Effective Work Methods

Lots of companies talk about AI, but making it stick means changing how work actually gets done. Forget just the tech hype – these are the kinds of operational shifts that separate real progress from noise:

Rapid Prototyping, Not Endless Planning

Get ideas built and tested fast. Instead of getting stuck planning forever, build something quickly, see if it works, and then decide the next step. Momentum matters.

Collaborating Across Teams

Get the right people talking from day one. Tech, business, design, data – everyone involved early helps ensure solutions actually hit the mark and meet real needs.

Stop Trapping Data in Slides

Information stuck in PowerPoint is mostly useless for AI or automation downstream. Push for formats like Markdown or collaborative tools (Notion, Loop) where data is accessible and usable by systems.

APIs are Non-Negotiable

If you want AI agents or serious automation, systems must talk to each other cleanly. That means proper APIs, not relying on manual processes or digital versions of fax machines.

Smart, Modular Tooling

Use the right tech for the specific job; don't get locked into one vendor's ecosystem for everything. Build solutions with reusable components so you stay flexible as technology evolves.

Automate the Boring Stuff

Find the repetitive, time-draining tasks and automate them. Let people focus their brainpower on work that actually requires human thinking and creativity.

Solve Real Problems

Tie every AI effort directly back to a specific, identified business challenge. If it doesn't solve a real problem or deliver tangible value, it's probably not worth doing.

Build Your Own Muscle

The real goal is for your organization's teams to get capable and own their AI journey long-term. Sustainable success comes from internal strength, not permanent reliance on outsiders.