Insights & AI Pulse
Enterprise AI implementation insights, operational AI trends, AI Agents, Enterprise RAG, workflow automation, and systems integration.
For leaders building production-ready AI systems tied to measurable business outcomes.
- Cadence
- Monthly
- Topics
- 9 areas
- Audience
- CIO · CTO · COO
- AI AgentsAccelerating
- Enterprise RAGMaturing
- Workflow AutomationMainstream
- AI GovernanceEmerging
- AI IntegrationStandardizing
Indicative momentum signals from enterprise AI adoption patterns observed in field engagements. Not investment guidance.
This month's reading
Why your RAG system gets worse over time — and how to fix retrieval drift before users complain
The first 90 days, your RAG system feels accurate. By month five it’s firefighting. Four drift drivers, four detection signals, three embedding refresh strategies, and the operational practices that catch the regression in dashboards instead of customer complaints.
From RAG to GraphRAG: when vector search isn’t enough for legal, finance, and engineering docs
Vector search finds chunks similar to your query — that’s the whole mechanism. For legal contracts, financial filings, and engineering BoMs where relationships between entities matter, similarity isn’t structure. A practical guide to GraphRAG and the hybrid retrieval pattern that fits most enterprises.
Knowledge graphs + LLMs for Vietnamese enterprises: handling language nuance at scale
Vietnamese tone marks. Compound-noun word boundaries. Company-name conventions (Công ty Cổ phần / TNHH / JSC). Administrative restructuring of districts and wards. Code-switching with English. Regional vocabulary. Six realities that break off-the-shelf retrieval — and how a knowledge-graph layer handles them.
6 areas. One operational AI worldview.
Security
LLM threat modeling, prompt-injection patterns, AI agent governance, and practical security controls for enterprise AI deployments.
BrowseAgents
Agentic AI patterns, multi-agent orchestration, tool-call architecture, and operational AI Agent design.
BrowseAI Strategy
Executive-level AI strategy, ROI measurement, FinOps for AI, and platform-build decisions.
BrowseRetrieval & RAG
Enterprise RAG, GraphRAG, retrieval evaluation, knowledge graphs, and AI-powered enterprise search.
BrowseKnowledge AI
Enterprise knowledge intelligence — RAG, knowledge graphs, and Vietnamese-language knowledge AI applied to operational workflows.
BrowseVoice AI
Voice AI for enterprise customer service, Vietnamese-language voice deployments, and conversational AI design.
BrowseRecently published on AI Pulse
Computer-use agents vs. legacy RPA: where each one actually belongs
UiPath and Automation Anywhere aren’t dead — they’re still doing real work in real enterprises. But computer-use agents handle the tasks RPA was always bad at. A six-question allocation rule and the hybrid pattern most enterprises actually need.
The CFO's AI scorecard: measuring real ROI in the first 12 months
Most AI projects fail the CFO test not because they didn’t work but because nobody measured them in finance terms. Four buckets — revenue, cost, risk, capability — each with a baseline, a target, and a 30/60/90 cadence so the answer in month twelve doesn’t rest on storytelling.
Beyond chatbots: agentic AI is finally crossing into core enterprise workflows
Agentic AI — models that plan, call tools, verify their own outputs — has crossed the threshold from demo to production. Three things change in the architecture, three workflows earn it first, and one rule of thumb tells you when not to reach for an agent.
The token economics of scale: keeping AI costs flat as usage 10×s
Token cost grows linearly with usage. Five well-known levers — model routing, prompt caching, response budgets, batch APIs, eval-driven downgrades — compound to flatten that curve. Most teams pull them out of order. The eval suite is the prerequisite for the biggest savings.
Voice AI for Vietnamese customer service: dialects, code-switching, and brand voice
Voice AI works well in English. For Vietnamese customer service, off-the-shelf stacks miss three things — regional dialect variation, English/Vietnamese code-switching mid-call, and brand-appropriate Vietnamese register. Each one shows up in CSAT before the engineering team notices.
Beyond prompt injection: data exfiltration risks in enterprise AI agents
Prompt injection is the entry point. The interesting question is what the agent does next. Four exfiltration patterns appear repeatedly in real enterprise AI agent deployments — each one has an architectural remediation, not a prompt-level one.
Building an LLM threat model: a 7-step framework for enterprise AI
STRIDE doesn’t fit. OWASP’s LLM Top 10 is a taxonomy, not a process. Compliance checklists ask the right questions for the wrong systems. A seven-step framework that produces a CISO-signable artifact and a runbook your engineering team will actually use.
Five prompt injection patterns most security teams aren't testing for
Direct injection is the easy one. The four patterns that get past production red-teams — indirect injection via retrieved documents, tool-call hijacking, multi-turn context manipulation, encoding tricks — are the ones worth running before you ship.
What we're tracking
Patterns we observe across enterprise AI engagements — what's becoming standard, what's still emerging, and where the operational edge is moving.
AI Agents
Agent frameworks moving from POC to production-grade with RBAC and audit.
Enterprise RAG
Permission-aware retrieval and evaluation pipelines becoming table stakes.
Operational AI
AI moving out of marketing/support into finance, ops, and back-office workflows.
Workflow Orchestration
Multi-step orchestration with human-in-the-loop replacing single-prompt patterns.
AI Governance
From advisory committee to runtime controls, monitoring, and audit at the call site.
Human + AI Collaboration
Augmentation patterns winning over replacement narratives in adoption-led orgs.
Indicative qualitative signals from IDS field engagements across 10+ countries — not industry research. Updated quarterly.
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