Hi Data & AI Pros,
Oracle remains mission-critical but modernizing how Oracle data moves across your environment doesn’t have to mean complex tooling, fragile scripts, or risky migrations.
Join us on Thursday, January 29 at 10am ET for a live demo of CData Sync, where we’ll show how to modernize Oracle data integration without re-architecting systems, granting elevated privileges, or introducing operational risk.
In this session, you’ll learn how CData Sync:
Captures Oracle inserts, updates, and deletes using CDC without triggers or custom code
Connects to Oracle as both a source and destination across on-prem and cloud
Delivers data reliably to analytics, reporting, and AI platforms in near real time
Whether you’re a DBA, data engineer, or architect, this demo will show a simpler, more predictable path forward.
If you are aspiring to build a serious career in AI in 2026, learning tools is not enough. You need skills that actually compound over time.
Most people focus on prompts or the latest model. That helps you get started. It does not help you stand out.
The biggest shift I am seeing is this. AI roles are no longer about using one tool well. They are about understanding the full system around AI.
That is why I put together a breakdown of the top 15 AI skills almost everyone must know in 2026.
These are not hype skills. These are the skills teams quietly expect you to have.
A few that matter more than people realize:
- AI literacy
You must understand how models think, where they fail, and why hallucinations happen. Without this, everything else breaks.
- Context engineering
Great outputs do not come from clever prompts. They come from feeding the right context, instructions, memory, and examples before the model responds.
- Prompt chaining and workflows
Real work is never one prompt. It is plan, draft, improve, validate, and ship. This is how AI becomes useful at scale.
- AI research and fact checking
Using AI like a consultant matters more than generating text. Sources, comparisons, and insights are the real value.
- AI agents and automation
Delegating tasks to AI requires structure, guardrails, and evaluation. Otherwise agents become expensive demos.
- Evaluation and safety
The most underrated skill. If you cannot measure quality, consistency, cost, and failure modes, you are guessing instead of engineering.
- The key thing to understand is this.
In 2026, strong AI professionals are not judged by outputs. They are judged by reliability, repeatability, and real outcomes.
If you are planning to upskill this year, focus less on tricks and more on foundations.
This is where long term AI careers are being built.
READ MORE
🚨Breaking: Big announcements by MongoDB. I just spoke to Pete Johnson, Field CTO for AI at MongoDB on The Ravit Show. This conversation cuts through the noise around AI and focuses on what actually works in production!!!!
We get into:
- What the Field CTO for AI role really looks like in the field
- How MongoDB thinks about the data and AI intersection
- Which recent MongoDB announcements actually matter
- What enterprises should prioritize as they head into 2026
- Clear advice for developers, data, and DevOps teams building with AI
No hype. No buzzwords. Just practical insight from someone working directly with customers every day.
If you are building, scaling, or planning AI beyond pilots, this episode is for you.
🔍 Stay Ahead in AI & Data! Join 137K+ Data & AI professionals who stay updated with the latest trends, insights, and innovations.
📢 Want to sponsor or support this newsletter? Reach out and let's collaborate! 🚀
Best,
Ravit Jain
Founder & Host of The Ravit Show
