Devlyn AI · Engineering pods
Pick the stack you run, the vertical you operate in, or the city your team works from.
Most engineering engagements stall on the wrong question. Marketplace? Agency? FTE? The better question is what shape of work the next two quarters need.
In one sentence
Devlyn AI deploys AI-augmented engineering pods that own your roadmap, ship at 4x historical pace, and absorb the architecture, security, and compliance overhead your in-house team can no longer carry alone.
One retainer. One PM line. 150+ engineers across 25 stacks, 15 verticals, and 49 metros. 3-day free trial. 14-day replacement guarantee. From $2,500/month or $15/hour.
Where pods land today
Six engagements that show the breadth of the practice. Each page breaks down the stack, the vertical's compliance posture, and the metro's hiring-climate context.
Laravel · Fintech · London
Laravel for Fintech in London
The most common 2026 fintech engineering trap is shipping a feature that depends on a partner-bank integration that has not been contractually signed or technically certified, creating a rollback scenario that wastes months of engineering effort. Laravel pods compress the work — laravel pods typically ship multi-tenant saas platforms with per-tenant database isolation or row-level scoping, marketplace backends with escrow and split-payment flows through cashier and stripe connect, billing engines handling usage-based and seat-based pricing models, admin dashboards via filament or nova with complex reporting queries, and api-first products serving react or next. On the GMT / BST calendar, london fte hiring runs 3–5 months for senior fintech and ai roles, with offers regularly contested by us tech giants opening uk offices.
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Python · AI Startup · San Francisco
Python for AI Startup in San Francisco
The most common 2026 AI-startup engineering trap is shipping LLM-powered features without deterministic-test wrapping of stochastic systems, creating quality regressions that are invisible until users report hallucinations or incorrect outputs at scale. Python pods compress the work — python pods typically ship data pipelines with etl orchestration through dagster or airflow, ml and ai inference services with model-serving endpoints behind fastapi, async api backends using fastapi with automatic openapi documentation and dependency injection for authentication and database sessions, batch-processing systems for report generation and data transformation with polars or pandas, real-time streaming consumers on kafka or redis streams, and platform-engineering tooling including cli utilities and infrastructure automation scripts. On the Pacific (PT) calendar, fte hiring in sf has slowed structurally since 2024 layoffs but compensation expectations have not.
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React · B2B SaaS · New York
React for B2B SaaS in New York
The most common 2026 B2B SaaS engineering trap is integration-first roadmaps that fragment the codebase into per-customer hacks and one-off webhook handlers, creating a maintenance debt spiral that slows all future feature work. React pods compress the work — react pods typically ship product uis with complex multi-step workflows and conditional rendering pipelines, admin dashboards with real-time data tables and chart visualisations, marketing sites and landing pages through next. On the Eastern (ET) calendar, fte-only paths to scale engineering in nyc routinely run 2–3 quarters behind the roadmap.
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TypeScript · Healthtech · Boston
TypeScript for Healthtech in Boston
The most common 2026 healthtech engineering trap is shipping a clinical feature that has not been reviewed against HIPAA BAA requirements or FDA SaMD classification boundaries, creating regulatory exposure that can halt the entire product. TypeScript pods compress the work — typescript pods typically ship full-stack javascript projects across next. On the Eastern (ET) calendar, boston fte pipelines run 4–6 months for senior backend roles.
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Go · Logistics · Amsterdam
Go for Logistics in Amsterdam
The most common 2026 logistics engineering trap is shipping a routing-optimisation feature that fails under carrier-API outage or peak-season volume surge, creating delivery-promise violations at the worst possible time. Go pods compress the work — go pods typically ship high-throughput api services handling tens of thousands of requests per second, grpc backends with protocol buffer contracts for inter-service communication, infrastructure tooling including custom operators, clis, and platform-engineering utilities, network proxies and load balancers with connection-pool management, and event-driven microservices consuming from kafka, nats, or redis streams with goroutine-based concurrent processing. On the CET / CEST calendar, amsterdam fte pipelines run 2–4 months for senior backend roles.
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Node.js · Marketplace · Berlin
Node.js for Marketplace in Berlin
The most common 2026 marketplace engineering trap is building trust-and-safety features reactively after a fraud incident or policy violation rather than proactively designing detection and enforcement systems before scale arrives. Node.js pods compress the work — node. On the CET / CEST calendar, berlin fte pipelines run 2–4 months for senior backend roles.
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How a Devlyn engagement starts
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1 · Discovery
Book a 30-minute discovery call. We scope pod composition against your roadmap and timeline.
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2 · Try free
Three days free with a senior engineer. Real PRs against your roadmap, before you hire.
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3 · Deploy
Engineer in your Slack, tracker, and repos within 24 hours of greenlight.
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4 · Replace if needed
Not a fit within 14 days? Replaced at no charge. Pace stays. Risk goes.
Real outcomes
Calenso · Switzerland
4x productivity
5,000+ integrations on the platform after AI-augmented engineering replaced manual workflows.
Creator.ai
6 weeks to 1 week
6x faster delivery, 2x output per engineer, 50% leaner team.
Klaviss · USA
$4,800/mo pod
Two engineers + PM + shared DevOps. Real-estate platform overhaul shipped in 8 weeks.
Haxi.ai · Middle East
AI engagement at scale
Real-time, context-aware AI conversations across platforms. Spec to production by one pod.
Browse by stack
The engineer-side of the question. Each stack carries its own pod composition, AI-augmented angle, and ecosystem depth.
All 50 stacks
- .NET →
- AWS →
- Airflow →
- Android →
- Angular →
- C++ →
- Databricks →
- Django →
- Docker →
- Elixir →
- Flutter →
- GraphQL →
- Haskell →
- Kafka →
- Kotlin →
- Kubernetes →
- MATLAB →
- MongoDB →
- PHP →
- PostgreSQL →
- R →
- React Native →
- Redis →
- Ruby on Rails →
- Scala →
- Shopify →
- Snowflake →
- Solidity →
- Spring Boot →
- Supabase →
- Svelte →
- Swift →
- Tableau →
- Terraform →
- Unity →
- Unreal →
- Vue →
- WordPress →
- dbt →
- iOS →
Browse by vertical
The compliance-and-architecture side. Each vertical carries its own regulatory posture, named risks, and key metrics the pod designs around.
All 30 verticals
Browse by city
The calendar side. Each city has its own talent pool, hiring climate, and time-zone alignment with the pod.
- New York →
- San Francisco →
- London →
- Berlin →
- Austin →
- Boston →
- Amsterdam →
- Toronto →
- Dubai →
- Paris →
- Seattle →
- Chicago →
All 144 cities
- Aarhus →
- Abu Dhabi →
- Amman →
- Ann Arbor →
- Athens →
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- Baltimore →
- Bangkok →
- Barcelona →
- Belfast →
- Belgrade →
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- Bristol →
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- Cairo →
- Calgary →
- Cape Town →
- Charleston →
- Charlotte →
- Cincinnati →
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- Cluj-Napoca →
- Cologne →
- Columbus →
- Copenhagen →
- Cordoba →
- Curitiba →
- Dallas →
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- Detroit →
- Dublin →
- Edinburgh →
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- Geneva →
- Glasgow →
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- Guadalajara →
- Halifax →
- Hamburg →
- Hanoi →
- Helsinki →
- Ho Chi Minh City →
- Houston →
- Indianapolis →
- Jakarta →
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- Krakow →
- Kuala Lumpur →
- Lagos →
- Las Vegas →
- Leeds →
- Leipzig →
- Lima →
- Lisbon →
- Los Angeles →
- Louisville →
- Lyon →
- Madison →
- Madrid →
- Malmo →
- Manchester →
- Manila →
- Medellin →
- Melbourne →
- Mexico City →
- Miami →
- Milan →
- Milwaukee →
- Minneapolis →
- Monterrey →
- Montreal →
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- Nairobi →
- Nashville →
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- Orlando →
- Osaka →
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- Philadelphia →
- Phoenix →
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- Portland →
- Porto →
- Prague →
- Quebec City →
- Raleigh →
- Richmond →
- Riga →
- Rio de Janeiro →
- Riyadh →
- Rome →
- Rotterdam →
- Salt Lake City →
- San Diego →
- San Jose (CR) →
- Santiago →
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- Sofia →
- St. Louis →
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- Valencia →
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- Washington DC →
- Waterloo →
- Wroclaw →
- Zurich →
Common questions
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How fast can a Devlyn pod start?
Within 24 hours of greenlight after a 3-day free trial. The trial runs against real work from your roadmap. Total elapsed time from discovery call to engineer in your repo is typically 5 to 7 days.
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What does a pod cost?
Engagements start at $15/hour, with monthly retainers from $2,500 for a single embedded engineer. Pods scale to multi-engineer teams with shared DevOps, QA, and PM under one retainer.
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What stacks does Devlyn cover?
Laravel, React, Node.js, Python, AI/ML, Go, Rust, Java, Kotlin, Swift, Flutter, React Native, .NET, Spring Boot, Angular, Svelte, AWS, Kubernetes, and the cloud-native tooling around them.
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What happens if the engineer is not the right fit?
Try free for 3 days before hiring. Replacement is free within 14 calendar days. The replacement ramps in 24 hours from a 150+ engineer practice.
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How is this different from a marketplace like Toptal or Upwork?
Marketplaces match individual contractors. Devlyn deploys coherent pods that own architecture, security, DevOps, and QA under one retainer. The pod ships at 4x historical pace through AI-augmented workflows, not just individual tool adoption.
Skip the browse
If your roadmap is shaped and the next move is a conversation rather than more reading, book a 30-minute discovery call. No contracts. No commitment. Or run the Pod ROI Calculator against your current vendor's burn first.