Industry

SaaS

Software that scales with your customers

I partner with SaaS companies to build products that customers love and operations that scale efficiently. From early-stage startups to growth-stage companies, I help solve the technical challenges of building software businesses.

At a glance
Regulations
5 frameworks
KPIs tracked
6 core metrics
Reference stacks
5 patterns
Services
4 engagements
Case studies
1 published
Perspective

How I think about saas

The architecture, the trade-offs, and where I push back on conventional wisdom.

SaaS is the discipline of compounding small decisions into a business that survives its own success. The companies I work with usually hit one of three walls: a multi-tenancy model that breaks at the first enterprise deal, a billing system that can't express the new pricing the CRO just promised, or a frontend that has accumulated five years of accidental complexity. My job is usually to widen the wall before we hit it, or to refactor through it without taking the product down.

The multi-tenancy question is foundational. Pooled, siloed, and bridge models each have legitimate reasons to exist, and the right answer depends on your buyer. SMB self-serve products almost always want pooled tenancy with row-level security; enterprise-only products often need siloed databases per customer for procurement reasons. I've helped teams migrate between models without downtime, and the pattern is always the same: dual-write, backfill, shadow read, cutover, decommission.

Feature velocity is a function of architecture, not effort. Teams that ship daily have invested in deployable units, feature flags, and a test pyramid that actually catches things. Teams that ship monthly are usually paying interest on a monolith that nobody dares to touch. The answer isn't always microservices - most SaaS companies under $50M ARR are better served by a well-modularized monolith with strong CI/CD and a clear path to extraction when a service starts pulling its own weight.

Enterprise readiness is a checklist that turns into a roadmap. SSO via SAML and OIDC, SCIM provisioning, audit logs your customers can export, IP allowlisting, custom domains, BYOK encryption, data residency. I help teams sequence this work against deal pipeline so you're shipping the controls your largest prospect actually needs, not building speculative compliance features. SOC 2 and ISO 27001 follow the same logic - let the buyers pull it forward.

Reliability is the silent feature that kills churn. A 99.9% SLA sounds reasonable until you realize it's nearly nine hours of downtime a year, most of which will land during your customer's quarterly close. I build observability into the platform - distributed tracing, RED metrics, SLO-based alerting - so issues are detected before customers file tickets. Performance optimization on the front end matters too: every 100ms of latency on the dashboard load shows up in retention. See a recent SaaS rebuild or read my SaaS playbooks.

Challenges

What teams struggle with

The recurring problems I see on saas engagements.

  • 1Multi-tenancy architecture decisions
  • 2Feature velocity vs. technical debt
  • 3Scaling from hundreds to millions of users
  • 4Enterprise requirements (SSO, audit logs, compliance)
  • 5Churn reduction through performance and reliability
How I help

Capabilities I bring

Concrete engineering work that resolves the challenges on the left.

  • Multi-tenant architecture design
  • Enterprise feature implementation
  • Performance optimization for user retention
  • API design for integrations
  • Usage-based billing implementation
Metrics

What teams measure

The KPIs leadership obsesses over in this sector. Most tie back to performance and architecture decisions made years before the dashboard was built.

01

Net Revenue Retention (NRR)

The North Star for SaaS health - expansion plus renewals minus churn; >120% is best-in-class.

02

Activation rate

Percentage of signups that hit the aha moment; the single biggest lever on long-term LTV.

03

Time-to-value

Minutes from signup to first meaningful action - a product and infrastructure problem.

04

p95 page load

Tail latency on core dashboards correlates directly with daily active usage.

05

Gross margin

Infrastructure as a share of revenue; healthy SaaS sits at 75-85%.

06

API uptime / SLO attainment

What you actually owe enterprise customers in their MSAs.

Reference stacks

Stacks I see most often

Patterns I reach for first when scoping a saasengagement. I don't pick technologies for novelty - read more about how I choose.

1

Next.js + tRPC or REST + Postgres on Vercel and Neon/Supabase

2

Rails or Django monolith with Sidekiq/Celery, fronted by React, deployed on AWS ECS

3

TypeScript node services, Postgres, Redis, BullMQ, Datadog observability

4

Stripe Billing or Metronome for usage-based pricing, Workos or Auth0 for enterprise auth

5

Clickhouse or Tinybird for product analytics, Segment as the CDP layer

Technologies

Tools of the trade

The platforms and frameworks I lean on for saas work.

References

Primary sources & further reading

Public regulator pages, standards bodies, and vendor docs I rely on for saas work. For my own writing on these topics, see Insights.

Building for SaaS?

Let's discuss your specific challenges and how technology can help you ship safely, sleep well, and keep regulators happy.

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