 is out and there are interesting results for AI tools and how developers feel about them. 65k devs were surveyed over 30 days from May to June 2024. It was a pleasant surprise to see that the average time spent responding to the survey was 21 minutes! Yes, it's a long survey but it also signals very high engagement, giving me a lot of confidence in the responses. 

Usage continues to increase, with a jump from 44% to 62% compared to 2023, still leaving a lot of room for adoption growth.

Sentiment has gone down though, compared to 2023 with a dip of 5% from 77% to 72%. 

The question was "How favorable is your stance on using AI tools as part of your development workflow?"

Those who responded "Indiferent" were quite high at 19%, indicating that 1/5 devs surveyed seem to be using AI tools due to a company or team mandate, rather than finding intrinsic value out of the tools.

The top 3 benefits of using AI tools were:

Increased productivity (81%) - Still, productivity continues to be a mythical concept that is 

, hinting that it is a subjective measure comparable to CSAT, which is good news with these high response markers.

Faster learning (62%) - Predictably, faster learning ranked higher for devs who identified themselves as students or in the process of learning how to code 

Greater efficiency (59%) - A topic for a further post, I would like to explore the differences between perceived productivity vs. efficiency in coding.

The accuracy of AI output continues to be questioned with only 43% of respondents feeling confident and 31% feeling skeptical.

Almost a third of respondents (27%) neither trust nor distrust accuracy, a huge opportunity for AI dev tool companies to capture!

The confidence in AI handling complex tasks is still very low with almost half of respondents (45%) believing they are not good enough. 

With 33% thinking AI is good but not great with complex tasks and 21% not sure if AI is good or bad, AI tools still have a long way to go in understanding complex environments, architectures, and setups.

Looking forward, devs want to see more of the following workflows supported by AI dev tools:

Probably the most interesting question, producing a lot of interesting theories:

This is a great source for identifying dev use cases by popularity, especially for CSM or dev advocate teams looking to help developers succeed and make the most out of AI dev tools. 

AI tools seem to be delivering good results and being highly used for the most important parts of dev workflows: 

"Writing code" - most likely with autocomplete.

"Search for answers" and "Debugging and getting help" - most likely using AI chat.

Surprises in low-ranked use cases, hinting a low confidence in the quality of the output: 

Seeing "Testing in code" ranking as the top workflow for devs who are not currently using AI, is aligned with my experience working as a director of Technical Advisory at Sourcegraph, enabling 

 for enterprise prospects. This was one of our most requested workflows for enablement and to support additional product features.

I'm surprised to see other workflows that ranked low for devs who are currently using AI dev tools such as "Committing and reviewing code", "Project planning", "Predictive analytics", and "Deployment and monitoring" ranked as high priorities for devs not using AI tools.

These are not currently supported in the most popular Code AI tools such as Copilot, IntelliCode, and Gemini.

Glad to see that most devs (68%) don't perceive AI tools as a threat. Interestingly, this number is much lower (58%) for devs who are learning to code. This hints that only devs who have hands-on trying the tools and are somewhat disappointed in the current quality and output, feel more reassured that AI is not a threat 

Misinformation or disinformation is the top concern for devs (79%), closely followed by incorrect attribution (64%) and biased results (50%). This confirms that most devs still feel like we're in the wild west of AI output and that it still can't be fully trusted.

This is reaffirmed by 66% of respondents saying they don't trust the output outright.

Context - Still a key piece in how success and quality of responses are perceived; 63% of respondents claim the AI dev tools lack context about their codebase, environments, architecture, and setups.

Lack of policies and training - About 1/3 of devs see this as a challenge to fully embrace AI dev tools.

Although the last question of the survey was grouped under ethics, Stack Overflow asked an open-ended question to devs in the form of "Please describe how you would expect your workflow to be different, if at all, in 1 year as a result of AI advancements". By grouping the most popular terms in the responses, it was interesting to see devs hoping for:

Seamless, Time - Hinting that devs hope for better DX/UX and helping them reclaim more time from tasks with heavy toil.

Well, code, Able code - Devs want to code well and better.

Complex task - They want the AI tools they use to get better at understanding complex tasks and environments. 

Well, integration - More AI tools are starting to get more integrated with other context sources besides code. Code reviews, wikis, docs, specs, etc will give more context to AI tools and will hopefully produce better results.

Mid-2024 AI dev tools temperature check

In all sales cycles, there is always a pre and post-sales phase regardless of how big or small the engagement is. In pre-sales, sales and tech partners will perform the initial tech scoping, requirement identification, and solution ideation that the post-sales delivery teams will build upon. This is why the transition of deals and projects from pre to post-sales is such a critical part of the customer journey to set the delivery for success. In my experience kicking off and onboarding dozens of customer projects, establishing a common set of expectations and duties that each team should follow during this critical stage has yielded amazing results. 

Recommendations to improve the pre to post-sales handoff

Define note templates for tech scoping and technical requirement identification calls for Solution/Sales Architects/Engineers with required and optional sections that ensure that individuals record critical information to be passed to the post-sales teams. 
This will reduce the time needed to digest and extract the most crucial bits of information gathered during pre-sales calls. The post-sales teams will know what to expect and where to find crucial info.

 template and make the Solution/Sales Architect/Engineer responsible for preparing this doc at least 14 days before the project is set to kickoff. This doc should cover information such as:

Customer stakeholder contacts involved so far in the customer journey and sales cycle.
Record their titles, and their role (budget owner, technical decision maker, product/project owner, legal/procurement, IC, etc) and place them in an org chart.

Customer business objectives for the project and success metrics. 
What is the customer trying to solve and how are we going to prove that we are solving it efficiently and delivering business impact? This is a good time to start drafting a value realization proposal.

Define a tentative kickoff date and propose what will be the main milestones for onboarding.

List the status of the contracts (NDA, MSA, SOW). What is done and what is pending?

Call out any foreseeable risks, impacts, and possible mitigation strategies.

Handoff call: Confirmation, alignment, and preparing kickoff

Have a synchronous call to review the pre-to-post sales handoff doc with the pre and post-sales teams. Define an owner for this call to schedule the call, invite the relevant internal partners, and run the call; this should be a delivery, engineering, solutions, consulting, customer success, or project manager.

Confirm the information recorded in the pre-to-post sales handoff doc to make sure it's updated with any recent progress in the sales cycle.

Align the pre and post-sales teams around the project priorities, goals, and objectives.

Arm the post-sales teams with all the available info gathered during pre-sales to have the best project kickoff and customer onboarding possible.

Bonus: Give the post-sales team a chance to challenge some of the assumptions defined during pre-sales. This is a great forum to polish the delivery proposal to better meet the customer's business objectives.

As the post-sales owner compiles all the necessary resources for doing a project kickoff call with the customer and defining the onboarding milestones, they can start sharing drafts and progress of the materials that will be used for the kickoff call with the pre-sales teams so they can provide feedback. This will make sure there is better alignment and the post-sales team is best prepared to kick off the project.

It's worth adding some metrics to measure how much the activities above are improving the customer journey and streamlining the sales cycle. Make sure you measure and establish a baseline before introducing any of the metrics and measure progressive improvements regularly.

Time to first contribution: Measure how fast the delivery teams can ship/commit their first contribution to the project to production or test environments.

Onboarding completion: See if the overall onboarding time decreases. Make sure to set clear and commonly agreed exit criteria with the customer.

Onboarding CSAT: Send satisfaction surveys to the customer no more than 14 days after onboarding has been completed.

Customer business objective fulfillment and value realization: See if the success metrics and value realization are realized faster.

Decrease in support tickets submitted: Better understanding and alignment of the customer's business objectives might decrease the number of support tickets and bug reports filed by the customer that are related to deviation from design, product, and feature specs.

Pre to post-sales handoff, a key moment in the customer journey

, I decided to start a new blog that I could deploy on a Vercel hobby account to practice some of the skills I learned while working there as a Manager of one of the CSM teams. I wanted to get started quickly, so I searched the available 

 to see my options. After considering a few blog templates with CMS integrations like WordPress and Prismic, I went with the 

 powered blog with native content editing and instant previews. 

A few thoughts about my experience with setting it up from scratch:

I had no previous experience with Sanity but I didn't need much to get going. Creating a free Sanity account first makes the project creation flow in Vercel much easier

The process of creating a new Vercel project (like starting your personal blog) by using a template is wonderful and easy for all levels of coders. The process boils down to:

Add the Vercel Sanity integration and create a new Sanity project

Let Vercel do the initial deployment and enjoy the 

 to set up your project locally and deploy it to production

Open your deployed URL to see your brand new blog and follow the "Next steps" suggested to access your 

 (the content creation backend) by adding a CORS origin URL from Vercel that can connect to the Sanity API

Create some content in your Sanity Studio

The Sanity integration for Vercel comes with a basic Sanity schema that allows me to set up the basic information for the blog like title, description, OG image, add myself as an Author and create posts 

The post schema is enough to get started, offering a title, post slug, content (that uses 

Publishing new content and content updates requires no new Vercel builds as long as you set up ISR but once you do, the content flows seamlessly in seconds

So this is it. I have a new blog up and running with Next.js + Vercel + Sanity.io and all in all, the process took me about 1 hour. There are a couple of improvements that I have in mind to make it feel more my own like:

Improve the post content presentation to my liking and support more content styles and decorators

Play with the Sanity schemas to add post categories or tags

I highly encourage anyone to go through this journey if you're interested in learning how to build a website with Next.js + Vercel. I could've well gone with an out-of-the-box solution like Medium, Substack, Tumblr, or even the good old WordPress but that would be no fun, right?

David Medina

Starting a new blog with Next.js + Vercel + Sanity.io

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