day10 / mode.build
/01
The Problem
Why existing solutions fail
01
Legacy dev shops are structurally stuck
Their business models depend on scaling headcount
Clients expect more with fewer people
02
In-house teams face a different problem
Seniority is no longer defined by years of experience or mastery of a single tech stack
While some teams have embraced AI, without a unified system and shared protocol, they’re still nowhere near the level of efficiency AI actually makes possible
The result is a widening performance gap that compounds over time
/02
The Solution
Redefined Team Structure
Traditional teams fragment across many roles, losing context at each handoff. AI-native teams consolidate into core functions operating through a unified AI agent orchestration system that maintains context across the entire workflow.
/03
Impact
Day10 Method: Build faster,
built better
By wiring best-in-class tools through a single system, we eliminate repetitive work and maintain end-to-end context from requirement to production.
Two AI-native engineers inside the right system outperform a legacy team of ten — not because they work harder, but because they're not doing work that shouldn't require humans in the first place.
/04
Application Architecture
AI-driven additions
AI Monitoring & Evaluation
Observability for AI behavior: drift, hallucinations, latency, cost, and output quality.
Agent Orchestration
Coordination layer for multi-step AI workflows: planning, tool calling, validation, and guardrails.
Retrieval & Vector Search
Embeddings, vector databases, and RAG/S-RAG pipelines that transform data into context for AI models.
Core AI Models
Foundation models (GPT, Claude, Gemini) providing reasoning, generation, and decision-making.
tech stack
Frontend
User interface: web, mobile, chat interfaces, and streaming components.
Backend
Business logic, authentication, feature endpoints, integrations.
Databases
Relational and NoSQL storage, caching layers, and search indexes.
Cloud Infrastructure
Compute, networking, CI/CD, containerization, security, GPU workloads.