Agentic AI is not a standalone marvel but a powerful addition to an ecosystem deeply rooted in foundational engineering excellence. Agentic AI systems—those that can autonomously pursue goals, make decisions, and adapt, are "Built on Foundational Engineering Pillars", and requires -> Robust data pipelines for context and learning. -> Scalable infrastructure to support real-time reasoning and action. -> Secure environments to ensure safe autonomy. -> Reliable software engineering for modularity, observability, and resilience. Without these, agentic behavior becomes brittle or unsafe. Agentic AI doesn’t operate in isolation. It "Thrives in an Ecosystem of Interoperability" and needs -> Access to APIs, tools, and systems to take meaningful actions. -> Integration with governance frameworks to ensure ethical boundaries. -> Feedback loops from users and systems to refine its behavior. This makes it a system-level capability, not a plug-and-play feature. Alex Wang - thanks for this post! You are hitting the right chord with this.
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Building AI agents = 5% AI + 95% software engineering. Not exact ratio, but you get the point. We don’t just “build an agent”; we architect a system and let the AI sit inside it. Enterprise-ready agent platforms are classic software + reliability engineering work: ✅ Identity and access management ✅ Document filtering and governance (ACLs, redaction, PII masking) ✅ Schema mapping and data contracts ✅ Human-in-the-loop escalation ✅ Infra that scales across vector and SQL ✅ Observability, evals, guardrails, cost controls, and audit logs Think of agents like APIs that can reason, not magic. They still need: - Fine-grained access control - Storage that separates structured and unstructured knowledge - Tracing, fallback routing, and lineage - Flows that connect document pipelines with model orchestration (MCP, tools, integrations) Before you tune prompts, build the foundations. If you’re exploring agent workflows, check out our open-source platform, a lightweight framework we use to run multi-agent systems: GitHub: https://bit.ly/4kzE1Mt Explore our public investment: 🔗https://bit.ly/41JeDNO __________ For more on AI and learning materials, plz check my previous posts. I share my journey here. Join me and let's grow together. Alex Wang #AIagents #AgenticAI #EnterpriseAI #Technology
Director of Technology at Publicis Sapient
4wThe GitHub repo in the article is a real booster. Thank you for sharing Anita Alexander