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Future of Code with Poolside CEO Jason Warner | 5YF #20

AI eats software, specialized models win, billions of coders, synthetic data, NVIDIA and the Hyperscalers

Future of Code: AI-led Software Development

Hi there!

It’s release day! Tune in here 🎧.

Today, we explore the future of developing software in an AI-led world.

If you're relying on AI not becoming 100X better, you're about to get steamrolled.

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Our world is increasingly written and run in code. Software has created the digital infrastructure powering every industry and has enabled human capital to reach ever increasing productivity. Yet all of the software in the world is created by just a small cohort of developers that represent 0.3% of the global population. What would progress look like if that number grew to 100%?

Jason Warner is one of the most qualified people to talk about software development and how it is transforming with Artificial Intelligence. He believes we have barely seen the start of ‘software eating the world’ and that our ability to produce software is about to explode.

My 5 Year Outlook:

  • Everyone will code

  • Search replaced by Action

  • AI will generate its way out of data scarcity

  • Foundation models to become cloud companies

Curious? Read on as I unpack each below 👇🏼

Everyone will code

The best code you never wrote.

GitHub’s Co-Pilot, pioneered during Jason’s tenure as CTO, revolutionized how developers interact with code by introducing AI-assisted coding. Today, AI contributes to 40% of code production. While this trend continues, the next significant shift will be moving from developer-led, AI-assisted programming to AI-led, developer-assisted programming. This transition will elevate junior developers and significantly boost software productivity.

However, this advancement benefits only those proficient in coding. More exciting is the prospect of enabling non-developers to code. Enabling the other 99% of the population to build and execute software is a thrilling possibility. With advancements translating code into plain English for documentation, reversing this process to convert English into code is a logical future step.

This shift will democratize software development, dismantling barriers that have historically required specialized training. Imagine a small business owner creating applications to best run their business, a teacher designing new educational tools, an entrepreneur shipping a new marketplace — all without hiring developers. This revolution will accelerate innovation, empower a wide spectrum of individuals, and foster a more inclusive and dynamic technological landscape.

🎧 Listen to our discussion

Jason Warner, Co-founder and CEO of Poolside

Poolside is an AI startup challenging OpenAI and Anthropic by creating its own models to build the most capable AI for software development. Although less than two years old and launching this summer, Poolside has already raised over $500M from leading investors such as Redpoint, Bain, and DST.

Jason is co-founder and CEO of Poolside. Jason was previously the CTO at GitHub, the world’s largest developer platform, both before and after Microsoft’s $7.5B acquisition, where he helped develop Co-pilot. Prior to that, he was the Head of Engineering at Heroku and a senior technical leader at numerous other companies. In addition to leading top software development teams, Jason served as a General Partner at Redpoint Ventures, who have invested in companies like Snowflake, Stripe, Hashicorp, and Netflix. He also sits on the Operator Board at Bridgewater Associates, helping them innovate at the technology frontier.

Search replaced by Action

Beyond democratizing coding, AI’s capabilities can redefine how we interact with technology by replacing traditional search methods with action-oriented requests. Instead of searching for information or tools for us to leverage towards achieving our ultimate goal, we could simply state our end objective, and AI would generate the necessary software on the fly.

For instance, someone needing to analyze sales data could request a specific analysis, and the AI would create a customized program to perform that task instantly. This shift from search to action would streamline workflows, enhance productivity, and provide tailored solutions in real-time.

Jason calls it “full program synthesis”, where a simple prompt in plain english is enough to kick off the software development lifecycle that can be completed end-to-end by the AI model.

As AI models get more capable, what we will see is the entire software development lifecycle collapse into the models.

It would represent a paradigm shift that will lay down a challenge to search engines like Google as well as traditional software players like Salesforce, which rely on lock-ins with high switching costs. With AI enabling on-demand custom software, the need for expensive, one-size-fits-all solutions diminishes. Users can generate tailored applications, reducing reliance on proprietary systems and long-term contracts. 

AI will generate its way out of data scarcity

The dirty little secret of the entire industry is we have access to the exact same data.

Lange Language Models (LLMs) like OpenAI have amazed the world due to the immense amount of data they have been trained on — about 150 trillion gigabytes from the internet. However, improving model performance continuously requires more data, and the quality of the data is crucial.

To address this, OpenAI has partnered with content providers like Reddit, while Elon Musk’s xAI leverages Twitter. These specialized data partnerships are essential and something we will see a lot more of going forward, yet they may not be sufficient alone.

Jason points to synthetic data as a potential solution.

The holy grail of all this is being able to generate your way out of the data problem.

Synthetic data involves generating new data through algorithms that mimic real-world data, overcoming privacy and access issues. This method not only augments existing datasets but also creates diverse, large-scale data for model training. While concerns about diminishing data quality persist, companies like Poolside, which generate substantial original data as their model runs different code executions, demonstrate the potential of synthetic data to unlock new advancements in AI, providing a scalable solution to the data bottleneck.

Foundation models to become cloud companies

As software collapses into the AI model layer and users increasingly come to model companies like Poolside with requests to create software, it opens the question of where will this software be hosted and run? Will the foundation models, who are soliciting the demand for new programs, be best placed to then run those programs for their users and take up the role of cloud providers as well as model companies?

Phase two is for us to be a cloud company, we’re going to run that software for you.

This evolution will likely involve partnerships with existing cloud providers, such as OpenAI and Microsoft Azure or Anthropic and Amazon AWS. This indicates an increasing integration of models and cloud services, pointing to a future where outcomes are requested and delivered end-to-end by a single provider.

This concept isn’t entirely new. We’ve seen it with open-source software like Elastic and MongoDB, where the software itself is open but the hosting, access, and execution are monetized. This business model aligns well with users’ willingness to pay for comprehensive solutions and outcomes.

The future is arriving fast, and with it, an exciting era of integrated AI and cloud services.

Onwards!