DEV Community: dev.to staff

18 Hot Takes On Where AI is Headed Next

dev.to staff — Thu, 02 Jul 2026 15:53:07 +0000

by Peter Yang, Behind the Craft

Today, I want to share 18 hot takes on where I think the AI market is headed.

AI is in a weird place right now. The government is restricting access to frontier models, enterprises are becoming conscious of token costs, and everyone’s trying to rebuild their product for agents first instead of humans.

I’ve interviewed dozens of AI leaders and spent far too much time following these topics on X/Twitter. Here are 18 hot takes on where I think AI is headed next:

The frontier-only AI stack is collapsing
The AI super app era is here
Traditional software risks becoming a dumb pipe for agents
Cloud agents and collaboration are the next wave

The Frontier-Only AI Stack Is Collapsing

Tokenmaxxing at frontier API prices makes no sense. Uber burned through its entire 2026 AI budget in 4 months, Microsoft moved engineers off Claude Code due to cost, and companies are realizing that running everything on frontier models can get expensive fast. Tokenmaxxing makes sense when you’re on a subsidized $200/month plan but is unsustainable at API rates.
Companies will rely on a portfolio of models. Coinbase recently cut its AI spend nearly in half by switching engineers to Chinese open-source models like GLM and Kimi. Airbnb and Pinterest have done the same with Alibaba’s Qwen models. I believe that this will be the default path forward — using frontier for high-stakes work and cheaper models for everything else.
China’s open-source strategy is working. Chinese models are taking market share from frontier models at US companies. China is also building the full AI stack — from energy (e.g., solar, nuclear) to data centers to domestic chips. The Chinese government is planning a $295B investment in AI data centers with at least 80% of the chips built domestically.
Frontier labs are in a catch-22 situation. If they release great open-source models, they might undercut their own frontier API revenue. If they gate the best models behind a trusted list, companies will just lean on open alternatives more. The last major US open-source model was OpenAI’s gpt-oss series back in August 2025, which already feels like decades ago in the AI space.
The US needs to think about its AI strategy holistically. I believe that restricting access to frontier models will only hurt American innovation. Banning US companies from Chinese models won’t work either. Just look at how China took over the global electric vehicle market. To compete, we need the best closed and open models while scaling our energy grid and data centers much faster.

The AI Super App Era Is Here

Anthropic and OpenAI want to transform all knowledge work. Both labs want to remake how white-collar work gets done with agents. What started with coding has expanded to design, finance, legal, science, and more. Knowledge workers are now adopting Codex three times faster than developers.
The race to build the best AI super app is on. Whoever wins it will take massive market share away from pre-AI knowledge work tools. The main players are Codex, Claude, Cursor, and a few others. With browser and computer use, I can already get Codex to handle almost everything I want to do on my computer.
OpenAI is well positioned to win the super app race. ChatGPT has 800M+ weekly active users and Codex is arguably the best AI super app right now. OpenAI has a clear opportunity to merge ChatGPT and Codex into one app and push agents into the mainstream. I think this is imminent.
Anthropic leads enterprise but has a fragmented product suite. Long term, I don’t think it makes sense for Claude, Cowork, Claude Code, and Claude Design to all exist as separate products. Working with Claude needs to feel more like working with a single capable coworker instead of a product suite. Claude Tag, Anthropic’s new agent for Slack, is a step in the right direction.

Software Risks Becoming A Dumb Pipe For Agents

Agents are becoming the default user. Most products are still designed for humans clicking buttons, but agents will very soon read, write, buy, and do a lot more on our behalf. Cloudflare’s data shows that bot traffic to websites already exceeds human traffic. This matches my personal experience — I rely on agents like Hermes and Codex to browse websites and steer traditional apps.
If your product isn’t built for agents, it might as well not exist. Without clear APIs, documentation, and CLIs or MCPs, agents simply won’t discover your product, and neither will the humans who now lean on agents to find things. That’s why the best AI builders I’ve interviewed are all building for agents first.
Existing knowledge work products risk becoming dumb pipes. There’s a dark side to building everything for agents first. Take Google Workspace, for example. If I can just use Codex to edit Google Docs for me, I might never touch the Google Docs interface. Today’s apps risk becoming tomorrow’s dumb pipes for agents, the same way cable became the dumb pipe for internet apps.
Adding an AI chatbot to your product isn’t going to save you. A chatbot trapped inside a single app, with only that app’s context, can’t compete with an agent like Hermes or Codex that carries my personal context and gets work done across many apps. For example, I get a daily morning brief from Hermes that pulls info from my calendar, unread emails, and Slack.
Pure-play SaaS is losing to services with SaaS bolted on. Companies don’t want another SaaS tool to onboard to and maintain. Instead, they want an outcome delivered to them. Pure-play SaaS will struggle to compete with AI skills that users and teams can build and personalize inside their favorite AI super app.

Cloud Agents And Collaboration Are The Next Wave

Startups can compete with AI labs by going deep and using a portfolio of models. For example, coding startups like Devin and Factory are doing well because their harnesses route across multiple models to help customers save on cost without giving up performance. They’re also focused on a few specific use cases instead of trying to be everything to everyone.
Always-on cloud agents will be accessible from any device. Running agents with your laptop half-open will feel silly soon. Instead, many builders are already launching cloud agents using Cursor, Devin, and others. Codex and Claude Code are no doubt working on the same experience, and this will be the default soon.
Collaboration between agents and teams has yet to be figured out. The default agent harness with a list of threads on the left is still very much a single-player experience. The multiplayer experience is still being defined — whether that’s Claude Tag in Slack, agents in Linear, or something else.
“The future isn’t 20 terminal tabs. It’s better loops.” I watched Peter Steinberger share this in his keynote at yesterday’s AI Engineer conference. He no longer watches the agents code. Instead, he defines the requirements, and let agents plan, execute, and validate by themselves. I’m a bit wary of loops since they can lead to AI slop, but I’m sure better planning and models will make them more mainstream.

The AI Market Is About To Get A Lot More Interesting

Here are my 18 takes summarized in four bullets:

The frontier-only AI stack is collapsing. Companies will use a portfolio of models to save costs, with everyday tasks defaulting to low-cost open models from China.
The AI super app era is here. Codex, Claude, Cursor, and others are competing to disrupt knowledge work by using agents for everything you can do on a computer.
Traditional software risks becoming a dumb pipe. Agents will become the default user. They’ll use APIs and browser use to access your website and app without humans ever seeing them.
Cloud agents and collaboration are the next wave. The future is agents living in the cloud, accessible from any device, and collaborating closely with both you and your team. This will happen very soon.

Let me know what you think about these takes in the comments!

How Docusign is Bringing Contract Table Extraction to Production with NVIDIA Nemotron Parse

dev.to staff — Thu, 02 Jul 2026 15:34:59 +0000

By Hiral Shah, Senior Director, Product Management, Docusign

A major recurring theme among the engineering teams at this week’s AI Engineer World’s Fair in San Francisco is the push to move specialized AI models out of research and directly into high-volume production.

At Docusign, that optimization challenge happens at massive scale: we handle millions of transactions daily and have nearly 1.9 million customers in over 180 countries. Organizations have historically lost significant value every year to the friction, delays, and missed obligations that come from treating these agreements as static documents rather than live sources of business data.

Much of that trapped value sits inside tables: the pricing schedules, SLA obligations, and contractor rate cards that define enterprise relationships but are often the hardest part of a contract to extract accurately.

To solve this, we integrated NVIDIA Nemotron Parse, a vision-language model purpose-built for document understanding, directly into our document processing pipeline.

Docusign and NVIDIA took the AI Engineer World’s Fair stage this week to give attendees a look at how the architecture works under the hood. Here’s what that looks like:

Why Contract Tables Break General-Purpose AI

Contracts routinely contain merged cells, multi-page structures, mixed formatting, and nested layouts that general-purpose vision language models (VLMs) and broad AI models weren't designed to handle. The result is inaccurate extractions that require manual correction, slowing down the workflows they are intended to accelerate.

Our teams watch this operational friction play out across real enterprise scenarios every day:

System Downtime: When a critical system goes down, operations teams need to know immediately which SLA notification requirements apply and to whom.
Resource Tracking: When business stakeholders ask legal what hourly rate was agreed to in a contractor engagement, the answer is often buried deep inside a rate card table.
Vendor Renewals: When procurement teams manage a complex vendor renewal, pricing structures scattered across multiple exhibits require significant manual review to piece together.

The Production Pipeline: From Layout To Structured Data

Docusign's document understanding pipeline processes agreements at scale, handling layout detection and Optical Character Recognition (OCR) across millions of documents. Adding reliable table extraction required a dedicated model layer that can handle the structural complexity those earlier stages couldn't fully resolve.

At the core of this integration is NVIDIA Nemotron Parse, a compact vision-language model that combines layout detection, OCR, and document semantics to interpret and reconstruct complex tables accurately.

For production deployment, the model infrastructure centers on two core requirements:

Serving with vLLM: Nemotron Parse is served via vLLM and integrated directly into Docusign's existing layout and OCR pipeline.
Data Governance & Locality: Sensitive agreement data stays entirely within Docusign's secure environment. Keeping documents local is a hard requirement when handling confidential business terms, while giving our engineering teams the flexibility to run and optimize the model for our specific use case.

Moving Beyond Synthetic Benchmarks

To properly validate this integration, we skipped clean, synthetic benchmarks, which fail to capture the formatting variations, inconsistent structures, and mixed-language content that enterprise contracts actually contain. Instead, we tested the architecture against real, complex enterprise contracts.

The accuracy and reliability of this production deployment gave NVIDIA the confidence to deploy Docusign IAM to manage its own enterprise agreements.

What’s Next On The Roadmap

The work doesn't stop here. Our engineering teams are continuing to improve model accuracy on more complex and varied table structures. We are also actively exploring deeper integrations with agentic workflows through the NVIDIA Agent Toolkit, and a public API for direct integration with downstream developer systems is coming soon.

Table extraction powered by Nemotron Parse is currently accepting beta customers for extractions in Agreement Manager, with full general availability on the horizon.

If you're building document intelligence pipelines or moving VLMs into production, how are your teams tackling structural layout variations? Let's swap notes in the comments!

Your Agents Should Be Multiplayer

dev.to staff — Thu, 02 Jul 2026 15:32:03 +0000

by Sergey Karayev, cofounder @ Superconductor

Recently, my wife and I sat down to plan an upcoming trip. Naturally, we each asked an AI. Trouble was, I had my chat and she had hers, and they knew nothing about each other. So we served as couriers between chatbots: her idea pasted into my chat, my hotel booking screenshotted into hers, the itinerary reconciled by hand in a Google Doc.

I bring this up because your team probably works the same unfortunate way: each person in their own chat or coding agent session, with precious little shared.

I've been building software with the same set of people for over a decade. In the past year, we all got a superpower: coding agents that can do extremely impressive things. But each one (Claude Code, Codex, Cursor, etc.) was built for a single player. That's fine and dandy if you're vibe-coding your own little app. It's just you and Claude, and it's absolutely magical.

But put that same agent on a team and the magic fades quite a bit. The model is no longer the bottleneck. Coordination is. You don't know who's working on what. You can't see that an agent already tried the approach you're about to attempt, and abandoned it. You spend an hour re-deriving context that a teammate has, because it's trapped in their private chat.

Now let me tell you of a better way. On the Superconductor team, every coding agent session is in the cloud, open to anyone else on the team to join. What this enabled was transformative.

Code review improved first. My teammate reviews my work by joining the session I built it in. The session holds the full history of decisions, including the dead ends. Instead of Slacking me "why'd you name it this way?" she asks the agent. She gets her answer, and I never waste time answering. She also doesn't have to check out the branch locally — the live app preview in the cloud sandbox does the job.

Handoffs became easy. If I have to pass a feature to a teammate, he picks it up with full context: what's done, what's left, what the agent already tried. Nothing is trapped on my laptop, and the ball keeps rolling. And since agents don't sleep, a team spread across time zones can push forward around the clock. The old "shift" model of work might be making sense again.

Perhaps most importantly, we are continually learning best practices from each other. Every knowledge worker is facing the same question right now ("what's the best way to use these things?") and mostly figuring it out alone. Your teammates are quickly going to teach you more than any blog post.

And the utility of multiplayer AI goes beyond code. We now have an agent sitting in all of our team and customer meetings, reading the live transcript and taking actions while we talk. Another agent regularly checks on our progress against our stated goals and messages people as needed for clarifications.

My bet is that the agentic company of the future runs on shared cloud sessions. More like Slack threads, less like terminal sessions. The teams that pull ahead will place their agents where everyone can collaborate with them, instead of handing each person a genie with a lamp to hide it in.

My co-founder Arjun expands on the theme in his talk on "multiplayer agentic engineering: how to have your whole team and your best agents work together." Come by today (Thursday, July 2) at 1:55 p.m., Room 2020 — we'd love to hear what you think.

Fable is Back, Baby.

dev.to staff — Wed, 01 Jul 2026 14:53:47 +0000

Fable is back. The Commerce Department announced yesterday it has lifted the export controls it slapped on Anthropic's newest model, and access returns this week. However, nobody's spelled out the fine print yet. Early reports point to credit gating and ID checks.

The reprieve isn't the story, though — the speed is. A frontier model vanished from every cloud on an unexpected government order. Washington leaned on OpenAI days earlier, too, pushing it to limit its flagship to vetted partners. That's not a one-off. U.S. policy on AI tools is shifting fast.

Here's the takeaway for builders. The whims of the federal government now outrank any lab's roadmap, and one letter from Commerce proved it. Stop counting on a steady drip of bigger, better models. The open-weight models nobody can revoke start looking a lot more strategic. Power could be drifting away from the big U.S. labs.

So we wait with bated breath for Fable to come back — and our productivity right along with it.

Winner Announcement Delayed for the Github "Finish-Up-A-Thon" Challenge

dev.to staff — Thu, 25 Jun 2026 18:52:00 +0000

Hey all, we have a quick update for everyone who participated in the Github "Finish-Up-A-Thon" Challenge.

As we've already stated, we were blown away by the volume of submissions we received for this challenge. We still need a bit more time to carefully review everything and make our final decisions.

We'll be back with the winner announcement next week. Thank you so much for your patience, and for putting so much effort into your builds.

In the meantime, check out all the amazing submissions by browsing #githubchallenge:

#githubchallenge Follow

This is the official tag for submissions and announcements related to GitHub Copilot Challenges.

Watch Google Cloud NEXT Live Right Here on DEV!

dev.to staff — Mon, 20 Apr 2026 16:50:30 +0000

Big things are happening at Google Cloud NEXT, and you don't have to go anywhere to catch the action. We're simulcasting the keynotes and various additional developer livestreams throughout the day on April 22 & 23 directly on the DEV homepage so you can tune in with the community.

Here's what's on the schedule:

📺 April 22 at 9:00 AM PT: Opening Keynote & Livestreams

Kick off Google Cloud NEXT with the opening keynote, streaming live on the DEV homepage. Expect big announcements, product reveals, and a look at where Google Cloud is headed.

Join the livestream immediately after for a breakdown of the announcements and get hands-on keyboard with Google product leaders, customers, and GDEs.

🔔 Get Notified on YouTube

👩‍💻 April 23 at 10:30 AM PT: Developer Keynote & Livestreams

This one's for us. The Developer Keynote will show you some of the latest advancements in AI and cloud tech.

Immediately after, stay for live-coding agentic workflows and testing new announcements in real-world scenarios with Google product leaders, customers, and GDEs.

🔔 Get Notified on YouTube

In addition to the keynotes, we'll be streaming developer sessions all throughout the day PT during April 22 & 23, so keep an eye on the DEV homepage across the full run of Google Cloud NEXT!

🎯 Something Exciting Is Coming...

We'll also be launching a special challenge in conjunction with Google Cloud NEXT very soon.

So set a reminder, tell your friends, and come hang out on DEV while we watch the future of cloud development unfold together. You're not going to want to miss it. 🙌

What are you most excited to see announced at Google Cloud NEXT? Drop it in the comments!

Congrats to the Winners of the Auth0 for AI Agents Challenge!

dev.to staff — Thu, 06 Nov 2025 23:16:49 +0000

It's that time! We are excited to announce the winners of the Auth0 for AI Agents Challenge:

We were thrilled to see how the community leveraged Auth0 to ship AI agents with built-in auth and security. From anti-piracy platforms to medical apps to legal hubs, we were impressed by the various use cases submitted that demonstrated the importance of prioritizing security, user control, and transparency as it relates to authentication and authorization. These submissions showcased that the future of AI agents is not just intelligent, it's secure.

We hope you enjoyed working on your submission and are proud of what you accomplished, regardless of whether or not you received the crown.

Without further ado, our winners.

Congratulations To…

ESG Copilot

@omkar598 built an autonomous multi-agent AI system that automates ESG compliance for small and medium businesses, showcasing the full power of Auth0's security stack.

Auth0 for AI Agents Challenge Submission

omkar

Oct 27 '25

From $50K Reports to AI Automation: Securing Multi-Agent ESG Compliance with Auth0

#devchallenge #auth0challenge #ai #authentication

8 min read

ESG Copilot implements Auth0 Universal Login for user authentication, Token Vault for securing API keys (Climatiq, SendGrid, Pinecone), and OpenFGA for fine-grained authorization ensuring zero data leakage between companies.

Assistant0

@async_dime delivered an secure eneterprise-grade AI assistant that seamlessly manages Gmail, Google Calendar, web search, and document access all secured through Auth0's comprehensive security features.

Auth0 for AI Agents Challenge Submission

Adam

Oct 27 '25

Assistant0 - Secure AI Personal Assistant

#devchallenge #auth0challenge #ai #authentication

6 min read

Assistant0 stands out for its sophisticated implementation of Client-Initiated Backchannel Authentication (CIBA) for high-risk operations, requiring explicit user approval before actions like purchases or sending emails, utilization of TokenVault, and FGA with Okta.

Study-Flow

@prime_299792 took an hybrid authentication approach by integrating Auth0 Token Vault into an existing study management platform while maintaining their original Convex Auth system.

Auth0 for AI Agents Challenge Submission

Anshu Mandal

Oct 27 '25

Study-Flow: Auth0 for AI Agents: The Missing Piece My Study App Was Begging For

#devchallenge #auth0challenge #ai #authentication

21 min read

This approach highlights versatility of Auth0 for AI Agents as well as the benefit of utilizing Token Vault over manual token management.

Our three winners will each receive $1,000 USD, an exclusive DEV badge, and a DEV++ Membership. All participants with valid submissions will receive a completion badge for rising to the challenge!

Our Sponsor

A huge thank you to Auth0 for sponsoring this challenge! It's obvious that Auth0 is at the forefront of providing tools to build secure AI Agents and we are grateful the community had an opportunity to build with Auth0's authentication and authorization features.

What's next?

We always have challenges going on! Follow the tag so you don't miss out:

#devchallenge Follow

This is the official tag for submissions and announcements related to DEV Challenges.

We hope you had fun, felt challenged, and maybe added a thing or two to your professional profile.

See you next time!

Interested in being a volunteer judge for future challenges? Learn more here!

Auth0 for AI Agents Challenge: Deadline Extended by 1-Week!

dev.to staff — Fri, 17 Oct 2025 16:26:42 +0000

You've got more time to secure your AI agents!

We're extending the deadline for the Auth0 for AI Agents Challenge to give everyone extra room to work on their intelligent agent projects. We've heard from participants that they're building some really innovative solutions and want to ensure the community has the time needed to bring their secure AI applications to life.

The new deadline is Sunday, October 26 at 11:59 PM PDT.

That's one more week to build, test, and deploy your AI agents using Auth0's authentication and security features.

A few friendly reminders:

🤖 Your project must leverage Auth0 for AI Agents to qualify
💰 There's a $3,000 prize pool up for grabs
🏆 Winners will be featured on DEV and receive exclusive badges
✅ All participants with valid submissions will receive a completion badge

If you haven't joined in yet, now's the perfect time to start building your secure AI agent!

Jess Lee for The DEV Team

Oct 8 '25

Join the Auth0 for AI Agents Challenge: $3,000 in Prizes!

#devchallenge #auth0challenge #security #ai

3 min read

Good luck and happy coding!

Congrats to the Heroku "Back to School" AI Challenge Winners!

dev.to staff — Mon, 13 Oct 2025 14:28:12 +0000

Thank you to everyone for being patient, the wait is over! We are excited to announce the winners of the Heroku "Back to School" AI Challenge.

Students who participated in this challenge built AI-powered applications that sought to make the back-to-school transition smoother, smarter, and more successful. Each submission showcased thoughtful applications of Heroku's AI features, demonstrating creative approaches to solving real educational problems. We appreciate the dedication and technical sophistication demonstrated by all participants.

We hope every participant is proud of what they accomplished and gained valuable experience working with Heroku AI features, regardless of whether they're taking home a prize today.

Without further ado, our winners.

Congratulations To…

Crazy Creative Winner

@prime_299792 delivered a comprehensive AI-powered study management platform that goes far beyond traditional study tools.

Anshu Mandal

Sep 29 '25

Study-Mate: AI Powered Study Success Platform.

#devchallenge #herokuchallenge #webdev #ai

9 min read

What sets Study-Mate apart is its implementation of MentorMind, an AI assistant that leverages a multi-agent architecture with intelligent orchestration between GPT-OSS, Nova Lite, and Claude agents.

Educator Empowerment Winner

@victor_lakra_e1910abe17fc built a practical solution addressing a time-consuming challenge that educators face daily: lesson planning. Teacher Assistant transforms the lesson planning process by enabling teachers to upload teaching materials and receive comprehensive, context-aware lesson plans in minutes.

VICTOR LAKRA

Sep 28 '25

AI-Powered Teacher Assistant: Revolutionizing Lesson Planning for Educators

#devchallenge #herokuchallenge #webdev #ai

3 min read

The application leverages Heroku Managed Inference with Cohere embeddings and Claude Sonnet 4, combined with pgvector-enabled Postgres for semantic search capabilities.

Student Success Winner

@juliodiaz0209 created a powerful multi-agent learning platform that demonstrates the future of AI-powered education. StudyFlow AI coordinates seven specialized AI agents working seamlessly together to provide personalized learning experiences across multiple dimensions of student success.

Jules

Sep 29 '25

StudyFlow AI

#devchallenge #herokuchallenge #webdev #ai

2 min read

The integration of Heroku's Model Context Protocol for real-time agent communication, pgvector for context storage, and Managed Inference creates a truly adaptive learning experience that adjusts to individual student needs.

Each winner will receive $1,000 USD, a DEV++ Membership, and an exclusive DEV badge. All eligible student participants will receive a completion badge for rising to the challenge!

Sponsor Shoutout

A huge thank you to Heroku for sponsoring this challenge and providing students with the opportunity to build with cutting-edge AI features. Heroku's AI PaaS platform featuring Model Context Protocol (MCP), Managed Inference and Agents, and pgvector for Postgres enabled participants to create sophisticated multi-agent applications without getting bogged down in infrastructure complexity!

What's next?

Stay tuned for upcoming DEV Challenges! Follow our challenges page to be the first to know when new opportunities launch:

#devchallenge Follow

This is the official tag for submissions and announcements related to DEV Challenges.

We hope you had fun, felt challenged, and maybe added an impressive project to your professional profile.

See you next time!

Interested in being a volunteer judge for future challenges? Learn more here!

Join the Heroku "Back to School" AI Challenge: $3,000 in Prizes, just for students!

dev.to staff — Wed, 27 Aug 2025 17:01:43 +0000

Winners Announced

dev.to staff for The DEV Team

Oct 13 '25

Congrats to the Heroku "Back to School" AI Challenge Winners!

#devchallenge #herokuchallenge #heroku #ai

2 min read

UPDATE 10/09/25: Winner announcement is delayed.

We are so delighted to partner with Heroku for a new DEV challenge designed exclusively for students.

Running through September 28, the Heroku "Back to School" AI Challenge is all about building intelligent AI-powered experiences that make the back-to-school transition smoother, smarter, and more successful. We have one overarching prompt with three exciting ways to win!

From coordinating multi-agent workflows to leveraging cutting-edge MCP servers, this challenge invites student developers to showcase their skills with Heroku's powerful AI platform. Build something that helps fellow students, empowers educators, or gets wildly creative with back-to-school experiences!

Our Prompt

For this challenge, your mandate is to build an AI-Powered Back to School Experience. Create a multi-agent AI application that helps with any aspect of the back-to-school experience.

Your application should incorporate one or more of the following Heroku AI features:

Model Context Protocol (MCP) on Heroku
Heroku Managed Inference and Agents
pgvector for Heroku Postgres

👉 Additionally, your submission should fall under one of these categories:

Student Success: Awarded to a top submission that directly supports student learning, organization, or academic achievement.
Educator Empowerment: Awarded to a top submission with tools that help teachers, professors, or administrators be more effective.
Crazy Creative: Awarded to a top submission with the most creative or unexpected use of AI for back-to-school needs.

Think study planning assistants, classroom optimization tools, campus navigation systems, academic collaboration platforms, or anything else that makes returning to school better. The possibilities are endless!

Submitting Your Project

When you're ready to submit your project, you will need to publish a post using this submission template:

Heroku Back to School Submission Template

If your submission qualifies for multiple categories, just publish one post and list all the categories it qualifies for.

Please review our judging criteria, rules, guidelines, and FAQ page before submitting so you understand our participation guidelines and official contest rules.

Important Note: This challenge has additional eligibility requirements listed below so be sure to check if you're eligible before participating.

Prizes

We'll select one winner per category for a total of three winners. Each winner will receive:

$1,000 USD each
DEV++ Membership
Exclusive DEV Badge

All Student Participants with a valid submission will receive a completion badge on their DEV profile.

How To Participate

In order to participate, you will need to enroll in the GitHub Student Developer Pack, sign up for the Heroku for GitHub Students Offer, and be a resident from one of the countries or territories listed below.

Github Student Developer Pack Enrollment

Enroll in the Github Student Developer Pack (if you haven’t yet)
Click the Heroku offer.
Sign up for a Heroku account, or log into your account if you already have one.
Apply for the "Heroku for Github" student offer

Once these steps have been completed, your credits will be added to your Heroku account within 1-2- hours.

Additional Notes

Credits will be applied toward any Heroku products, including Heroku Dynos, Heroku Postgres and Heroku Key-Value Store, except for third-party Heroku Add-ons
The offer is $13/mo credit for 2 years for a total of $312 credits. Credits won't carry over month to month, so it's use it or lose it.
All students are required to add a valid payment method as part of the application process to cover third party total usage that the credits don't cover.
See the Heroku for GitHub Students page for more information about the program.

Eligibility Requirements

Geographic Eligibility: This challenge is open to residents of the following countries and territories: 50 United States (including the District of Columbia), Argentina, Australia, Belgium, Canada (excluding Quebec), Croatia, Cyprus, France, Germany, Hungary, India, Ireland, Japan, Latvia, Luxembourg, Morocco, Netherlands, New Zealand, Norway, Philippines, Singapore, Spain, South Africa, Ukraine, and United Kingdom.
Student Status: All participants must be currently enrolled students with active access to the GitHub Student Developer Pack. Please refer to the registration instructions above for how to get access to the GitHub Student Developer Pack.

If you do not meet these eligibility criteria, we encourage you to explore our other available challenges!

Need Help?

Get started with Heroku AI by exploring their comprehensive documentation and resources.

We recommend using Cursor IDE for development, which offers excellent MCP support and AI-powered coding assistance.

Important Dates

August 27: Heroku "Back to School" AI Challenge begins!
September 28: Submissions due at 11:59 PM PDT
October 10: Winners Announced

We can't wait to see how you leverage AI to enhance the back-to-school experience! Questions about the challenge? Ask them below.

Good luck and happy coding!

DEV Community: dev.to staff

18 Hot Takes On Where AI is Headed Next

The Frontier-Only AI Stack Is Collapsing

The AI Super App Era Is Here

Software Risks Becoming A Dumb Pipe For Agents

Cloud Agents And Collaboration Are The Next Wave

The AI Market Is About To Get A Lot More Interesting

How Docusign is Bringing Contract Table Extraction to Production with NVIDIA Nemotron Parse

Why Contract Tables Break General-Purpose AI

The Production Pipeline: From Layout To Structured Data

Moving Beyond Synthetic Benchmarks

What’s Next On The Roadmap

Your Agents Should Be Multiplayer

Fable is Back, Baby.

Winner Announcement Delayed for the Github "Finish-Up-A-Thon" Challenge

#githubchallenge Follow

Watch Google Cloud NEXT Live Right Here on DEV!

📺 April 22 at 9:00 AM PT: Opening Keynote & Livestreams

👩‍💻 April 23 at 10:30 AM PT: Developer Keynote & Livestreams

🎯 Something Exciting Is Coming...

Congrats to the Winners of the Auth0 for AI Agents Challenge!

Congratulations To…

ESG Copilot

Assistant0

Study-Flow

Our Sponsor

What's next?

#devchallenge Follow

Auth0 for AI Agents Challenge: Deadline Extended by 1-Week!

Congrats to the Heroku "Back to School" AI Challenge Winners!

Congratulations To…

Crazy Creative Winner

Educator Empowerment Winner

Student Success Winner

Sponsor Shoutout

What's next?

#devchallenge Follow

Top 7 Featured DEV Posts of the Week

Top 7 Featured DEV Posts of the Week

Join the Heroku "Back to School" AI Challenge: $3,000 in Prizes, just for students!

Winners Announced

Our Prompt

Submitting Your Project

Prizes

How To Participate

Github Student Developer Pack Enrollment

Eligibility Requirements

Need Help?

Important Dates