Every year I make a list of predictions and score last year’s predictions.

2021 marked the second year of COVID and like other crises, the pandemic accelerated change, especially in technology pushing many technologies like SaaS, video conferencing, crypto/web3 deeper into the Perez deployment cycle .

Here are my predictions for 2022:

1. Web3 consumer products go fully mainstream with more than 35% of Americans, about 100m people, engaging with them by 2023. Metamask counts 10m MAU and Phantom is at 1.5m MAU growing quickly. This trend is only increasing. Wallets are the gateway to crypto and have funneled millions into consumer apps that have driven web3 adoption. These throngs stress systems and demand infrastructure advances. Improved infrastructure enables new applications, which attract more users. This oscillation between apps and infrastructure continues forever as a pendulum. Meanwhile, once there are enough infrastructure and consumer companies to serve, software businesses pop up, in this case to serve DAOs.
2. Data companies continue to achieve astronomical growth. Software engineering best practices have begun to infuse data: data observability, specialization of different ETL layers, data exploration, and data security all thrived in 2021 and will continue as users stuff more data into databases and data lakehouses. Large software companies accelerated growth this year, despite their scale reinforcing the notion that users write data into systems but rarely delete it.
3. GPT-3 and BERT infuse software massively reducing repetitive work and unlocking huge productivity gains. GTP-3 and BERT are massive machine learning systems called neural nets. Their neuron count is only one or two orders of magnitude less than a human brain, and parity isn’t far off. The result of all a supremely rational artificial cerebrum: type in a few key sentences into a GPT-3 powered app, click a button, and a blog post pops out. (Not this one; I enjoy writing too much to automate it). Or a personalized email to a sales prospect. Or a tweet. Toil will be automated by these robots, leaving us to garnish the vanilla cake output with a layer of digital frosting. Marketing, customer success, and sales software will be upended. Engineers’ productivity will skyrocket as AI pair programming increases code authoring speed and reduces errors simultaneously.
4. The ML stack folds into the classic data stack. This idea is more controversial. The vast majority of ML users prefer simplicity and speed to customization and control. Consequently, data innovators will continue to push AutoML and SQL to query ML models to the technically analytical. Much of what’s built in the ML stack is a re-implementation of the modern data stack. ML specific data applications aren’t much different than classical data applications. ML specific feature stores can be managed through data lakehouse technologies like Nessie and Parquet, just as regular data ought to be. These stacks will begin a convergence. Within Google, Facebook, and other data leaders bespoke systems remain de rigeur as a core strategic advantage.
5. The spirit of Silicon Valley continues a spread outward. The valley remains an important locus on innovation but its monopoly recedes as new geographies rise in importance and remote work, plus the return of in-person travel, creates a new way of working for many. Silicon Valley falls to below 20% in all venture financing.

Scoring last year’s predictions:

1. Working remotely for a year changes how we work forever. Absolutely this happened. Friends have relocated to different cities. Remote-first and remote-only companies have gone public. Video-conferencing and remote collaboration is an integral part of knowledge workers days forever.
2. 2020 becomes the decade of data. Yes. The Snowflake IPO, the forth-coming DataBricks IPO. The valuation multiples in the data world top software both in the public markets and private markets.
3. M&As and IPOs continue at torrid rates. Yes. In 2021, 601 venture-backed IPOs raised $198b, up 40% in deal count and 173% in dollars. M&A value increased 24% and volumes up 28%. Both figures are records in the past decade.
4. Blockchain technologies become mainstream driven by the adoption of national reserve banks. Whiff. Central bank digital coins (CBDC)s are still very early in the US and China. El Salvador’s adoption of BTC and the Lightning network is a canary but the flock is still very much still at the nest.
5. Product-led growth becomes the standard GTM and infrastructure companies. Half a point. Most companies pitch PLG forward motions when raising capital and some have internal initiatives to push in this direction. But in the day-to-day operations of the majority of businesses, classic sales and marketing motions are the classical ones; and the transition has proved more fundamental and a longer investment to achieve.

3.5; same as last year. I’ll take a 70% accuracy on a one year prediction as success.

Regardless of these predictions, the pace of innovation and the breadth of advancement spellbinds me.

Ten years ago, we carried the iPhone 4 and the Motorola Droid in our pockets. Cryptocurrencies hadn’t been invented. VCs invested $10b per year. Most of us commuted every day and conference call bridges were state of the art. Electric cars remained curiosities and NASA sent the Space Shuttle to refuel the International Space Station.

Today, the iPhone has the leading chip architecture, the Google Pixels use ML to edit images and translate instantly. SpaceX will launch one rocket into space every other week. Electric car sales are doubling year over year and virtual backgrounds make every room our home office.