Prepare your team for the AI shift

AI works when your team is ready for it. We don't. We work with your leadership to make sure your team knows how to use AI before, during, and long after rollout.

FLINK
Akademie für Lernpädagogik
HEM
Circus Group

Prepare your team for the AI shift

AI works when your team is ready for it. We don't. We work with your leadership to make sure your team knows how to use AI before, during, and long after rollout.

FLINK
Akademie für Lernpädagogik
HEM
Circus Group

Prepare your team for the AI shift

AI works when your team is ready for it. We don't. We work with your leadership to make sure your team knows how to use AI before, during, and long after rollout.

FLINK
Akademie für Lernpädagogik
HEM
Circus Group

Most teams buy the tools, then wonder why no one’s using them.

Properly rolled out, adoption rates jump to [X]%, over the industry average of [X]%.

We recommend modern AI toolkits.

Choosing the right AI tools matters as much as how you roll them out. We stay current on the platforms and frameworks worth adopting, and only recommend what will genuinely fit your team.

defaultshop.ai
claude — fish — 100×30

Our technology stack

hubblrv0.4.2·stack categories

languages

·
name
used in
●TypeScriptfrontend, edge runtimes, agent SDKs
●PythonFastAPI services, data pipelines, agents
●Gohigh-throughput services, infra glue
●SQLPostgres-first · Atlas migrations · dbt
●BashCI, deploys, day-to-day glue

ai

·
name
used in
●Claude CodeAI pair-programmer in the terminal
●MCP serversexpose internal tools to agents
●Gemini SDKlong-context multimodal, planning
●MastraTypeScript agent SDK
●Vercel AI SDKstreaming + tool-use on the edge
●Vercel Chat SDKproduction chat scaffold · resumable streams
●AI Gatewaymodel routing, observability, budgets
●v0AI-built UI scaffolds · ship to Vercel
●Langfuseproduction tracing + evals
●pgvectorRAG straight in Postgres

agentic commerce

·
name
used in
●Agent Commerce Protocolopen spec for agent-to-merchant transactions
●Stripe Agent Toolkitagent-issued payments + checkout APIs
●Browserbaseheadless browser-as-a-service for agents
●StagehandPlaywright + LLM, structured browser control
●Computer UseAnthropic desktop control · agentic shopping flows
●LangGraphagent state machines · tool routing
●MCP serversexpose product catalog + checkout to agents

backend

·
name
used in
●FastAPIPython · async · Pydantic-typed
●SQLAlchemy 2async ORM · asyncpg
●Pydanticschemas + validation everywhere
●Postgres 16primary store · jsonb · pgvector
●Atlasdeclarative schema · HCL migrations
●Connect RPCHTTP/JSON · gRPC · gRPC-Web from one .proto
●Rediscache · queues · pubsub

frontend

·
name
used in
●React + Vitefast dev loop, modern build
●Tailwind CSSdesign system in classes
●Radix UIaccessible primitives
●shadcn/uicopy-pastable components
●Framer Motioninteraction + transitions
●React Nativeshared codebase across iOS/Android

devops

·
name
used in
●Turborepomonorepo · cached pipelines
●pnpm + uvfast install for JS + Python
●Docker Composelocal stack in one command
●AWSprimary cloud · prod workloads
●Google Clouddata + ML stack
●Terraforminfra-as-code
●Vercelmarketing + edge functions

quality

·
name
used in
●TypeScriptstrict mode, every file
●Ruff + MypyPython lint + types
●BufProtobuf lint + breaking-change checks
●Pytest · Vitestunit + integration
●Playwrightbrowser e2e + smoke tests

commerce

·
name
used in
●Shopifyheadless storefronts
●commercetoolsenterprise composable
●Contentfulheadless CMS
●emdash CMSgit-native headless CMS · TS-first
●Algoliasearch + recs

product

·
name
used in
●Linearissues, cycles
●Notiondocs + roadmaps
●Figmadesign + prototypes
●Dovetailuser research
← / → switch category·scroll

We recommend modern AI toolkits.

Choosing the right AI tools matters as much as how you roll them out. We stay current on the platforms and frameworks worth adopting, and only recommend what will genuinely fit your team.

defaultshop.ai
claude — fish — 100×30

Our technology stack

hubblrv0.4.2·stack categories

languages

·
name
used in
●TypeScriptfrontend, edge runtimes, agent SDKs
●PythonFastAPI services, data pipelines, agents
●Gohigh-throughput services, infra glue
●SQLPostgres-first · Atlas migrations · dbt
●BashCI, deploys, day-to-day glue

ai

·
name
used in
●Claude CodeAI pair-programmer in the terminal
●MCP serversexpose internal tools to agents
●Gemini SDKlong-context multimodal, planning
●MastraTypeScript agent SDK
●Vercel AI SDKstreaming + tool-use on the edge
●Vercel Chat SDKproduction chat scaffold · resumable streams
●AI Gatewaymodel routing, observability, budgets
●v0AI-built UI scaffolds · ship to Vercel
●Langfuseproduction tracing + evals
●pgvectorRAG straight in Postgres

agentic commerce

·
name
used in
●Agent Commerce Protocolopen spec for agent-to-merchant transactions
●Stripe Agent Toolkitagent-issued payments + checkout APIs
●Browserbaseheadless browser-as-a-service for agents
●StagehandPlaywright + LLM, structured browser control
●Computer UseAnthropic desktop control · agentic shopping flows
●LangGraphagent state machines · tool routing
●MCP serversexpose product catalog + checkout to agents

backend

·
name
used in
●FastAPIPython · async · Pydantic-typed
●SQLAlchemy 2async ORM · asyncpg
●Pydanticschemas + validation everywhere
●Postgres 16primary store · jsonb · pgvector
●Atlasdeclarative schema · HCL migrations
●Connect RPCHTTP/JSON · gRPC · gRPC-Web from one .proto
●Rediscache · queues · pubsub

frontend

·
name
used in
●React + Vitefast dev loop, modern build
●Tailwind CSSdesign system in classes
●Radix UIaccessible primitives
●shadcn/uicopy-pastable components
●Framer Motioninteraction + transitions
●React Nativeshared codebase across iOS/Android

devops

·
name
used in
●Turborepomonorepo · cached pipelines
●pnpm + uvfast install for JS + Python
●Docker Composelocal stack in one command
●AWSprimary cloud · prod workloads
●Google Clouddata + ML stack
●Terraforminfra-as-code
●Vercelmarketing + edge functions

quality

·
name
used in
●TypeScriptstrict mode, every file
●Ruff + MypyPython lint + types
●BufProtobuf lint + breaking-change checks
●Pytest · Vitestunit + integration
●Playwrightbrowser e2e + smoke tests

commerce

·
name
used in
●Shopifyheadless storefronts
●commercetoolsenterprise composable
●Contentfulheadless CMS
●emdash CMSgit-native headless CMS · TS-first
●Algoliasearch + recs

product

·
name
used in
●Linearissues, cycles
●Notiondocs + roadmaps
●Figmadesign + prototypes
●Dovetailuser research
← / → switch category·scroll

We recommend modern AI toolkits.

Choosing the right AI tools matters as much as how you roll them out. We stay current on the platforms and frameworks worth adopting, and only recommend what will genuinely fit your team.

defaultshop.ai
claude — fish — 100×30

Our technology stack

hubblrv0.4.2·stack categories

languages

·
name
used in
●TypeScriptfrontend, edge runtimes, agent SDKs
●PythonFastAPI services, data pipelines, agents
●Gohigh-throughput services, infra glue
●SQLPostgres-first · Atlas migrations · dbt
●BashCI, deploys, day-to-day glue

ai

·
name
used in
●Claude CodeAI pair-programmer in the terminal
●MCP serversexpose internal tools to agents
●Gemini SDKlong-context multimodal, planning
●MastraTypeScript agent SDK
●Vercel AI SDKstreaming + tool-use on the edge
●Vercel Chat SDKproduction chat scaffold · resumable streams
●AI Gatewaymodel routing, observability, budgets
●v0AI-built UI scaffolds · ship to Vercel
●Langfuseproduction tracing + evals
●pgvectorRAG straight in Postgres

agentic commerce

·
name
used in
●Agent Commerce Protocolopen spec for agent-to-merchant transactions
●Stripe Agent Toolkitagent-issued payments + checkout APIs
●Browserbaseheadless browser-as-a-service for agents
●StagehandPlaywright + LLM, structured browser control
●Computer UseAnthropic desktop control · agentic shopping flows
●LangGraphagent state machines · tool routing
●MCP serversexpose product catalog + checkout to agents

backend

·
name
used in
●FastAPIPython · async · Pydantic-typed
●SQLAlchemy 2async ORM · asyncpg
●Pydanticschemas + validation everywhere
●Postgres 16primary store · jsonb · pgvector
●Atlasdeclarative schema · HCL migrations
●Connect RPCHTTP/JSON · gRPC · gRPC-Web from one .proto
●Rediscache · queues · pubsub

frontend

·
name
used in
●React + Vitefast dev loop, modern build
●Tailwind CSSdesign system in classes
●Radix UIaccessible primitives
●shadcn/uicopy-pastable components
●Framer Motioninteraction + transitions
●React Nativeshared codebase across iOS/Android

devops

·
name
used in
●Turborepomonorepo · cached pipelines
●pnpm + uvfast install for JS + Python
●Docker Composelocal stack in one command
●AWSprimary cloud · prod workloads
●Google Clouddata + ML stack
●Terraforminfra-as-code
●Vercelmarketing + edge functions

quality

·
name
used in
●TypeScriptstrict mode, every file
●Ruff + MypyPython lint + types
●BufProtobuf lint + breaking-change checks
●Pytest · Vitestunit + integration
●Playwrightbrowser e2e + smoke tests

commerce

·
name
used in
●Shopifyheadless storefronts
●commercetoolsenterprise composable
●Contentfulheadless CMS
●emdash CMSgit-native headless CMS · TS-first
●Algoliasearch + recs

product

·
name
used in
●Linearissues, cycles
●Notiondocs + roadmaps
●Figmadesign + prototypes
●Dovetailuser research
← / → switch category·scroll

We stay until it actually works.

We're hands-on and opinionated. That means fewer handoffs, faster decisions, and a team that's actually in the room when it matters.

We stay until it actually works.

We're hands-on and opinionated. That means fewer handoffs, faster decisions, and a team that's actually in the room when it matters.

We stay until it actually works.

We're hands-on and opinionated. That means fewer handoffs, faster decisions, and a team that's actually in the room when it matters.

Testimonials

Case studies

Invested in Business Goals

To build a successful product organisation, it is essential senior leadership needs to find clarity on the business strategy and tools to communicate that to the teams.

Reduce Complexity to ship faster

The monorepo is back and we're here for it. Shipping fast means cutting technical setup complexity and human complexity, controlling what your team (including your agents) can consume and own.

Rich in experience, agnostic in language.

The best people you can have are those eager to learn, eager to unlearn, and who've seen software products break at scale. With agentic engineering, the right instincts matter more than which language you know.

Case studies

Invested in Business Goals

To build a successful product organisation, it is essential senior leadership needs to find clarity on the business strategy and tools to communicate that to the teams.

Reduce Complexity to ship faster

The monorepo is back and we're here for it. Shipping fast means cutting technical setup complexity and human complexity, controlling what your team (including your agents) can consume and own.

Rich in experience, agnostic in language.

The best people you can have are those eager to learn, eager to unlearn, and who've seen software products break at scale. With agentic engineering, the right instincts matter more than which language you know.

Case studies

Invested in Business Goals

To build a successful product organisation, it is essential senior leadership needs to find clarity on the business strategy and tools to communicate that to the teams.

Reduce Complexity to ship faster

The monorepo is back and we're here for it. Shipping fast means cutting technical setup complexity and human complexity, controlling what your team (including your agents) can consume and own.

Rich in experience, agnostic in language.

The best people you can have are those eager to learn, eager to unlearn, and who've seen software products break at scale. With agentic engineering, the right instincts matter more than which language you know.

Questions you might have

01

We're a small team, is this overkill for us?

Actually the opposite. Smaller teams adopt faster when it's done right, there are fewer people to bring along and decisions get made quickly.

02

We already use some AI tools informally, do we still need this?

Informal use is a starting point, not adoption. If different people are using different tools in different ways with no shared process, you're not getting the compounding benefit.

03

What if our team is resistant?

That's normal and we plan for it. Resistance usually comes from not understanding why the change matters, our approach is built around making that case clearly before anything gets rolled out.

04

Do you recommend specific tools or are you tool agnostic?

Tool agnostic. We recommend what's right for your team and your workflows.

Questions you might have

01

We're a small team, is this overkill for us?

Actually the opposite. Smaller teams adopt faster when it's done right, there are fewer people to bring along and decisions get made quickly.

02

We already use some AI tools informally, do we still need this?

Informal use is a starting point, not adoption. If different people are using different tools in different ways with no shared process, you're not getting the compounding benefit.

03

What if our team is resistant?

That's normal and we plan for it. Resistance usually comes from not understanding why the change matters, our approach is built around making that case clearly before anything gets rolled out.

04

Do you recommend specific tools or are you tool agnostic?

Tool agnostic. We recommend what's right for your team and your workflows.

Questions you might have

We're a small team, is this overkill for us?

Actually the opposite. Smaller teams adopt faster when it's done right, there are fewer people to bring along and decisions get made quickly.

We already use some AI tools informally, do we still need this?
What if our team is resistant?
Do you recommend specific tools or are you tool agnostic?

Final CTA
Related services

I care about software that runs in production, not software that looks good in a demo.

With AI that matters more than ever. The interesting work starts after the prototype: wiring agents into real processes, owning the edge cases, and making sure it still works next month.

We stay until it is in your hands and your team can run it without us.

Xaver Ebner

,

Managing Director at HUBBLR Technologies

I care about software that runs in production, not software that looks good in a demo.

With AI that matters more than ever. The interesting work starts after the prototype: wiring agents into real processes, owning the edge cases, and making sure it still works next month.

We stay until it is in your hands and your team can run it without us.

Xaver Ebner

,

Managing Director at HUBBLR Technologies

I care about software that runs in production, not software that looks good in a demo.

With AI that matters more than ever. The interesting work starts after the prototype: wiring agents into real processes, owning the edge cases, and making sure it still works next month.

We stay until it is in your hands and your team can run it without us.

Xaver Ebner

,

Managing Director at HUBBLR Technologies