4.8/5 ★★★★★Engineering insights on custom software, AI systems, eCommerce platforms, and enterprise development. Written by the people who build this stuff.
73 posts · Page 6 of 7
Most AI development companies ship demos. Production AI requires data pipelines, error handling, monitoring, security, and cost management that demos skip entirely. Here's what the gap looks like and how to evaluate vendors.
Both Anthropic and OpenAI ship agent SDKs in 2026. Claude excels at long-context reasoning and structured output. OpenAI leads in ecosystem breadth and multi-agent handoffs. A technical comparison for production teams.
Vibe coding gets you from idea to prototype fast. But production needs database design, auth, error handling, tests, deployment, and monitoring that AI tools skip. Here's the complete checklist.
A first-person account of building an AI-powered procurement agent for Tejas Networks. From paper-based approvals to a 90% reduction in manual processing, covering architecture decisions, integration challenges, and what we'd build differently in 2026.
Agentic AI in enterprise means autonomous agents executing procurement, compliance, and operations workflows — not chatbots. Here's what production agentic AI looks like, what fails, and how to build the business case.
Standard RAG retrieves and generates in one pass. Agentic RAG plans, retrieves iteratively, verifies, and acts. Here's when each architecture is the right choice — and what production pitfalls to watch for.
Agentic AI handles exception-heavy, judgment-intensive processes that break traditional automation. Traditional RPA and workflow automation remain the right choice for deterministic, rule-bound processes. Here is the decision framework.
An AI call quality agent that monitors 100% of sales calls in real time, scoring against quality criteria and generating coaching summaries. Here is how we built it, what it cost, and what we would do differently.
AI agents have replaced or augmented five distinct business processes across Madgeek's client base — call quality monitoring, sales lead qualification, procurement approvals, cost estimation, and CRM triage — with measurable outcomes in each case.
An AI agent is software that completes multi-step tasks autonomously — using tools, making decisions, and taking actions without a human at each step. Here is what that means in practice, with three real production examples.
SAP S/4HANA implementation for a mid-market manufacturer costs $500K-$2M and takes 18-36 months. A custom ERP for the same operation costs $50K-$200K and deploys in 16-24 weeks. Here is when each path makes sense.
An offshore development center (ODC) is a dedicated engineering team in another country that works exclusively on your projects — embedded in your tools, workflow, and communication cadence. Here is how it works, what it costs, and when it makes sense.
