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Course Intermediate

The Architect's Role

By the end of this course

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01

What Is Architecture

The definition and scope of architecture: telling apart decisions that are expensive to change, separating the application, solution, and enterprise levels by decision scope, the decision, communication, and oversight responsibilities, how a decision cut off from the code becomes the ivory tower problem, and carrying the decision to the team through consulting and coaching.

  1. 01 Software Architecture Definition Defining software architecture as a set of decisions that are expensive to reverse: reading each decision's cost of reversal from the dependent closure in a model codebase, ranking decisions by that number, writing down the source of the threshold, and comparing that ranking against one by body size.
  2. 02 Architecture Levels Separating application, solution, and enterprise architecture by decision scope: distributing the same set of decisions across three levels by how many units they operate, the number of decisions each level covers and the number of units it affects, and the counts of uninformed units, repeated decisions, and conflicting implementations when a decision is made at the wrong level.
  3. 03 The Architect's Responsibilities Building the decision, communication, and oversight responsibilities as a matrix: translating a decision into a machine-auditable constraint form, running the supervised and unsupervised schemes with the same edge sequence on a codebase that grows shortcuts, the share of decisions with no counterpart left in code, and the hour distribution across the three responsibilities.
  4. 04 The Architect and Developer Relationship Modeling the ivory tower problem as a knowledge gap: keeping the import graph the decision-maker knows separate from the actual graph, running the hands-on and hands-off schemes on the same sequence of changes, and counting the stillborn-decision rate, the average knowledge gap, and the feedback delay.
  5. 05 Consulting and Coaching Conveying the same decision as a directive, a written rationale, and by working together: separating the common case from the edge case, measuring the correct-application rate and the cost of conveyance in a two-wave model, and counting which form of conveyance survives a team change.

02

The Architect's Practice

The daily practice of decision: reconciling conflicting quality attributes, deliberately reducing complexity, making reversible and irreversible decisions with separate methods, communicating with non-technical stakeholders, evaluating technology through maturity, ecosystem, and exit cost, and the learning discipline that sustains knowledge freshness.

  1. 01 Striking Balance The practice of choosing between conflicting quality attributes: turning the alternative-attribute table into a data structure, scoring the same table with two weight sets, counting how the winning alternative changes as weight changes through a sensitivity sweep, and tying whether each weight's source is written down to the decision's defensibility.
  2. 02 Simplifying The deliberate reduction of complexity: separating accidental from essential complexity, splitting a solution's module graph's total complexity into two components against the essential floor read from the requirement graph, counting the accidental share simplification removes and the share it cannot, and measuring what grows in return for simplification by running the same change set on both graphs.
  3. 03 Decision Making Making reversible and irreversible decisions with separate methods: computing reversal cost from a dependency set, splitting the same decision set into two classes by that cost, running the quick-trial and long-evaluation methods on both classes, and comparing wait time against wrong-decision cost across four policies.
  4. 04 Stakeholder Management Measuring communication with a non-technical counterpart in a stakeholder model: the same decision's technical-terminology narrative produces 27 questions and 8 rounds, while its outcome-focused narrative produces 0 questions and 3 rounds by eliminating four of six constraints and turning them into four surprises; a third narrative that restores the constraints in plain language brings the total to 3 rounds for four additional statements.
  5. 05 Technology Evaluation Weighting candidate tools by maturity, ecosystem, and exit-cost metrics: a twelve-module source tree is written to disk and scanned, measuring exit cost between 53.0 and 60.5 hours; built-in capability drives total lines from 127 down to 73 while raising exit cost; the winner changes with the weight set; and a wrapper cuts the code share of exit cost from 33.5 hours to 4.0 hours while never reducing the data share at all.
  6. 06 Continuous Learning Discipline Measuring knowledge freshness as a budget allocation: tying a decision's basis to its validity period, counting the rate of decisions turning out wrong when resting on a stale basis over a 72-month run, and showing the same annual 72 hours gives a rate of 0.3958, 0.3715, and 0.2222 when distributed equally, by staleness, and stalest-first.

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