{"product_id":"ai-agent-design","title":"AI Agent Design","description":"\u003ch2\u003eAI Agent Design \u0026amp; Architecture\u003c\/h2\u003e\u003cp\u003eMost teams can demo an agent in a notebook. Few can ship one that survives production traffic, changing APIs, and real user behavior. Techwall's \u003cstrong\u003eAI Agent Design\u003c\/strong\u003e service closes that gap: we define the architecture, tool boundaries, and operational model before a single line of integration code is written.\u003c\/p\u003e\u003cp\u003eWe work with product leaders, CTOs, and innovation teams who need agents that connect to real systems — CRMs, ERPs, factory MES, device fleets, and custom APIs — not chatbots that stop at the browser.\u003c\/p\u003e\u003ch3\u003eWhat We Design\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eSingle-agent workflows\u003c\/strong\u003e — focused assistants with clear scope, tool access, and escalation paths.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMulti-agent systems\u003c\/strong\u003e — planner\/executor patterns, specialist sub-agents, and supervised handoffs.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTool \u0026amp; MCP layers\u003c\/strong\u003e — structured connectors so models invoke APIs safely and predictably.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eGuardrails\u003c\/strong\u003e — input\/output filters, policy checks, approval gates, and audit trails.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePhysical AI agents\u003c\/strong\u003e — agents that bridge cloud reasoning with edge devices and manufacturing workflows (\u003ca href=\"\/pages\/physical-ai\"\u003ePhysical AI hub\u003c\/a\u003e).\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eOur Design Process\u003c\/h3\u003e\u003col\u003e\n\u003cli\u003e\n\u003cstrong\u003eDiscovery\u003c\/strong\u003e — map stakeholders, data sources, latency requirements, and compliance constraints.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eUse-case framing\u003c\/strong\u003e — define agent roles, success metrics, and what stays human-owned.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eArchitecture draft\u003c\/strong\u003e — diagrams for agent graph, tool registry, auth model, and deployment topology.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePrototype scope\u003c\/strong\u003e — thin vertical slice to validate tool calls and failure modes.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eProduction roadmap\u003c\/strong\u003e — phased rollout tied to \u003ca href=\"\/products\/ai-agent-harness-design\"\u003eharness \u0026amp; eval design\u003c\/a\u003e and optional \u003ca href=\"\/products\/forward-deployed-engineering\"\u003eforward deployed engineering\u003c\/a\u003e.\u003c\/li\u003e\n\u003c\/ol\u003e\u003ch3\u003eDeliverables\u003c\/h3\u003e\u003cul\u003e\n\u003cli\u003eArchitecture decision record (ADR) and system diagrams\u003c\/li\u003e\n\u003cli\u003eTool\/MCP specification with schemas and error contracts\u003c\/li\u003e\n\u003cli\u003eGuardrail \u0026amp; security checklist\u003c\/li\u003e\n\u003cli\u003ePilot backlog with acceptance criteria\u003c\/li\u003e\n\u003cli\u003eTechnology recommendations (models, frameworks, observability) — pragmatic, not a laundry list\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eHow This Differs From Integration\u003c\/h3\u003e\u003cp\u003eOur \u003ca href=\"\/products\/ai-agent-enterprise-integration\"\u003eAI Agent Enterprise Integration\u003c\/a\u003e service focuses on wiring agents into N8N, Make, Zapier, and existing automation stacks. \u003cstrong\u003eAgent Design\u003c\/strong\u003e is upstream: the blueprint that makes integration durable. Many clients engage Design first, then Integration or FDE for rollout.\u003c\/p\u003e\u003ch3\u003eRelated Services\u003c\/h3\u003e\u003cp\u003e\u003ca href=\"\/collections\/ai-engineering-service\"\u003eAI Engineering\u003c\/a\u003e · \u003ca href=\"\/products\/ai-agent-harness-design\"\u003eAgent Harness \u0026amp; Eval\u003c\/a\u003e · \u003ca href=\"\/products\/forward-deployed-engineering\"\u003eForward Deployed Engineering\u003c\/a\u003e · \u003ca href=\"\/pages\/physical-ai\"\u003ePhysical AI\u003c\/a\u003e\u003c\/p\u003e\u003ch3\u003eFrequently Asked Questions\u003c\/h3\u003e\u003cp\u003e\u003cstrong\u003eDo you build the agent or only design it?\u003c\/strong\u003e\u003cbr\u003eBoth. Design can be a standalone engagement; we often continue into build, harness design, and deployment.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWhich models and frameworks do you support?\u003c\/strong\u003e\u003cbr\u003eWe are model-agnostic — OpenAI, Anthropic, open-weight models, and edge deployments. Framework choices depend on your stack; we document trade-offs in the architecture phase.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eCan you design agents for regulated industries?\u003c\/strong\u003e\u003cbr\u003eYes. We incorporate audit logging, data residency, and human approval steps into the design from day one.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eHow long does agent design take?\u003c\/strong\u003e\u003cbr\u003eTypical discovery + architecture: 2–4 weeks for a focused use case; larger multi-agent programs are phased.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWe already have an internal team — can you augment them?\u003c\/strong\u003e\u003cbr\u003eYes. We deliver architecture packages your team can implement, or pair via forward deployed engineering.\u003c\/p\u003e\u003cscript type=\"application\/ld+json\"\u003e{\"@context\":\"https:\/\/schema.org\",\"@type\":\"FAQPage\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"Do you build the agent or only design it?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Both. Design can be a standalone engagement; we often continue into build, harness design, and deployment.\"}},{\"@type\":\"Question\",\"name\":\"Which models and frameworks do you support?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"We are model-agnostic — OpenAI, Anthropic, open-weight models, and edge deployments. Framework choices depend on your stack.\"}},{\"@type\":\"Question\",\"name\":\"Can you design agents for regulated industries?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Yes. 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We deliver architecture packages your team can implement, or pair via forward deployed engineering.\"}}]}\u003c\/script\u003e","brand":"Tech Wall Electronics","offers":[{"title":"Default Title","offer_id":46479069446280,"sku":null,"price":0.0,"currency_code":"HKD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0641\/6692\/0328\/files\/TechwallAIAgentDevelopmentService_7ac23e6a-32f7-4fcb-b3c1-f949dfd7dab7.jpg?v=1788428273","url":"https:\/\/www.techwall.com.hk\/products\/ai-agent-design","provider":"Tech Wall Electronics","version":"1.0","type":"link"}