Engineering Leaders-Specific Decision Intelligence

Architecture decisions are Type 1 — high-stakes, hard to reverse, and expensive to get wrong. Choosing the wrong database, cloud provider, or application framework costs months of migration effort and millions in engineering time. SolveRight gives you the quantified, sensitivity-tested analysis to make these decisions defensible.

155

Decision Frameworks

10

Framework Categories

<6s

Analysis Time

7

Export Formats

Decision Challenges Engineering Leaders Face

Type 1 Decisions With Type 2 Analysis

Irreversible infrastructure choices get evaluated with a two-week proof of concept, a Slack thread debate, and a meeting where the loudest voice wins. The stakes demand rigor, but the process delivers opinion.

Justifying Technical Choices to Non-Technical Stakeholders

The board asks 'why not DynamoDB?' and 'what is the downside risk?' Your PostgreSQL expertise is not the answer they are looking for — they want structured, quantified reasoning they can evaluate without a CS degree.

Engineer Opinions Masquerading as Analysis

Every engineer prefers the technology they used at their last company. Team debates devolve into personal preference battles. There is no objective framework cutting through the noise.

ADRs Written After the Fact

Architecture Decision Records are supposed to document the reasoning process. Instead, they are written retroactively to justify a decision already made in a meeting — losing the actual analysis forever.

How Engineering Leaders Use SolveRight

Database Selection for a High-Traffic SaaS Platform

Situation: Evaluating PostgreSQL, DynamoDB, and CockroachDB for a new SaaS product expecting 10,000 requests per second at launch with 100x growth projected over 3 years. Latency requirements are strict (<50ms p99).

Outcome: CockroachDB scored highest overall (81/100), but sensitivity analysis showed that if cost weight exceeded 30%, PostgreSQL overtook it. FMEA revealed CockroachDB had fewer single points of failure. The exported ADR documented exactly which criteria would need to change to reverse the decision — giving the team a clear trigger for re-evaluation at the 12-month mark.

Build vs Buy for Authentication Infrastructure

Situation: Custom auth system vs Auth0 vs Clerk vs Supabase Auth. Security team wants full control. Product wants fast time-to-market. Finance wants predictable cost at scale.

Outcome: Build-vs-Buy analysis showed custom auth scored 73/100 but carried 4x the operational risk. TCO over 3 years revealed Auth0 cost $180K more than Supabase Auth at projected scale. First Principles stripped out the assumption that 'we need custom auth for compliance' — the actual compliance requirement was satisfied by all SaaS options. Supabase Auth won with 84/100.

Monolith vs Microservices for Platform Rewrite

Situation: The legacy monolith is becoming unmaintainable. Three options: full microservices, modular monolith, or strangler fig pattern for incremental migration. Team of 12 engineers across 3 squads.

Outcome: Modular monolith scored 79/100, beating full microservices (71) and strangler fig (76). The key differentiator: execution feasibility scored modular monolith 25 points higher because it did not require distributed systems expertise the team lacked. Contradiction detection flagged that scalability frameworks favored microservices — surfacing a genuine trade-off rather than hiding it.

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Features Built for Engineering Leaders

ADR-Compatible Export Format

Export your analysis as a structured Architecture Decision Record with context, decision, consequences, and the full scoring methodology. Drop it directly into your ADR repository.

Failure Mode & Effects Analysis (FMEA)

Every option is evaluated for failure modes — what breaks, how badly, and how likely. Technical decisions need failure analysis, not just feature comparison.

Sensitivity Analysis for Weight Robustness

Change any weight and see if the winner flips in under 100 milliseconds. When the CTO asks 'what if scalability matters more than we thought?' — you have the answer instantly.

Total Cost of Ownership Over Time

Infrastructure costs compound. TCO analysis projects licensing, operational, migration, and opportunity costs over 1, 3, and 5-year horizons — not just the sticker price.

Methodology Transparency

Drill into any score to see the extracted data, rubric computation, and reasoning trace. Engineers trust transparency — SolveRight shows its work on every calculation.

Top Frameworks for Engineering Leaders

These frameworks are pre-selected in the Engineering Leaders bundle. All 155 frameworks are available in every analysis.

Engineering Leaders — Frequently Asked Questions

How does SolveRight help with architecture decisions?+
SolveRight evaluates your options across frameworks specifically designed for technical decisions — FMEA for failure modes, TCO for lifecycle costs, sensitivity analysis for weight robustness, and reversibility assessment for migration risk. The result is a scored ranking with full methodology transparency that survives technical review.
Can I export the analysis as an ADR?+
Yes. SolveRight exports in markdown format compatible with Architecture Decision Record repositories. The export includes context, decision rationale, alternatives considered, consequences, and the complete scoring breakdown.
How is this different from writing an RFC?+
RFCs capture the proposal and discussion. SolveRight provides the quantified analysis that feeds into the RFC. Instead of 'I recommend PostgreSQL because...' you include a multi-framework scorecard showing PostgreSQL at 84/100 vs alternatives, with sensitivity analysis proving the decision holds under different weight assumptions.
Does it handle build-vs-buy decisions?+
Build-vs-buy is one of the 155 built-in frameworks. It evaluates control, cost, time-to-market, maintenance burden, and vendor risk. Combined with TCO and risk analysis, you get a complete picture that includes hidden costs most spreadsheet evaluations miss.
Can my engineering team collaborate on the same analysis?+
On Teams and Enterprise tiers, multiple engineers can contribute to the same decision, add criteria, adjust weights based on their expertise, and compare independent scorecards before aligning on a shared recommendation.
How long does an architecture analysis take?+
About 20 minutes — compared to the 2-week proof-of-concept approach. Describe your options, customize the Architecture Decision bundle weights for your constraints, and get scored results in under 6 seconds. The real time investment is thinking through your criteria, not waiting for the tool.
Is the scoring deterministic and reproducible?+
Yes. The scoring engine is fully deterministic — same inputs always produce the same scores. AI is used only for data extraction and narrative generation. The scores themselves are computed by mathematical rubrics with 10 pattern types, making results reproducible and auditable.

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