I would treat staying current as an operating benchmark, not a news-consumption problem. Pick three recurring tasks and rerun the same tests monthly across the tools you are considering. Track output accuracy, time saved, cost, and how often a human has to intervene. A new release matters only if it improves one of those numbers.

For a searcher, useful benchmarks could be broker-listing monitoring, first-pass document review under clear confidentiality rules, and turning call notes into a follow-up workflow. This keeps you competent without chasing every demo, and it also shows where the tools are reliable enough for real work.

Which workflow are you trying to improve first: sourcing, diligence, or post-close operations?

I spent 20+ years in Fortune 500 tech consulting I've watch wave after wave of technology but there is one pattern that the companies that are successful and it is slightly contrarian: The tools don't matter. or at least as much as where and how you use them. I found that AI tools tend to be 90% accurate at best...and I will share why in a moment. The thing now with AI is something new launches every week. These rapidly emerging tools fail not because the AI is bad because the tool has very little context on your organization. It doesn't know your customers, your pricing, your process, or what "good" looks like in your shop. It demos great and then can't do the job. So I'd flip the question. Instead of "how do I stay current on tools," build three things that compound: 1. Find one tool and get super familiar with it Claude, ChatGPT, the specific one matters less than people think by using it for everything for 30 days. Deal screening, CIM summaries, DD checklists, stress testing add backs. Live in it. Training it, challenging it, having it challenge you. It starts to understand your context. This can be transferred to any AI tool that wins next year with a simple prompt. 2. Know your business workflows cold. AI can only automate what you can describe. The operators I work with that are getting value out of AI aren't the ones with the best tools they're the ones who know exactly how work moves through their business and where the biggest constraint is in their busienss. 3. Hire the AI like an employee, not use it like a tool. That means onboarding it, give it the context a new hire would get. Training it...correct it, keep it up to date as the business changes. And connecting it to the systems it needs to actually do the job. Give it a job description and a standard, and ask for a deliverable, not an answer. People who use it like google get just better search answers and conclude it's overhyped. People who onboard it like a new hire end up with leverage. For staying current without drowning, I mostly rely on one source...Greg Isenberg's Startup Ideas Podcast...what's actually working with AI in real businesses, not demos. One good filter beats twenty newsletters, because newsletters keep you reading about tools instead of using them. The tools will keep changing. Context, knowing the real workflows of the business, and treating AI like an employee won't.