Practice v of v · For CTOs and VPs of Engineering
Retire the technical debt. Keep the system running.
Full rewrites freeze the roadmap, overrun the budget and rarely reach parity. We modernize legacy systems incrementally with the strangler-fig pattern, prove every step with tests, and add AI at the seams.
A predictable monthly retainerNo big-bang risk, no feature freeze, no hourly surprises.
01 The status quo
Legacy is not old code. It is code you are afraid to change.
The cost of an aging system rarely shows up on a balance sheet. It shows up in release weekends, in knowledge that walked out of the door, and in AI projects that cannot start.
Every release is a gamble
Deploys take a weekend and a prayer. The team spends more time firefighting regressions than shipping features.
The knowledge left with the people
The original authors are gone. Critical logic lives in undocumented code nobody wants to touch.
AI is stuck at the door
You want to add AI, but the data is trapped in a schema and an architecture that cannot support it.
02 The approach
Modernize without the rewrite.
We treat modernization as a controlled, reversible migration, not a leap of faith. The old system keeps running while the new one grows around it.
Code and architecture audit
What is load-bearing, what is dead weight, where the risk hotspots are, and the shortest safe path to value.
- Codebase map
- Risk hotspots
- Sequenced plan
A written diagnostic
Strangler fig, not big bang
We wrap the legacy system and peel off capabilities one at a time behind a routing layer. No 18-month rewrite, no feature freeze.
- Routing seam
- Incremental extraction
- Modules and services
Each capability live in production
Characterize before we change
Before touching anything, we pin down current behaviour with characterization tests, so every migration step is provably equivalent and never a regression.
- Characterization tests
- Test harness
- Equivalence checks
Old and new agree, test by test
Data migration with lineage and rollback
Data moves with the capability that owns it, traced from source to destination, with a way back at every step.
- Lineage
- Rollback
- Parallel run
Reconciled before cutover
AI added at the seams
Once a capability is behind a clean interface, we add AI there: retrieval, classification, agents. No re-architecting of the whole platform to do it.
- Retrieval
- Classification
- Agents under a gate
Measured against the old path
Reading Fig. 1
Traffic passes a routing seam. Each capability moves to the modern stack only after its behaviour is pinned by tests, and the legacy path is retired once the new one is proven in production. The share of traffic moves a slice at a time, never all at once.
03 How it works
Four steps, shipped continuously.
Value arrives every sprint, not at the end of a rewrite. Each step is shipped and verified in production before the next one starts.
Engagement path
Diagnostic
FirstA technical audit maps the codebase, the risk hotspots and the shortest safe path to value.
Seam and scaffold
Per capabilityWe introduce the routing seam and a characterization test harness around the target capability.
Incremental cutover
ContinuousCapabilities move to the modern stack one at a time, each shipped and verified in production.
AI and operate
OngoingWith clean interfaces in place, we layer in AI and keep operating the system on retainer.
Engagement
A predictable retainer, not an open-ended project.
A senior engineering team on a fixed monthly retainer, with architecture, migration and AI execution included. No hourly surprises, no scope roulette. Scale the engagement up or down as the modernization progresses.
04 · Case study, healthcare
Paper records replaced, hospital systems kept.
An oncology department captured patient and trial data on paper. Algobain built an electronic data capture system that works with the hospital systems already in place rather than replacing them.
All case studies
The brief
Manual, paper-based patient data collection that was error-prone and slow, no standard for treatment data across sites, and strict requirements for privacy and audit.
What we built
Electronic case report forms, treatment protocol tracking, adverse-event reporting and multi-site trial tools, with automated validation and an audit trail on every change.
How it meets what exists
FHIR APIs and HL7 messaging into the hospital EHR, lab results and imaging, and CDISC exports for regulatory submissions. The existing systems stayed in service.
Client view, another engagement
“Algobain rebuilt a system we had written off as legacy, and shipped it before our last vendor finished scoping the work.”
05 · Insights
Written for the CTO who has to decide.
Legacy application modernization: the step-by-step guide for CTOs
A practical roadmap for planning a modernization: how to audit, sequence and de-risk the move without freezing the roadmap.
Signs your legacy application is costing you more than you think
Cost and risk · 8 min readHow to modernize a legacy system without stopping the business
Migration · 10 min readThe legacy code audit checklist: what to assess before you rewrite anything
Engineering · 9 min readMonolith to modular: when to refactor and when to rebuild
Architecture · 10 min read06 Questions
What CTOs ask before they start.
- Why not a full rewrite?
- Full rewrites freeze the roadmap, blow the budget and rarely reach parity with the system they replace. An incremental migration delivers value every sprint and can be stopped, slowed or redirected at any point.
- Do we need to freeze features while you work?
- No. The legacy system keeps running and keeps receiving changes while capabilities move across behind the routing seam, one at a time.
- How do you prove nothing broke?
- Before touching a capability we pin its current behaviour with characterization tests. Each migration step has to pass them, so the new path is provably equivalent to the old one before traffic moves.
- How is the work priced?
- On a fixed monthly retainer, with architecture, migration and AI execution included. You can scale the engagement up or down as the modernization progresses. [Confirm how the retainer sits alongside the two-week fixed-fee assessment.]
- When does AI come in?
- Once a capability sits behind a clean interface. That is where retrieval, classification or agents can be added safely, without re-architecting the whole platform. See AI agents and automation.
- Where do we start?
- With a [free 15-minute] technical audit call. We map the risk hotspots and the shortest safe path to a modern, AI-ready stack, then propose the diagnostic in writing.
Related practices
Where the modernized system lands.
See where your technical debt actually lives.
Start with a technical audit. We map the risk hotspots and the shortest safe path to a modern, AI-ready stack.
- 1Within 48 hoursA senior engineer replies. If we are not the right fit, we say so.
- 2NDA, then the audit callWe sign first, then walk the system with the people who know it.
- 3A written diagnostic proposalScope, sequence and the monthly retainer, in writing.