#Mobile Development

Articles about Mobile Development — exploring patterns, best practices, and real-world implementations in production systems.

2 posts tagged with mobile development. ← All posts

#A2A (14)#ADK (8)#AG-UI (6)#AI (9)#AI Agents (303)#AI Architecture (10)#AI Cost (10)#AI Cost Optimization (8)#AI Engineering (160)#AI Governance (28)#AI Red Teaming (9)#AI Research (9)#AI Safety (6)#AI Security (21)#AI in Production (12)#AML (3)#API Design (10)#API Security (8)#APIs (47)#AWS (17)#Accounting (9)#Agent Skills (3)#Agentic AI (24)#Agentic Commerce (12)#Agentic RAG (8)#Agents (4)#Amazon Bedrock (8)#Architecture (36)#Audit (3)#Authentication (10)#Authorization (3)#Automation (6)#Azure (11)#Azure AI Foundry (9)#Backend Engineering (267)#BigQuery (6)#CI/CD (8)#Capital Markets (14)#Card Payments (12)#Cards (13)#Career (7)#Checkpointing (4)#Claude Code (8)#Cloud (3)#Cloud Architecture (3)#Code Review (8)#Collaboration (4)#Communication (4)#Compliance (51)#Computer Networking (8)#Concurrency (25)#Consulting (3)#Context Engineering (10)#Cost Optimisation (5)#Credit (14)#Credit Risk (14)#CrewAI (8)#Crypto (12)#Cryptocurrency (12)#Custody (9)#DSPy (8)#Data (4)#Data Engineering (4)#Data Structures (8)#Databases (33)#Deployment (3)#DevOps (9)#DevSecOps (11)#Developer Experience (5)#Distributed Systems (88)#Documentation (3)#Edge AI (8)#Embeddings (14)#Engineering (7)#Engineering Culture (3)#Engineering Practices (16)#Evaluation (44)#Event-Driven Architecture (8)#FREE-AI (8)#FX (5)#FinOps (23)#FinTech (6)#Financial AI (14)#Financial Systems (129)#Fine-Tuning (11)#Fintech (131)#Flutter (8)#Foreign Exchange (5)#Forward Deployed Engineer (8)#Forward Deployed Engineering (8)#Fraud (10)#Function Tools (5)#GCP (5)#Gemma (4)#Go (220)#Google ADK (36)#Governance (55)#Granite (6)#GraphQL (3)#Guardrails (24)#HIPAA (3)#HTTP (3)#Harness Engineering (8)#Hugging Face (8)#Human-in-the-Loop (8)#IBM watsonx (8)#Identity (11)#Integration (3)#Interfaces (3)#KYC (11)#KYC and AML (12)#Kafka (10)#Kubernetes (9)#LLM (5)#LLM Inference (8)#LLMs (110)#LangChain (8)#LangGraph (11)#Ledger (12)#Lending (14)#LlamaIndex (8)#MCP (22)#MLOps (30)#Machine Learning (13)#Markets (4)#Memory (13)#Memory Management (4)#Microservices (3)#Microsoft Agent Framework (150)#Middleware (6)#Migration (9)#Mobile Development (2)#Monitoring (3)#Multi-Agent (10)#Multi-Agent AI (14)#Multi-Agent Systems (70)#Multimodal (3)#NIM (5)#NVIDIA (8)#OAuth (3)#OWASP (7)#Observability (43)#On-Device AI (8)#Open Source (6)#OpenTelemetry (5)#Opinion (6)#Orchestration (10)#Payment Rails (16)#Payments (54)#Performance (29)#Platform Engineering (9)#Privacy (4)#Privacy Engineering (3)#Product (4)#Production (6)#Programming (10)#Programming Languages (16)#Prompt Engineering (64)#Prompt Injection (6)#Protocols (9)#Providers (4)#Pydantic AI (8)#Python (142)#Quality (3)#RAG (58)#RBI (3)#REST (5)#Rails (16)#Reconciliation (3)#RegTech (8)#Regulation (9)#Reliability (45)#Resilience (3)#Responsible AI (5)#Retrieval (3)#Risk (13)#Rust (16)#SRE (20)#Scalability (3)#Security (80)#Self-Evolving Agents (16)#Sessions (3)#Settlement (9)#Software Architecture (35)#Software Engineering (138)#Spanner (4)#Strands (8)#Streaming (25)#Structured Output (4)#System Design (32)#Systems Programming (16)#Testing (34)#Tool Use (21)#Tools (3)#Trading (8)#Treasury (6)#Type System (3)#Type Systems (3)#Vector Databases (21)#Vector Search (11)#Web Development (6)#Workflows (14)#gRPC (5)#smolagents (8)
Pratik Dhanave · ·7 min read

Shipping an Edge-AI App

The demo runs on your phone; now you have to get it running on thousands of phones you'll never touch. Shipping on-device AI has its own hard problems — a model file too big to bundle, first-run downloads, a fleet of wildly different devices, and updates you can't push instantly — and handling them is what separates a hackathon project from a product.

The demo runs on your phone; now you have to get it running on thousands of phones you'll never touch — a model file too big to bundle, first-run downloads, a fleet of different devices, and updates you can't push instantly.

#On-Device AI#Edge AI#Flutter#Mobile Development
Pratik Dhanave · ·6 min read

The Constraints of the Edge

A phone is not a small server — it's a fundamentally different environment with four hard limits a data center never imposes: a tight memory budget, modest and heterogeneous compute, a battery that your model drains, and a thermal ceiling that throttles you when you push it. Every on-device AI decision is a negotiation with these four.

A phone is not a small server — it's a different environment with four hard limits a data center never imposes: a tight memory budget, modest heterogeneous compute, a battery your model drains, and a thermal ceiling that throttles you.

#On-Device AI#Edge AI#Performance#Mobile Development#Flutter

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.