Finding the right opportunities in AI, scaling lessons
+ AI reading list
Hi! I hope you’ve enjoyed the mini-series on building AI products. This week I’m back with a series of interesting reads on product building and go to market lessons.
Unsolicited feedback’s live event about advancing your product career in an AI world explored a thought experiment about what AI’s good at and not good at today. Eg. it’s good at execution tasks, and not so good at deeper thinking and planning. Because of this, Brian and Fareed predict that mid-level management will shift to senior ICs (principal, staff). Some recommendations? Get great with data manipulation (eg. SQL), and tinker with a side project with LLMs, it’s the best way to learn.
Mini product teardown: Lapse, the disposable camera app that’s trying to become the anti-Instagram. It apparently ranked 3rd on the App store at in November. My quick review after trying it for a few days? They nailed the film look but wow it’s got a passive aggressive personality! It forces you to invite 5 friends before allowing access to any feature. It uses sad emojis and snarks to guilt-trip you into adding friends and publishing snaps. How do you think about the balance between aggressive push for growth vs. generally pleasant user experience? How likely would this friend only / authenticity-driven model survive over the following/influencer model with traditional social media giants? I’m doubtful. Kevin Systrom’s Artifact shut down after a year. It’s hard to make a new king in social.
Winning the AI Products Arms Race. The AI survival curve uses “consideration” vs. “context” axes to evaluate AI opportunities. Consideration: the amount of effort needed to make a decision. Context: the volume of abstract concepts AI needs to know. Successful AI products all fall on this curve.
Finding the right opportunities in AI. Christoph shares his mental map on how to think about opportunities in AI. Vertical products is more opportunistic than horizontal, because AI-first startups can leapfrog from pen& paper to AI, and there are more opportunities to sell work products instead of software. He’s also more interested in very hard to solve problems, and in new categories that are enabled by AI rather than applying AI to existing areas.
Arc Browser’s act 2. Arc describes a vision for a new internet that blends together search engine + web pages + browser. It browses for you, ie. goes through all the websites and presents a new page with exactly what you need, no ads, no filler content that’s optimized for SEO. It’s a lot of grandiose exclaimations. What would that future mean for webpages? Do they just become "headless" information?
On platform shifts and AI. “What separates a major platform shift from a minor platform shift is a platform shift that enables both a technological shift (new ways of making things possible) paired with a distribution shift (new ways of reaching people with it).”
What it really takes to be successful in enterprise SaaS sales. Christian, CRO of Splunk, emphasizes using the quality of pipeline as the key metric for assessing the overall health of the business - ie. characteristics of the pipeline, conversion rates. Splunk’s favourite demand gen strategy is product generated pipeline, basically PLG. Leverage existing usage to generate expansion opportunities. Segmentation is key to structuring sales - done by ARR and ARR potential.
The only playbook for competitor research and strategy you’ll ever need. A wildly comprehensive resource by Patrick Campbell who founded ProfitWell, sold to Paddle. Most companies don’t do competitive strategy properly. Don’t be seduced by the idea that “competitor are not important”, there are very few one in a million unicorn products out there. Watch your competitors and defend. This guide gives highly specific tactics and frameworks on competitive intelligence.
How revenue leaders at Box, Calendly, and Lattice scaled from $0 to $100M+. This conversation is filled with million dollar lessons from pivotal moments at these cloud 100 companies. At Lattice, pausing PLG and getting clear on ICP definition significantly grew conversion. Sales were having less calls per day but they were much higher quality accounts with higher conversion. For horizontal products like Calendly, leverage popular use cases to build vertical solutions around. Consider org changes across product, people, and process when going upmarket to enterprise. When sharing challenges outside your own domain, develop relationships with all the functional leaders first. Understand when to be a functional leader vs. a corporate executive (removing biases towards your own function and thinking as a single team towards a north star).
The Model Market Fit threshold & what it means for your growth strategy. A classic by Brian Balfour, thinking beyond just product market fit. It’s the concept that your market and the number of customers in your market influence your model. On a graph of ARPA by # of customers, there’s an inverse line that represents the model market fit threshold. The model market fit hypothesis is based on this equation: ARPU x Total Customers In Market x % You Think You Can Capture >= $100M
🔗 AI resources
AI and everything else - Ben Evans’ annual presentation. Analysis and predictions on where AI is at and where it’s going.