Choose to begin; progress will learn to follow. — Ada Lovelace
The Choice That Creates Motion
Lovelace’s line pivots on a deceptively simple truth: direction emerges from decision. By choosing to begin, we generate the very conditions under which improvement becomes possible. Uncertainty narrows as experiments return signals; competence compounds as we iterate. In other words, initiation is not the end of doubt but the engine that converts doubt into data. Consequently, the first move carries outsized leverage. Effectuation research in entrepreneurship shows that practitioners often start with available means and discover achievable goals along the way (Sarasvathy, 2001). Rather than wait for perfect plans, they step, see, and adjust. In this frame, progress does not precede the choice; it learns to follow it.
Lovelace’s Computational Foresight
To ground the idea historically, consider how Lovelace herself worked. Translating Menabrea’s paper on Babbage’s Analytical Engine (published 1843), she did not stop at explanation; she began to extend, annotating with speculative and technical Notes. In the famed Note G, she sketched an algorithm for Bernoulli numbers and envisioned machines handling symbols beyond arithmetic, including music structured by rules. The machine was not built, yet beginning in thought opened a path for progress in concept. Her annotations functioned like a prototype on paper, revealing capabilities by simulating them. Thus, the act of starting—first as translator, then as theorist—created a runway that subsequent generations would taxi down.
Momentum and the Psychology of Action
Transitioning to psychology, research repeatedly shows that action begets motivation. Behavioral activation therapy demonstrates that small, structured actions can lift mood and increase engagement, even when motivation is low (Jacobson et al., 1996). Likewise, the Zeigarnik effect suggests that initiated tasks stay cognitively alive, tugging us toward completion (Zeigarnik, 1927). Practical mechanisms support this: implementation intentions—if-then action plans—dramatically raise follow-through by reducing ambiguity at the moment of choice (Gollwitzer, 1999). The lesson aligns with Lovelace’s maxim: begin in micro, and momentum will scale in macro. Start a five-minute draft; the brain often keeps writing.
Iteration as a Scientific Habit
Moreover, science advances through beginnings that invite refinement. Deming’s Plan-Do-Check-Act loop (1950s) and the Agile emphasis on short sprints (Agile Manifesto, 2001) formalize a rhythm where each cycle makes the next smarter. Edison’s relentless filament trials—thousands by some counts—did not waste time; they mapped the problem space until a durable solution emerged (Edison patent, 1880). The pattern is consistent: a preliminary test produces feedback, which reshapes the next test. Starting is not a hasty indulgence; it is the only way to discover constraints you cannot theorize away. Progress follows because each iteration learns.
Creative Drafts and Entrepreneurial MVPs
Extending this logic to practice, writers and founders ritualize beginnings. Anne Lamott’s counsel on messy first drafts (Bird by Bird, 1994) reframes early imperfections as fuel, not failure. In startups, The Lean Startup popularized the minimum viable product to catalyze the build–measure–learn loop (Ries, 2011). Both approaches prioritize shipping a testable version over defending an immaculate idea. Crucially, this is not settling for mediocrity; it is sequencing excellence. By front-loading learning, creators let evidence guide refinement. The act of beginning converts speculation into signals, and those signals direct progress with far greater precision.
Learning Through Constraints and Absence
Finally, Lovelace’s milieu illustrates how progress follows even without full resources. The Analytical Engine never ran, yet its conceptual start—abstract architecture, punched-card control inspired by the Jacquard loom—seeded a lineage that Turing would formalize in computability decades later (Turing, 1936). When reality withholds a lab, paper becomes the laboratory. This underscores a counterintuitive comfort: you need not have everything to start, but you must start to know what you truly need. In beginning, we expose gaps, gather constraints, and attract collaborators. Thus, as Lovelace suggests, choose to begin; the curriculum of progress will assemble itself around your first step.