Airtable的动态

Power of public product roadmaps ?????? At TextCortex AI, going full transparency with a public product roadmap ??? has been a game-changer for customer happiness and our dev speed! ??? Some months ago, we opened up and started sharing our roadmap publicly. The impact has been simply mind-blowing: - Customers feel heard and in the loop ?? - We get a firehose of customer insights ?? - Faster dev velocity with accountability ?? - Stronger product/market fit ?? You can see how in our product update video with Dominik Lambersy (see comments ??) on exactly how we manage this public roadmap process and incorporate constant customer feedback. Check out Ducalis for their awesome product roadmap tool!

Shipping fast means *making decisions* fast. Here's how we optimize for fast, non-blocking decision-making at Shortwave. #1: Communications bandwidth -- we do everything we can to increase the rate of information flow between team members. If everyone has the same information they're more likely to be close to consensus, which makes decisions easier. Most of our team is in-person every day. Our remote folks join us in-person for week-long offsites 5 times per year. We use a ton of collaboration tools. Notion, Asana, Figma, etc. Gather is esp critical - it's our virtual office & makes sure everyone is always accessible. We do a *ton* of writing. New folks are often shocked by how much. We write PRDs, design docs, and, of course *lots of emails*! We heavily use @Shortwave & have channels for everything: Eng, Product & Design, Ops, Support, etc. I send 30-40 emails per day internally. #2: Process & schedule, but with *progress* as the real goal Well-defined & well-oiled processes can help a company move fast -- until they don't! We put a lot of effort into process -- but we sidestep (or change) it any time it's getting in the way of the real objectives. Our schedule is broken into "Oceans" - ~11 week periods that start with an offsite. We reprioritize everything at the offsites, write down goals & then execute like hell until the next one Time-boxing high level discussion avoids bikesheds during the ensuing work period. We're super organized: everything is in Asana, our Notion is carefully structured, and we have clear expectations for how to communicate things. There's clear process for how to file bugs, propose new features, get PRs reviewed, etc. It's all written down. #3: Non-blocking decision making We give our team a ton of latitude in what they can push forward unilaterally & we trust them to use good judgement. Is this task important? Does this design need more review? Who should be in this meeting? -- you tell me! We have to have *some* coordination -- but we want it to be non-blocking. Our approach is "FYI emails". Every time you make a change that affects end users or core internal abstractions, you send an email to the team letting them know. You don't block on people responding -but people have a chance to speak up. For the programmers out there, think of this as "optimistic concurrency" for organizations. Make the decision assuming everyone is on board, communicate it, and then roll back if needed. #4: Type 1 and Type 2 decisions Type 1 decisions are irreversible, or at least very hard to change once executed. Make them very carefully. Type 2 decisions can be undone easily. Just move fast and reverse course if you were wrong. The vast majority of decisions are Type 2. #5: Super clear company priorities I have a clear, stack-ranked list of "company priorities" at all times. Knowing what matters most to the business has a trickle down effect to every single decision made at the company.

BIG NEWS out of LogRocket Today! ?? Galileo AI is officially launched ?? Imagine a new member on your product team - but it can watch EVERY user session while still understanding those interactions like a real human would. With product teams owning conversion, adoption, retention, and more, they need help understanding what’s causing user struggle. That’s where Galileo comes in, helping you quickly surface key user patterns and detect those struggle areas. Check out our blog post in the comments for all the details.

In the past few months, we’ve prioritized features that increase users’ efficiency. And one of the solutions we launched at Team O'clock was “AI-Assist.” We released this feature to take over trivial management tasks so users can focus on building and shipping successful products. AI-Assist helps you: - Get retrospective activities based on your prompt - Group notes based on context and message, on autopilot - Receive suggestions for task breakdown with high estimation effort AI-Assist was our first major AI-powered feature and is available to all Team O’clock users. Want to learn more? ?? https://bit.ly/3ucbhoC

And, it's a wrap at #M365Conf. - 3 sessions on Teams and Copilot for industries (Health and Life Sciences, Retail and Consumer Goods, Financial Services) - 18 Customer meetings discussing Copilot, AI and Teams - 5 Partner meetings discussion Copilot, Teams and Platform extensibility Couple of key highlights: - Sharing the stage with David Feldman who was gracious to share his thought leadership in the AI space by sharing his experience on Copilot. Thanks Dave! - Meeting colleagues who I haven't seen in a while. It was great to spend time discussing product, customer feedback and getting to know each other better!

How does Dovetail turn customer conversations into actionable insights? Learn how Sales and Success teams use our customer insights hub to get instant context, close deals faster, and influence more roadmap decisions, all using the power of AI. This live demo session with Dovetail product experts is perfect for teams on all plans, as well as new starters. See you on September 26: https://dvtl.link/4dXfxuh

So many questions go unanswered when home delivery operations are managed manually. - Did the rider really deliver? - Do you really need more riders? - Which store is performing best? - Who is your top rider? - What is the optimum trip capacity? - How many orders are on time and how many are late right now? With an AI automated delivery operation, a wealth of insights are automatically revealed in real-time to help identify what is holding you back and how to grow. Book a demo and learn how Roboost makes delivery the easiest part of your business. https://lnkd.in/dQBGBE3U

Last week in my AI course at MIT Sloan School of Management, we delved into machine learning. There are two main areas where this can be practical for businesses: 1- training computers to recognize things ?? and take action as a result, for example in autonomous cars 2- using historical data to train computers to predict future events ?? , for example predicting credit card fraud The second one is quite interesting and a classic use is recommendation engines. Many consumer-facing businesses have sufficient data to be able to recommend the next best products to their customers and cross-sell in a very personalised way. This makes it easier for customers to find great products and is obviously a driver of incremental revenues for companies. Amazon and Netflix are obvious examples of companies doing this, but going much further back so was Tesco with their Clubcard. What's nice now is that it has become much easier to do, so there should be no reason why any business shouldn't do it. I wanted to share this short video about the Spotify recommendation algorithm which is a great example of machine learning in action. Do you know of any other examples of machine learning in action in business? https://lnkd.in/evdCQGHk #machinelearning #artificialintelligenceforbusiness #personaldevelopment

Check this out .... Our new suite of Bot Analytics is here! Learn how Calabrio Bot Analytics helps contact centers measure, understand and improve chatbot and voice bot performance: https://bit.ly/3TTyvsY #Calabrio #botanalytics #chatbots #QM

Our new suite of Bot Analytics is here! Learn how Calabrio Bot Analytics helps contact centers measure, understand and improve chatbot and voice bot performance: https://bit.ly/3TTyvsY #Calabrio #botanalytics #chatbots #QM