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Harnessing agentic coding toward autonomous engineering: What we’ve learned so far

A CTO's hard-won perspective on moving AI beyond code generation, building the guardrails, review loops, and text-driven control planes that make autonomous engineering safe, reviewable, and realy.

AI engineering
Apr 1, 2026

All Articles

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Generative AI
Apr 2, 2025
Seven RAG engineering failure points
Explore the seven key failure points in engineering RAG systems, from missing content and retrieval errors to wrong formats and incomplete responses.
Cobus Greyling
Cobus Greyling
Generative AI
Mar 31, 2025
UniMS-RAG: Unified multi-source RAG for personalised dialogue
Explore UniMS-RAG, a unified framework that enhances LLMs by integrating multi-source retrieval and self-refinement for highly personalized AI dialogues.
Cobus Greyling
Cobus Greyling
Enterprise search
Mar 30, 2025
How is RAG reinventing enterprise search and reducing time-to-insight?
RAG transforms enterprise search from keyword matching to context-aware intelligence. Learn how retrieval-augmented generation cuts time-to-insight, reduces hallucinations, and powers faster decisions.
Juhi Tiwari
Juhi Tiwari
Generative AI
Mar 29, 2025
Breaking knowledge silos with RAG: The future of enterprise search
Fragmented knowledge kills productivity. Discover how retrieval-augmented generation (RAG) breaks down enterprise data silos and delivers context-aware answers, at scale, on the Kore.ai Agent Platform.
Juhi Tiwari
Juhi Tiwari
Generative AI
Mar 28, 2025
What is RAG - Retrieval-Augmented Generation ?
Retrieval-augmented generation (RAG) improves LLM accuracy by grounding responses in real enterprise data. Learn how RAG works, when to use it, and how Kore.ai uses it to power secure, context-aware AI agents.
Juhi Tiwari
Juhi Tiwari
Generative AI
Mar 28, 2025
Chain-of-Symbol prompting (CoS) for LLMs
LLMs need to understand a virtual spatial environment described through natural language while planning & achieving defined goals in the environment.
Cobus Greyling
Cobus Greyling

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