Cto Advisor

CTO Advisor

Technical leadership frameworks for architecture, engineering teams, technology strategy, and technical decision-making.

Keywords

CTO, chief technology officer, tech debt, technical debt, architecture, engineering metrics, DORA, team scaling, technology evaluation, build vs buy, cloud migration, platform engineering, AI/ML strategy, system design, incident response, engineering culture

Quick Start

python scripts/tech_debt_analyzer.py      # Assess technical debt severity and remediation plan
python scripts/team_scaling_calculator.py  # Model engineering team growth and cost

Core Responsibilities

1. Technology Strategy

Align technology investments with business priorities.

Strategy components:

• Technology vision (3-year: where the platform is going)
• Architecture roadmap (what to build, refactor, or replace)
• Innovation budget (10-20% of engineering capacity for experimentation)
• Build vs buy decisions (default: buy unless it's your core IP)
• Technical debt strategy (management, not elimination)

See references/technology_evaluation_framework.md for the full evaluation framework.

2. Engineering Team Leadership

Scale the engineering org's productivity — not individual output.

Scaling engineering:

• Hire for the next stage, not the current one
• Every 3x in team size requires a reorg
• Manager:IC ratio: 5-8 direct reports optimal
• Senior:junior ratio: at least 1:2 (invert and you'll drown in mentoring)

Culture:

• Blameless post-mortems (incidents are system failures, not people failures)
• Documentation as a first-class citizen
• Code review as mentoring, not gatekeeping
• On-call that's sustainable (not heroic)

See references/engineering_metrics.md for DORA metrics and the engineering health dashboard.

3. Architecture Governance

Create the framework for making good decisions — not making every decision yourself.

Architecture Decision Records (ADRs):

• Every significant decision gets documented: context, options, decision, consequences
• Decisions are discoverable (not buried in Slack)
• Decisions can be superseded (not permanent)

See references/architecture_decision_records.md for ADR templates and the decision review process.

4. Vendor & Platform Management

Every vendor is a dependency. Every dependency is a risk.

Evaluation criteria: Does it solve a real problem? Can we migrate away? Is the vendor stable? What's the total cost (license + integration + maintenance)?

5. Crisis Management

Incident response, security breaches, major outages, data loss.

Your role in a crisis: Ensure the right people are on it, communication is flowing, and the business is informed. Post-crisis: blameless retrospective within 48 hours.

Workflows

Tech Debt Assessment Workflow

Step 1 — Run the analyzer

python scripts/tech_debt_analyzer.py --output report.json

Step 2 — Interpret results The analyzer produces a severity-scored inventory. Review each item against:

• Severity (P0–P3): how much is it blocking velocity or creating risk?
• Cost-to-fix: engineering days estimated to remediate
• Blast radius: how many systems / teams are affected?

Step 3 — Build a prioritized remediation plan Sort by: (Severity × Blast Radius) / Cost-to-fix — highest score = fix first. Group items into: (a) immediate sprint, (b) next quarter, (c) tracked backlog.

Step 4 — Validate before presenting to stakeholders

• Every P0/P1 item has an owner and a target date
• Cost-to-fix estimates reviewed with the relevant tech lead
• Debt ratio calculated: maintenance work / total engineering capacity (target: < 25%)
• Remediation plan fits within capacity (don't promise 40 points of debt reduction in a 2-week sprint)

Example output — Tech Debt Inventory:

Item                  | Severity | Cost-to-Fix | Blast Radius | Priority Score
----------------------|----------|-------------|--------------|---------------
Auth service (v1 API) | P1       | 8 days      | 6 services   | HIGH
Unindexed DB queries  | P2       | 3 days      | 2 services   | MEDIUM
Legacy deploy scripts | P3       | 5 days      | 1 service    | LOW

ADR Creation Workflow

Step 1 — Identify the decision Trigger an ADR when: the decision affects more than one team, is hard to reverse, or has cost/risk implications > 1 sprint of effort.

Step 2 — Draft the ADR Use the template from references/architecture_decision_records.md:

Title: [Short noun phrase]
Status: Proposed | Accepted | Superseded
Context: What is the problem? What constraints exist?
Options Considered:
  - Option A: [description] — TCO: $X | Risk: Low/Med/High
  - Option B: [description] — TCO: $X | Risk: Low/Med/High
Decision: [Chosen option and rationale]
Consequences: [What becomes easier? What becomes harder?]

Step 3 — Validation checkpoint (before finalizing)

• All options include a 3-year TCO estimate
• At least one "do nothing" or "buy" alternative is documented
• Affected team leads have reviewed and signed off
• Consequences section addresses reversibility and migration path
• ADR is committed to the repository (not left in a doc or Slack thread)

Step 4 — Communicate and close Share the accepted ADR in the engineering all-hands or architecture sync. Link it from the relevant service's README.

Build vs Buy Analysis Workflow

Step 1 — Define requirements (functional + non-functional) Step 2 — Identify candidate vendors or internal build scope Step 3 — Score each option:

Criterion              | Weight | Build Score | Vendor A Score | Vendor B Score
-----------------------|--------|-------------|----------------|---------------
Solves core problem    | 30%    | 9           | 8              | 7
Migration risk         | 20%    | 2 (low risk)| 7              | 6
3-year TCO             | 25%    | $X          | $Y             | $Z
Vendor stability       | 15%    | N/A         | 8              | 5
Integration effort     | 10%    | 3           | 7              | 8

Step 4 — Default rule: Buy unless it is core IP or no vendor meets ≥ 70% of requirements. Step 5 — Document the decision as an ADR (see ADR workflow above).

Key Questions a CTO Asks

• "What's our biggest technical risk right now — not the most annoying, the most dangerous?"
• "If we 10x our traffic tomorrow, what breaks first?"
• "How much of our engineering time goes to maintenance vs new features?"
• "What would a new engineer say about our codebase after their first week?"
• "Which technical decision from 2 years ago is hurting us most today?"
• "Are we building this because it's the right solution, or because it's the interesting one?"
• "What's our bus factor on critical systems?"