I think everyone should have an AI toolkit.

Not a long list of apps saved in a browser tab. A real toolkit: a small group of tools you trust, understand, and know how to bring into the work at the right moment.

My own toolkit has started to feel like a second operating system.

I use NotebookLM for learning. I give it material, stay with the source, ask questions, and turn a pile of information into something I can use. I use Perplexity for search and research when I need to move quickly from a question to sources and directions.

I use Claude Cowork and Claude Code for development and building. They help me move from an idea to a working thing, then keep working when the first version is not good enough. I use Codex for system configuration and for shaping the environment around the work.

For images, I use Higgsfield when I want to create a visual, and ChatGPT on the web when I need an image for internal communication or a LinkedIn post. These are different jobs. That distinction matters.

The most exciting change came when the tools stopped being isolated.

I created MCP connections for the Odoo ERP and Hostinger systems behind GPUMart. Once the systems could be reached through a useful interface, work that used to feel like several separate tasks became much easier to move through. We also built rdp.in/gpt with this broader way of working.

This is the part that is easy to miss when people talk about AI tools. The value is not only inside each tool. It is in the handoff between them.

NotebookLM helps me learn what I need to know. Perplexity helps me find what I do not know. Claude helps me build. Codex helps me configure. MCP helps me reach the systems where the work actually lives. Image tools help me explain the work to another person.

That is orchestration.

And orchestration is where the next level begins.

Without it, AI stays a chatbot. With it, AI becomes a working environment.

I have seen this in Odoo. Work that used to need what felt like half a dozen people can now be pushed forward by one person producing many times more output, because the person is no longer working inside one screen or one tool. They are moving across a connected set of tools, each doing the part it is good at.

This does not make the work automatic. It makes the worker more capable.

There is also a difficult side to this.

The tools are changing so quickly that before we have understood the new feature in one product, hundreds of new products have appeared around it. Learning the tool is one challenge. Learning how to get the desired output is another. Then comes the hardest question: how do you make the whole organization use the right tools without turning every person into a full-time tool researcher?

That requires more than buying licenses. It requires a living knowledge base: what the tool is for, when to use it, what good output looks like, what mistakes to expect, and how the work should move to the next tool.

It also requires a workflow that the organization can see.

• Find the tool. Start with the problem, not the novelty.
• Master the tool. Learn its edges, limits, and best use.
• Keep the tool in the workflow. Make it part of a real recurring task.
• Record the learning. Turn personal discovery into organizational memory.
• Repeat. The toolkit should keep getting better.

That is how an organization moves beyond asking a chatbot for an answer. It builds a system for learning, making, checking, connecting, and improving.

I am still discovering my own toolkit. The names will change. New tools will earn their place. Some tools will disappear. The important thing is not loyalty to a brand. It is the discipline of finding the right capability and putting it where it can compound.

So what is your toolkit?

Which tool helps you learn? Which one helps you search? Which one helps you build? Which one connects to the systems your organization actually runs? Which one helps you explain the work to another human?

The answers will be different for each person. But the pattern is becoming clear.

– Vikram Redlapalli