T4

Tomorrow, Angel Squad and T4 are hosting a lively discussion on: How to approach market entry strategy We’ll dive into the 5 critical steps that frame your market opportunity analysis: - Hypothesis Generation - Evaluation Criteria - Deep Segment Discovery - Prioritization - Validation Join us tomorrow for this insightful discussion👇

Tomorrow, Angel Squad and T4 are hosting a lively discussion on: How to approach market entry strategy We’ll dive into the 5 critical steps that frame your market opportunity analysis: - Hypothesis Generation - Evaluation Criteria - Deep Segment Discovery - Prioritization - Validation Join us tomorrow for this insightful discussion👇

How do you turn 125 good ideas into 3 ideas worth testing and pursuing? Tomorrow, we’re sitting down with our friends at T4 to discuss exactly this. We’ll go through everything you need to know to conduct a market opportunity analysis and examples of companies that have done this well and not so well. This is crucial for any founder or aspiring founder to listen to. Register here 👇

As a founder, you may have an ideal customer segment in mind and some possible solutions to the challenges they face, but how do you narrow down all the possibilities to one solution you can build? Your market entry strategy is key to building the right thing for the right people at the right time. Next week, Angel Squad and T4 are co-hosting a discussion on exactly this dilemma facing founders. We’ll dive into the 5 critical steps that frame your market opportunity analysis: -Hypothesis Generation -Evaluation Criteria -Deep Segment Discovery -Prioritization -Validation We’ll also provide some great examples of companies that have done this really well and others that haven’t. You’ll want to hear this one. Registration link is in the comments 👇

How do different members of your team define "value", and could these different definitions be leading your team to feel undervalued? This week, I delved into what "feeling valued" truly means to our team at T4. The results offer valuable insights applicable to any team, so I'm sharing my findings here: 🎯 Differing Perspectives by Seniority: Across the board, our team members strongly associate their sense of value with the impact of their work, but the way this impact is perceived differs based on seniority levels. Associates, still in the process of building confidence, seek validation through recognition and feedback from managers and clients. Meanwhile, seasoned managers find value in witnessing the growth and development of their team and clients. 🤝 Embracing Collaboration: Collaboration and feeling “part of the team” contribute heavily to feelings of impact and value. Balancing "total ownership" from associates and offering opportunities for collaboration is important in fostering feelings of value. ⬆ Managing Up: Overdependency on a "managing up" model may lack opportunity for active management and collaboration, which feels isolating, and increases opportunities for wheel spinning. 🌟Initiative vs Trust: Managers expect initiative from associates for new ideas and projects., while associates appreciate delegated tasks as a sign of trust from managers. 📉 Feedback "Death Spiral": When managers feel too stretched to give timely and actionable feedback, I call this the "feedback death spiral". Managers find value in watching the growth and development of associates, but may be too stretched to do so --> they feel less valued. Associates find value in knowing their work is impactful but are having to wait to receive input, and feel like lower on the priority list --> they feel less valued. So, how aligned are you on how your team feels valued? Could any of these gaps apply to your team, too?

One of my favorite activities is figuring out what an "AI" company actually does. I believe there are five distinct categories of AI: Truly New AI, AI at Scale, Purposing Existing AI Tools for Special Applications, Human AI, and Not AI. The first category, Truly New AI, represents less than 0.1% of AI companies and includes big names like OpenAI and Google DeepMind. The second category, AI at Scale, focuses on analyzing large volumes of data quickly, even if it's not always AI. Splunk, for example, is an "AI" company that made its name doing simple data regressions at scale on large amounts of data (not AI). The third category, Purposing Existing AI Tools for Applications, comprises the bulk of AI companies. AlphaSense is a prime example of a company that took an existing AI search model, trained and tuned it, and wrapped it in incredible marketing and PR to create a leading financial data search platform. The fourth category, Human AI, might surprise some people. This category includes applications that people think are powered by special analytical tools but are actually powered by humans. Ever wait 5 hours for your Coinbase's KYC algorithm to match your webcam photo and Driver's License? Maybe waited two hours for your Amazon Go receipt? Your Human AI may have been taking a lunch break. The fifth and final category: Not AI. This includes companies that advertise AI but may only be white labeling a basic AI tool, or not doing AI at all. Customer support chatbots often use if-then decision trees, not AI. In fact a client once asked us to size the AI Chatbot market. The result? Despite all the fancy reports claiming it was a multi-billion dollar market, the reality is true AI chatbots were almost non existent at the time. Are there any categories you think should be added to this list?

When it comes to resolving conflicts in the workplace, it's important to have a system in place. That's why when Yev Spektor and I started T4, we developed a simple three-question approach that resolved 95% of our conflicts in under five minutes. What problem are we really trying to solve? Is this really a problem? What's the easiest way to solve this problem? 1. What problem are we really trying to solve? Here's the thing - you may come to your colleague with a problem or a proposed solution. Sometimes if you take a step back, you realize the problem you actually need to solve is different than what you thought. 2. Is this really a problem? This has a few flavors - is the impact as big as we initially thought? Is it worth spending our time on? Is this actually an opportunity? You'd be surprised how many conflicts you can resolve with this question. 3. What's the easiest way to solve this problem? This is one of the most expensive questions people don't ask. I can't tell you how many times we found a 5 minute solution to what initially seemed like a 5 day problem. What about the other 5% of conflicts? For Yev and I, these were typically designed related conflicts. We would ask for external input. #conflictresolution #teamwork #businessgrowth