexpensive production does not guarantee purchasing power. Household access, prices, income, available time, and necessities require separate observation; capability records must not be confused with spendable claims. The resulting proposition remains conditional: human purpose guides action, services bear measurable technical responsibilities, bounded experiments expose failure, and reality determines which candidates deserve continued use. The objective is to remove dead waiting, not the time required for continued human judgment. Evidence lets a stranger change the journey, survive an upgrade, return next month, and keep driving, with explicit service boundaries, accountable repair, and support costs that remain affordable as participation grows.