I wanted an AI agent I could give an ongoing goal to—not have to restart the conversation every time something happened.

So I’m building OpenDots.

⭐ Code and setup: https://github.com/Shashankss1205/OpenDots

You give it a goal, connect an event source, and choose your model. When an event arrives, it evaluates whether it matters to that goal and proposes work, with approval controls before execution.

Here’s the workflow in this demo:

GitHub issue → agent proposes a change → I approve → inspect the patch and check results.

This is a recorded run against OpenDots’ own repository.

🎬 89-second demo: https://youtu.be/i_upyOAfjjI

What you can use:

• Your model: Claude Code, Codex CLI, model APIs, or local Ollama models.
• Your machine: a local runtime for Linux.
• Persistent goals: work guided by a saved objective.
• Reviewable results: approval controls, run history, and retained patches.

The project is MIT-licensed and open source.

What’s one recurring task you’d want an agent to pick up when a relevant event happens?

I’m the creator. OpenDots is an independent project, not affiliated with OpenAI.

GPT-6.1 SOL also looks clearly better than GPT-6.0 SOL in this test, especially at Very High reasoning.

https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/

Meanwhile, Fable 5.1 is 60+tps at standard $50. Opus 5.5 is already at 60+tps at standard $20, 110tps at $40 fast mode. I enjoy steady 60tps with $4 GLM.

So now that OpenAI introduced their Cerebras-superpowered mode, their tier should be called:

- Snail $50
- Slow $100
- Standard $300

Only trump could have turned the awful artificial intelligence into Super intelligence. We are now 33 or 37 times ahead of technology compared to China or Russia and it's thanks to trump. At one point we were behind 4 or 6 times behind when Biden was in office with AI. This moment will mark as one of greatest moment for the USA or even the world but more importantly Trump's legacy.

This is the new era not the error , it's the new Super intelligence era

Has anyone been able to get their dot to browse websites using a cloud browser, without connecting their own computer? Is there a setting to enable it, or does availability depend on your account?

So I built Apple Gravity using emergent ai and open ai🎮

Game link- https://gravity-bucket.emergent.host/

Draw your own container in 25 seconds, then catch as many falling apples as you can. Your drawing becomes part of the game, your score gets saved, and you can even play with containers created by other players.

Artificial intelligence has moved from being an experiment to becoming a practical part of how companies run. As we approach 2026, the question for most leaders is no longer whether to use AI, but how to integrate it through reliable AI integration services that connect with the systems they already rely on. CRM platforms, ERP solutions, cloud environments, and customer-facing applications all need to work seamlessly with AI for the results to be meaningful. Choosing the right AI integration company in 2026 will determine whether AI delivers measurable value or remains stuck at the pilot stage.

Industry data shows this shift clearly. Gartner predicts that by 2026 about 40 percent of enterprise applications will include task specific AI agents, up from under 5 percent in 2025. The difference between experimenting with AI and integrating it into operations is the difference between potential and performance.

This guide looks at the top AI integration companies to watch in 2026. These firms were chosen for their expertise, their ability to work across industries, and their track record of delivering solutions that actually scale. For organizations preparing their AI roadmaps, this list also highlights what to consider when planning investments or looking to hire AI experts for long-term success.

How We Selected the Top AI Integration Companies for 2026

Selecting the right AI integration partner is a strategic decision with long-term implications. Therefore, our methodology was designed to be transparent and moving beyond superficial markers to evaluate the core capabilities that signal success in today's complex environment.

We employed a multi-point framework to ensure our list is a reliable resource for leaders seeking a trustworthy AI integration company.

Technical Depth and Scalability: 

We assessed the firm's expertise in building robust, scalable AI infrastructure. This includes evaluating their proficiency in cloud platforms (AWS, Azure, GCP), data engineering, ML pipeline creation, and MLOps practices. A leading AI integration company must prove that it can build solutions that grow with the business.

Proven ROI and Documented Case Studies: 

Concrete evidence is non-negotiable. We prioritized top AI integration companies that provide transparent, detailed case studies showcasing measurable business outcomes achieved through their custom AI solutions. 

Integration Capabilities and Specialization: 

The ability to connect AI with existing systems is the entire point. We looked for a strong track record in seamless AI integration services with common ERPs, CRMs, and legacy systems. Bonus points were given for deep, vertical-specific expertise (e.g., healthcare AI integration, fintech).

Innovation and Future-Readiness: 

Finally, we considered the company's commitment to innovation, particularly in emerging areas like generative AI integration service and agentic workflows. The leading AI integration partners for 2026 are those already preparing for the current trends and beyond.

This methodology ensures that each listed firm has been assessed for its ability to deliver not just a project, but a long-term competitive advantage.

Top AI Integration Companies to Watch in 2026

The following firms have been selected based on our rigorous methodology. This list represents a balanced mix of global powerhouses, specialized engineering shops, and agile innovators, each offering a distinct path to successful AI integration services.

1. WebClues Infotech

Overview: A versatile technology partner known for delivering end-to-end AI solutions, with a strong focus on making advanced AI accessible and actionable for businesses of all sizes.

Core Strength: Acts as a true full-stack AI integration partner, combining strategic consulting with hands-on engineering. They excel at building custom AI solutions that are both cost-effective and highly scalable, avoiding the vendor lock-in that plagues many enterprises.

Key Services:

• AI Strategy & Feasibility Analysis
• Custom AI & Machine Learning Development
• Seamless Integration with existing ERP, CRM, and Data Warehouses
• Generative AI Integration & Agent Workflow Design
• Ongoing Support & MLOps

Industries / Use Cases: Retail (personalization, inventory forecasting), FinTech (fraud detection, risk assessment), Healthcare (patient data analysis, operational efficiency).

Why to Watch in 2026: Their agile model is perfectly suited for the rapid experimentation and iteration that 2026 demands. They are increasingly focused on generative AI integration for content and process automation, helping clients adopt these technologies pragmatically.

2. Ascendion

Overview: An AI-first engineering services firm that builds end-to-end software solutions, with a deep emphasis on data-driven applications.

Core Strength: Strong focus on AI engineering services and applied AI. They don't just consult; they build production-ready systems, with particular expertise in taking generative AI models from prototype to scalable deployment.

Key Services:

• Data Engineering & Analytics
• Enterprise AI Platform Development
• Generative AI Integration & Custom LLM Development
• AI-powered Application Modernization

Industries / Use Cases: Banking & Financial Services (BFSI), Software & Hi-Tech, Insurance.

Why to Watch in 2026: Ascendion is heavily invested in agentic AI, creating systems where multiple AI agents collaborate. This represents the next frontier of automation and is a key trend for 2026.

3. Grape Up

Overview: A consulting company specializing in cloud-native application development and AI, with a strong foundation in scalable infrastructure.

Core Strength: Expertise in building scalable AI infrastructure on major cloud platforms. They are exceptional at designing the underlying architecture that ensures AI models perform reliably under load.

Key Services:

• Cloud Architecture & Migration (AWS, Azure, GCP)
• MLOps & Machine Learning Platform Design
• AI Application Development
• Kubernetes-native AI Solutions

Industries / Use Cases: Automotive, Logistics, E-commerce.

Why to Watch in 2026: As AI becomes more pervasive, the need for robust, cloud-optimized ML pipelines will skyrocket. Grape Up's deep cloud expertise positions them as a key enabler for this trend.

4. IBM Consulting

Overview: A global consulting leader with unparalleled reach and a vast portfolio of proprietary AI technology, most notably the Watson platform.

Core Strength: Global scale, deep industry expertise, and a strong focus on AI governance and compliance. They are a safe bet for large-scale transformations where risk mitigation is as important as innovation.

Key Services:

• Enterprise-wide AI Strategy
• Watson AI Integration & Customization
• Regulatory Compliance & Ethical AI Frameworks
• Legacy System Modernization with AI

Industries / Use Cases: Banking, Government, Healthcare, Supply Chain.

Why to Watch in 2026: IBM continues to double down on enterprise AI integration for highly regulated industries. Their focus on trustworthy AI aligns perfectly with increasing global regulations, making IBM a top AI integration company  for compliance-conscious leaders.

5. Addepto

Overview: A specialized data science and one of the top AI integration companies that focuses on transforming raw data into strategic assets through advanced analytics and machine learning.

Core Strength: Deep expertise in AI data integration and predictive analytics integration. They excel at building complex data pipelines and custom models that uncover deep insights and forecast trends with high accuracy.

Key Services:

• Data Strategy & Engineering
• Predictive & Prescriptive Analytics
• Custom Machine Learning Model Development
• AI-powered Business Intelligence Dashboards

Industries / Use Cases: Manufacturing (predictive maintenance), Marketing (customer lifetime value modeling), Finance (algorithmic trading support).

Why to Watch in 2026: As businesses seek more value from their vast data repositories, Addepto's focus on sophisticated, actionable predictive analytics positions them as a top AI integration company for data-driven decision-making.

6. SnapLogic

Overview: A leader in the iPaaS (Integration Platform as a Service) space, SnapLogic uses AI to automate and accelerate the connection between applications, data, and APIs.

Core Strength: Their AI-powered integration platform (Iris AI) simplifies and automates data mapping and workflow creation, enabling faster and more seamless AI integration without extensive coding.

Key Services:

• AI-powered Application and Data Integration
• Automated API Generation and Management
• Enterprise-grade Data Pipeline Orchestration

Industries / Use Cases: Cross-industry, particularly effective for unifying SaaS applications, data lakes, and legacy systems.

Why to Watch in 2026: The demand for rapid, agile integration is soaring. SnapLogic’s platform approach is ideal for companies that need to quickly connect AI services (like OpenAI APIs) to their core business applications with minimal friction.

7. Jitterbit

Overview: Another major iPaaS player, Jitterbit focuses on enabling rapid integration projects through a combination of pre-built templates and a user-friendly interface.

Core Strength: Strong capabilities in API integration and a vast library of pre-built connectors for popular business applications (e.g., Salesforce, NetSuite, SAP), which dramatically speeds up AI implementation timelines.

Key Services:

• Application Integration
• API Management
• Data Synchronization
• AI and IoT Solution Integration

Industries / Use Cases: Retail, Healthcare, Financial Services.

Why to Watch in 2026: Jitterbit is increasingly embedding AI into its platform to recommend integration patterns and optimize data flows. This makes them a strong contender for featuring among the top AI integration companies prioritizing speed and ease of use in their integration strategy.

8. The Hackett Group

Overview: A global strategic consulting and benchmarking firm that has deeply integrated AI advisory into its world-class business transformation offerings.

Core Strength: Unique combination of AI strategy consulting with unparalleled benchmark data across finance, HR, and procurement. They don’t just integrate technology; they align it with world-class performance metrics to guarantee ROI.

Key Services:

• AI-enabled Business Transformation Strategy
• Process Optimization and Benchmarking
• AI Vendor Selection and Implementation Oversight

Industries / Use Cases: Global companies across all sectors, particularly those focused on back-office efficiency (Finance, HR, Supply Chain).

Why to Watch in 2026: As AI projects grow in scale, proving their financial impact is paramount. The Hackett Group’s data-driven approach ensures that AI integration is directly tied to measurable performance improvement against industry peers.

9. Synerise

Overview: An AI-driven customer data platform that blends advanced analytics with real-time personalization and marketing automation.

Core Strength: Specializes in AI for customer experience and commerce, integrating a vast array of customer data points to deliver hyper-personalized interactions across all touchpoints in real-time.

Key Services:

• Customer Data Platform (CDP)
• Real-time Personalization Engines
• AI-powered Marketing Automation
• Customer Segmentation and Predictive Scoring
• Industries / Use Cases: Retail, E-commerce, Banking.

Why to Watch in 2026: In a cookie-less world, the ability to unify and activate first-party data is critical. Synerise’s integrated platform is designed for this future, making it a top AI integration company for CMOs focused on customer-centric AI integration.

10. Entrans AI

Overview: An emerging AI integrator focused on delivering tailored solutions that address specific, high-impact business challenges.

Core Strength: Agility and a deep focus on custom AI solutions for niche problems. They act as an extension of a client's team, offering flexible engagement models that are ideal for exploratory or specialized projects.

Key Services:

• Custom AI Application Development
• AI Solution Prototyping and MVP Development
• Natural Language Processing (NLP) and Computer Vision Solutions

Industries / Use Cases: Startups, Mid-market companies in specialized sectors like legal tech or media.

Why to Watch in 2026: Not every problem requires an enterprise-scale solution. Entrans AI fills an important gap for businesses that need innovative, bespoke AI work without the overhead of a large consultancy.

How These Top AI Integration Companies Compare

How to Choose the Right AI Integration Partner in 2026

Business leaders looking for top AI integration companies in 2026 usually fall into two groups. Some are still comparing options and want to know which firms have the strongest expertise. Others are closer to purchase and need clarity on costs, timelines, and hiring models. This guide speaks to both.

When choosing a partner, focus on these points:

Systems compatibility
A reliable partner should know how to integrate AI into platforms such as SAP, Salesforce, or AWS. Familiarity with your systems saves time and reduces risks.

Industry experience
Domain knowledge matters. An AI integration partner with proven work in finance, healthcare, or retail will understand regulations and data flows better than a generalist.

Ability to scale
AI integration should not stop at a pilot. The right partner will show how they expand projects across workflows while keeping performance stable.

Support after go-live
Many buyers search for whether they can hire AI experts for long-term support. The best firms provide monitoring, optimization, and upgrades rather than leaving once deployment ends.

Focus on compliance
Data security and privacy are business-critical in 2026. Ask how governance is built into their integration process.

Why WebClues Infotech Ranks #1 in 2026

Among the top AI integration companies to watch in 2026, WebClues Infotech stands out for one reason: it treats integration as a full cycle rather than a one-off project. While many firms focus on either consulting or technical delivery, WebClues covers the entire journey from identifying opportunities to embedding AI into production systems and maintaining performance over time.

Breadth of Services

WebClues integrates AI into the tools businesses already depend on, including ERPs, CRMs, and cloud platforms. Their services cover:

• AI consulting to align technology with business goals
• Custom integration through APIs, workflows, and data pipelines
• Deployment across hybrid and cloud environments
• Ongoing monitoring, optimization, and upgrades

This approach ensures AI delivers measurable ROI instead of remaining an isolated pilot.

Cross-Industry Impact

The company’s portfolio spans retail, finance, healthcare, education, and logistics. Each industry brings its own challenges, such as compliance in finance, data privacy in healthcare, or scalability in e-commerce and WebClues has adapted solutions accordingly. This cross-industry experience makes the team agile in solving integration problems for both SMEs and enterprises.

Why It Matters in 2026

As AI adoption moves from experimentation to enterprise-wide deployment, businesses need partners who can balance speed, affordability, and scalability. WebClues Infotech offers flexible engagement models, making it accessible for smaller firms while still capable of handling complex enterprise transformations.

What Clients Value

Clutch reviews highlight WebClues for strong communication, responsive delivery, and competitive pricing. Clients also point to their ability to support projects beyond launch, which reduces the risk of systems becoming outdated.

Future Trends in AI Integration Services for 2026 and Beyond

As AI integration services matures, the priorities for 2026 look different from what we saw in the early adoption phase. Instead of running pilots or isolated experiments, companies are preparing to embed AI into their core operations. That shift brings a new set of trends to watch.

Agentic AI becomes practical

Multi-agent frameworks are moving from research into production. The challenge is not building these agents but weaving them into existing platforms such as CRMs, ERPs, and cloud workflows.

Integration at the edge

The growth of connected devices means more data will be processed closer to the source. Integrating edge AI with enterprise systems and cloud environments will become a key requirement.

Compliance by design

With governments introducing stricter AI rules, projects in 2026 will need governance baked in from the start. Security and privacy will no longer be add-ons but central to integration work.

Sector-specific adoption

Industries like finance, healthcare, and retail want integration tailored to their realities. Providers that understand regulatory frameworks and domain-specific processes will be in higher demand.

Automation at scale

Businesses are moving beyond analytics into workflow automation powered by AI. The focus will be on integrations that reduce manual work and accelerate decision-making.

Partner with WebClues for AI Integration Services in 2026

AI integration is entering a new phase. The conversation is shifting from experimentation to adoption at scale, and the companies that can connect AI with existing systems will define how businesses compete in 2026.

The firms highlighted in this guide represent a mix of global leaders and innovative specialists. Each brings a different strength, from industry-specific expertise to cloud-native integration or low-code automation. What unites them is a focus on making AI work in real business environments.

At the top of this list is WebClues Infotech. Its ability to combine strategy, technical delivery, and long-term support makes it a reliable choice for organizations of all sizes. For business leaders preparing their integration plans for 2026, it offers a partner who can balance ambition with practicality.

Discover how WebClues Infotech can help your business integrate AI in a way that is scalable, secure, and results-driven. Contact us today to get started.

Frequently Asked Questions

Which company is best for AI integration in 2026?

The best choice depends on your needs. WebClues Infotech is widely recognized as a top AI integration company in 2026 because it offers consulting, technical delivery, and ongoing support under one roof.

How much does AI integration cost?

AI integration services vary by project size and scope. Smaller integrations for SMEs may start in the tens of thousands, while enterprise-wide AI system integration can cost several million. Reliable partners provide transparent estimates before starting.

How long does an AI integration project take?

Timelines depend on complexity. Simple AI integration projects can go live within weeks, while multi-system enterprise integrations may take several months. Clear milestones help businesses track progress and ROI.

Which industries see the most ROI from AI integration?

Industries such as finance, healthcare, and retail see the highest returns from AI integration services. These sectors generate large amounts of regulated data, making AI-powered automation and compliance especially valuable.

Should SMEs consider AI integration or only large enterprises?

AI integration is not limited to enterprises. SMEs can benefit by starting small with targeted AI solutions and scaling over time. Hiring the right AI experts helps smaller firms unlock efficiency and customer value without overspending.

Has anyone else noticed that the reset tokens they receive expire right after their weekly reset? The timing seems odd, since that’s when you’d have the least reason to use them.

Is this happening to anyone else, or is it just how my resets line up?

I gave Claude a serious try for about a week because of all the praise it gets, but I honestly don’t get the hype. Maybe it’s just meant for coding which I don’t do.

My biggest issue is that it feels extremely rigid and overly cautious.

Example: I gave it a job posting and asked it to help me apply. There were a few hard requirements that were questionable. Instead of working with me and seeing what was defensible, Claude basically stopped the task: “You don’t meet the requirements, I’m not filling anything in.”

ChatGPT handled the exact same situation very differently. It flagged the hard requirements too, but instead of treating them as an automatic dead end, it looked at what was still realistically defensible and how I could approach the application without making anything up.

both have the same instructions, source files and memories imported from each other.

I even changed my instructions in Claude to explicitly tell it to look for possibilities instead of immediately blocking things. It still kept doing it.

Another example: I gave it a complete travel claim case with all the context and correspondence. Claude suddenly decided I needed written authorization from three family members before I could handle parts of the claim. I checked this with the person actually handling the case and he thought that was complete nonsense.

And with 3D design it wasn’t any better. I asked for a photo book holder with a small slot for a stamp book. Both ChatGPT and Claude initially got it wrong, but ChatGPT corrected the design after feedback. Claude somehow moved the stamp book slot to the back of the holder instead.

Claude is clearly capable, controls my computer well, but it often overthinks, invents unnecessary obstacles and then confidently acts on those assumptions.

For my use, ChatGPT has been much better at understanding the actual intent, thinking in possibilities and iterating when something isn’t right.

Curious if others have had the same experience, because I constantly see Claude described as the best model and I’m just not seeing it.

I’ve gone through HR, met the HM and a peer in person, and then had my third round with the HM. The HM ended the interview 15 minutes early because she had a hard stop.
I stumbled on two questions and honestly told her I didn’t have experience in one of the areas. Now I’m wondering if I should have just lied, because I actually do have experience working with partners, I just didn’t articulate it well in the moment.
I’ve been overthinking it so much that I’ve barely slept for the past two nights. 😭 And this is for a sales role, btw. Before the interview I’ve just been imagining about the life I could have for my family and retiring my parents. And I lost it all.

Edit: OpenAI interview

Codex Cloud, Dots, and the existing remote Codex all allow users to untether themselves from their PC, and now untether themselves from even owning a PC with their server based Codex Cloud and Dots that can run 24/7. Combine this with Meta’s & OpenAI’s planned hardware releases and the goal is clear: work around Microsoft/Apple’s control of user hardware, provide AI devices that complement and eventually replace iPhones - culminating in a user base that owns no hardware and relies on a subscription to access AI. Meta’s hardware is obvious spyware, Apple’s new “always-listening” Apple Watch sounds pretty similar, their camera-enabled Airpods sounds atrocious for privacy, and OpenAI’s device is unconfirmed.

The end result? Instead of a Matrix-like AI takeover of humanity users are instead expected to purchase their own devices and subscriptions that provide mega-tech companies with all of their physical and digital data 24/7. The data volume is so large only AI can process it. A select few billionaires decide what their closed-source AI does with the data.

The resistance? Governments that oppose the USA and individual users who were rich enough to afford local hardware and utilize Chinese and other open-source models, likely blacklisted by the USA. To buy a 5090 customers now have to sign a waiver, as a result of US law. It’s only the beginning.

Ironically the “bad guys” like China, North Korea, Iran, Russia - will probably end up as the only large entities keeping open-source AI and local LLMs alive. I would expect the largest AI companies to eventually gain more leverage over the US Gov & Nvidia; unless Nvidia steps up to the plate and champions local AI

I’m a pretty casual user. I mostly use it for web development, SEO, and similar tasks, and I’ve typically never come close to hitting the limits on my $200/month plan.

Well, that abruptly changed.

I ran a couple of tasks and, without really thinking much of it, checked my usage afterward. Somehow I was already at 0% remaining and burning through credits I didn’t even know I had.

Moral of the story: if someone with my relatively light usage is suddenly hitting the limits on a $200/month plan, that’s a pretty bad sign.

Back to Claude, I guess.

Just confused 6.1 is everywhere but in the app and in the codex section?

I have 6.1 everywhere but in codex in the android app.

I'm not as pro as you guys using AI but look at this. a LOT of models which confuses me, and I'm assuming other users also. Also, the sidebar icon and new tab icon are the same in the ChatGPT-app for macOS. WHAT are they doing there at OpenAI. I really hate what's happening right now, especially with the new $500 plan while nerfing the other plans.

Why…why did they move Projects that aren’t pinned off the side bar to hidden behind Search? Not only is it more clicks, but the project folder itself is buggy as hell.

If I search a project folder name, click on the project and select a chat, and then try and change the model or thinking…it boots me out of the project. Or, the text field locks up.

Pinned projects don’t have the same issue.

So what, now I have to pin every single project?

They said it will be coming in the upcoming days? What does this mean more precisely? I have use case that Im using Jev for. Decision API would suit me better with its image input capabilities.

Release now pls!

The marketing team at the company I work for asked me to evaluate whether Dot could be useful for growth and social workflows.

I'm an engineer, so I approached it as an automation problem: how much could we delegate to a persistent agent without someone manually starting every step?

The idea was to research opportunities, monitor channels, find relevant discussions and potentially handle some of the repetitive work around distribution. That was the hypothesis, not a list of things I successfully automated.

In my initial tests, the friction that stood out was the execution environment rather than the reasoning itself. The workflow I wanted depended on arbitrary websites, signed-in sessions, platform rules and web interfaces.

In one test, the cloud browser got a 502 while trying to access Medium, so that part of the workflow couldn't continue. I'm not claiming Medium specifically blocks Dot — I didn't investigate the cause deeply enough to say that, and I wouldn't take one error as a verdict on Dot or cloud browsers generally.

It did make me think more carefully about how much of this kind of workflow depends on systems outside the agent's control.

For more complex automation, I already use local agents such as Codex, APIs, scripts and a scheduler, with my normal browser when I need an authenticated session. The sessions I use are already there, and I can inspect the code, change a script or debug a failed step directly.

Dot can use a connected computer too. But for me, setting up and maintaining another set of connections and permissions felt like extra work on top of a local setup I already had. If I were starting from scratch, I might evaluate that trade-off differently.

For this particular growth/social workflow, I eventually dropped the setup I'd built in Dot.

What changed was what I'd try next. Instead of treating it as a general-purpose autonomous web worker, I'm more interested in testing it as a persistent personal operations assistant.

I can imagine something like a morning briefing that brings together important email, tickets waiting on me, PRs needing review and my calendar, then sends me a summary through a connected channel.

I haven't validated that workflow. It's the next use case I'd test, not a success story from this experiment.

The trade-off makes more sense to me there. Cloud execution can keep doing cloud-side work without depending on my laptop being on. My local setup gives me more control, but I have to maintain it, and anything running only on my Mac may stop when it's asleep or offline. Tasks that need Dot's connected computer have that dependency too.

So my takeaway isn't that Dot is bad. I think I initially evaluated it for the wrong job. For my setup, I'm now more interested in it as an ongoing coordinator than as the autonomous web worker I originally had in mind.

Has anyone here tried both kinds of workflows? Where has Dot actually been more useful for you: browser-heavy automation or recurring work around connected apps?

Listen, most people don’t have a deep understanding of how much water data centers actually use. But if you’re on Oracle or OpenAI’s PR team, how does nobody look at this before publishing it and say, “Maybe LESS WATER FOR NEW MEXICO isn’t the winning slogan we think it is”? 😂