If you’re looking for data, both Github and StackOverflow released surveys this week covering this topic. You already know my stance if you’ve been reading my newsletter for awhile,

if you’re a dev tools co + not thinking about how AI can improve productivity of developers then you’ll be toast. Best implementations will have guardrails to leverage best of…

On to the surveys…

First up is Github which surveyed 500 U.S.-based developers at enterprise companies.

AI is here and it’s being used at scale. 92% of U.S.-based developers are already using AI coding tools both in and outside of work.

Waiting on builds and tests is still a problem. Despite industry-wide investments in DevOps, developers still say the most time-consuming thing they’re doing at work besides writing code is waiting on builds and tests.

Developers want more collaboration. Developers in enterprise settings work with an average of 21 other engineers on projects—and want collaboration to be a top metric in performance reviews.

And they think AI will help. More than 4 out of 5 developers expect AI coding tools will make their team more collaborative.

Developers also see big benefits to AI. 70% say AI coding tools will offer them an advantage at work and cite better code quality, completion time, and resolving incidents as some of the top anticipated benefits.

So if more AI is used, what will that allow developers to spend more time doing?

Here’s Stack Overflow’s data: 44% already use AI in developing now but Do Professional Coders Trust AI?

The reality is that developers are already using AI. 44% of them use AI tools in their development process now, and 26% plan to soon. Even more of those learning to code (55%) are currently using AI tools, and these early adopters will become established AI users once they settle into a professional developer position. 

While a growing number of developers are using AI tools, they aren’t using a wide variety. We asked developers which tools they were using, and out of the 21 options we listed this year, a vast majority are just using the two popular products: ChatGPT (83%) and GitHub Copilot (56%). Professional developers may need time to adjust existing workflows, and will most likely be motivated by their junior colleagues who are using AI tools while learning to code.

So right now we are talking about just code productivity but many are thinking beyond code to software architectures and that dirty old word AIOps which was tried before. Replit recently released its AI Manifesto with some ambitious goals.

At Replit, we are rethinking from the ground up the developer experience, with AI as a first-class citizen of the development environment. To this end, we have been working daily to build an ADI – Artificial Developer Intelligence. In time, the Replit ADI will create Agents capable of developing complex software architectures, both by generating code and by orchestrating advanced software tools developed and deployed on Replit. We have all the building blocks and the platform features in place to make this ecosystem thrive – for instance, Cycles (Replit’s platform credit system) will reward the creators of the tools orchestrated by the Replit ADI, while Bounties (Replit's creator marketplace) will engage developers in solving hard problems that our ADI still cannot tackle.

There is still a long way to go dealing with hallucinations, building trust, and ensuring accuracy, but the future is certainly bright, and I’m excited to meet the startups looking to make software development 10x better!

I reiterate:

if you’re a dev tools co + not thinking about how AI can improve productivity of developers then you’ll be toast. Best implementations will have guardrails to leverage best of…

As always, 🙏🏼 for reading and please share with your friends and colleagues.

Scaling Startups

1. In person or remote…so much debate on this as the pendulum is constantly swinging from the tech elite

   Agree with Jason Lemkin on this.

   My two cents - in person really is amazing in the early days where speed of product delivery matters, not saying it can’t be done remotely, but I’ve seen so many times startups move faster when together and iterating

2. 👇🏼 Must read - VCs overpromise but also what should founders really expect - this one is well done by my partner Ellen Chisa

   Ellen’s Newsletter

   Where your VC can't help

   VCs are notorious for saying “how can I help?” The last two weeks I've talked a bit about ways you help your VC help you - with customer introductions and with giving you useful input during meetings. There's plenty more a VC can do for you, but it's also important to recognize what a VC…

   Read more

   8 days ago · 8 likes · Ellen Chisa

Enterprise Tech

1. Must listen 🎙️ with two of my faves: What is MLSecOps? Ian Swanson, co-founder and CEO of Protect AI on The Secure Developer with Guy Podjarny, one of pioneers of DevSecOps and founder of Snyk (both Protect and Snyk are port cos). I encourage you to listen as Ian breaks down the five pillars of ML SecOps: supply chain vulnerabilities, model provenance, GRC (governance, risk, and compliance), trusted AI, and adversarial machine learning. We learn the key differences between software development and machine learning development lifecycles, and thus the difference between DevSecOps and ML SecOps…

   Ep 134. The Five Pillars of MLSecOps with Ian Swanson DevSecCon, Snyk Ltd, Guy Podjarny Episode

2. Google’s Secure AI Framework (blog post and Axios)

   Details: Google's Secure AI Framework pushes organizations to implement six ideas:

   *Assess what existing security controls can be easily extended to new AI systems, such as data encryption.

   *Expand existing threat intelligence research to also include specific threats targeting AI systems.

   *Adopt automation into the company's cyber defenses to quickly respond to any anomalous activity targeting AI systems.

   *Conduct regular reviews of the security measures in place around AI models.

   *Constantly test the security of these AI systems through so-called penetration tests and make changes based on those findings…

3. Interesting enterprise pricing model leveraging AI for support from Intercom - per chat - makes sense given how brutal seat-based SaaS models have been as of late

4. Sam wants to rule the world…licenses…

5. $105M Seed round for new AI LLM 🤯 (FT) - I still like a different kind of Phd - poor, hungry, determined but I do love the fact that there will be many more models, proprietary and OSS

   A French start-up founded four weeks ago by a trio of former Meta and Google artificial intelligence researchers has raised €105mn in Europe’s largest-ever seed round. Mistral AI’s first round of financing values the Paris-based concern at €240mn, including the funds raised, according to people close to the company.

   The record amount raised highlights the growing frenzy surrounding AI and Europe’s desire to create a viable alternative to Silicon Valley companies such as Microsoft-backed OpenAI and Google’s DeepMind.

6. Salesforce understands there is no real enterprise traction for AI/LLMs without better security (Bloomberg)

   Ahead of a Salesforce event focused on AI, the company is unveiling security standards for its technology, including preventing large language models from being trained on customer data.

   “Every client we talk to, this has been their biggest concern,” said Adam Caplan, senior vice president of AI, of the potential for confidential information to leak through the use of these models.

7. The companies that will really make 💰 in the AI boom - cloud providers and Nvidia

   Microsoft CFO Says OpenAI and Other AI Products Will Add $10 Billion in Revenue (from The Information)

   and Oracle on a comeback (Bloomberg)

   More than $2 billion in cloud capacity has recently been contracted by companies doing large language model development such as Mosaic ML, Adept AI and Cohere, Oracle Chairman Larry Ellison said in the statement. “Oracle’s Gen2 Cloud has quickly become the No. 1 choice for running Generative AI workloads,” he said. Separately, Oracle announced Tuesday morning that it plans to develop generative AI services in collaboration with Cohere.

8. Oh yeah, services to help build all of these AI apps and make them secure also = big 💰 as “Accenture to Invest $3 Billion in AI to Accelerate Clients’ Reinvention”

   *Expanded Data & AI practice to offer new industry solutions and pre-built models that will help companies across 19 industries drive value

   *Also launches AI Navigator for Enterprise platform to guide AI strategy, use cases, rigorous business cases, decision-making and responsible policies; and Center for Advanced AI to help maximize value of generative and other AI

   *Will double AI talent to 80,000 people through hiring, acquisitions and training

9. Pure gold for devtools founders from Ben Williams, formerly Snyk aka Ben Williams

10. Sapphire Ventures SaaS Buyers Outlook - mirrors exactly what we are seeing in the portfolio

    • Resilience at the core - majority of SaaS buyers say they plan to maintain or boost technology spending this year

    • A tale of two customer segments - large enterprises had much more resilient IT budgets compared to startups

    • A shift to value-focused spending - buyers across all segments demonstrating increased scrutiny on tool evaluations, underscoring the need for startups to show case ROI (see Anna Debenham (boldstart operating partner) post on selling value of Dev Tools in 2023

    • Pockets of budget growth largely driven by industry or company stage - CXOs who are increasing SaaS spending cited reasons driven by industry or company’s growth stage

    • The great hiring freeze - a vast majority of respondents planned to maintain or slightly reduce headcount

Markets

1. 🤯 Databricks at $1B revenue! (Bloomberg)

   Databricks Inc. said it generated $1 billion in annual revenue and has diversified its business with new products and tools for artificial intelligence.

   The closely held software maker, which in August effectively forecast the $1 billion goal, saw sales jump more than 60% in the fiscal year ended in January. Its data warehousing product, Databricks SQL, which competes with Snowflake Inc., passed $100 million in annualized recurring revenue in April, according to a spokesperson. Those figures haven’t previously been disclosed.

2. Sign of time for late stage investing - Insight Partners says great “reset in tech” is here as it cuts fund size from $20B to $15B (FT) and Tiger raises $2.7B, 77.5% less than initially targeted (The Information)