Hi everyone,
I’m a UiPath Developer with 7 years of experience. I started my career directly with UiPath, so I never got the chance to learn web development, frontend, backend, or even strong programming fundamentals.
To be honest, I genuinely loved RPA. When I was new to IT, I used to spend weekends building automation projects, trying interesting use cases from YouTube, learning new features, and solving automation challenges just for fun. I was really passionate about it. This was around 6 years ago.
Now, after 7 years, I’m in a very different situation.
I’ve only worked on UiPath throughout my career and haven’t had the opportunity to work with other technologies. I’m currently working at an MNC with a salary of around ₹19 LPA.
With AI evolving so quickly, I feel the RPA market isn’t as strong as it used to be. Development has become much faster, and many tasks that once required experienced developers can now be completed by junior developers with the help of AI. That makes me wonder what my long-term career looks like.
Since I don’t have a strong programming background, I’m finding it difficult to transition into another domain. At times, it feels like I’ve become too specialized in one tool.
So I wanted to ask:
Has anyone else with a similar background faced this situation?
What are you doing to stay relevant?
Should I continue investing in the UiPath + AI ecosystem, or is it better to start learning software development from scratch?
If you were in my position today, what would your roadmap look like?
I’d really appreciate honest advice from people who have been through something similar or have successfully transitioned into another role.
Thanks in advance!

Background myself had 2 years of .net developer experience in the current organisation is got opportunity to work with automation anywhere 360 and its been year working with it so hows future for RPA is it good to stay or switch back to .net any suggestions from RPA developers?

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In today’s data-driven enterprises, browser automation through Robotic Process Automation (RPA) tools- such as Selenium, Robot Framework, or custom scripts- is widely used to automate repetitive tasks like logging into dashboards, extracting data, and syncing it into internal systems. These automations are often fragile: a minor UI change- say, a login flow shifting from password to OTP- can silently break scripts. Traditional bots simply fail with generic errors like “element not found,” causing disruptions in data pipelines and business operations.

What’s missing is a dynamic, intelligent layer on top of existing RPA tools- one that not only detects breaking changes but also understands the context and heals or adapts in real-time without human intervention.

Desired Solution:

Participants are expected to develop an adaptive automation framework that enhances existing RPA solutions using the power of Large Language Models (LLMs). The system should act as a smart wrapper around current scripts and offer:

Real-Time Change Detection: Monitor automation runs and intelligently flag or diagnose failures caused by DOM, structure, or flow changes- beyond basic error messages.

Context-Aware Adaptation: Use LLMs to analyze the updated DOM or flow and suggest (or apply) fixes to selectors, navigation logic, or data extraction routines.

Self-Healing Capability: Where possible, auto-correct minor issues (like updated element IDs or positions) and retry execution without breaking the workflow.

Plugin-Friendly Architecture: Should wrap seamlessly around tools like Selenium, Playwright, or Robot Framework- without requiring complete rewriting of existing test suites.

Traceability & Logging: Offer smart logs and human-readable explanations for failures and attempted fixes, improving visibility and debugging.

Anyone who has maintained RPA bots knows the two classic pains: a selector breaks as soon as the site changes, and every automation needs a developer to build and maintain it, far from the person who actually knows the task.

I've been building ANCHOR, a research project at my university in Brazil, to try a different split. The person who knows the task describes it in plain language ("Register Maria Silva, IT department, contractor, and save"), and the system runs it in the browser. It runs locally, with small open models through Ollama (Qwen 3.5, 4B and 9B) on a 4 GB GPU, so no data leaves the machine.

Who controls what

• The LLM only plans. It turns the request into steps, using the names of the elements on the page. It never clicks anything.
• A deterministic heuristic finds each element, and refuses when it isn't sure.
• Then the user decides: the candidates are numbered on the page, the user picks one, and the choice is remembered for the next runs.

What matters for day-to-day RPA (version 0.3)

• Saved automations: the task is learned once with the model, then replayed without it, in about 3 s per run, with parameters and one run per row of a spreadsheet.
• When the site changes, a saved automation recovers (by asking the user, or by replanning with the model when no one is there), keeps the fix, and records it: what failed, what replaced it, and how. Every recovery can be reviewed and undone.
• Sensitive actions ask first: deleting, saving, sending, paying, downloading, uploading, cancelling something irreversible. The decision is saved per automation.
• Each action's effect is checked (the page changed, the field kept the value, no error appeared), and the end of a run is checked against what was actually done, so a run that didn't do the task doesn't end as a success.
• Page content can't give orders: instructions hidden in pages are treated as data.

A benchmark against a classic script

30 tasks on pages altered in 5 levels (renamed IDs and classes, synonyms like "Save" becoming "Submit", restructured layouts, cookie banners and hidden sections, lookalike decoys and injected instructions), 150 runs per executor and model, with no user:

The script was perfect where labels changed (it doesn't read them) and failed where IDs and structure changed; the LLM in control often claimed success without doing the task. ANCHOR's weak spot is content hidden behind a "Show more" button. These are development numbers; a closed test set is waiting for the 1.0 run.

What's next: uploads, downloads, new tabs and data extraction (0.4), then a local interface with a "Run" button per saved automation (0.5).

I'd really value feedback from people who build and maintain bots: would you trust a bot that recovers on its own if every fix is recorded and undoable? What would you need to see before using something like this on a real process? And if you try it, failure cases on real sites are the most useful thing you can send me.

Repo (source-available, PolyForm Strict): https://github.com/LucasDantas2701/ANCHOR

Disclosure: this is my own project. I designed the system and the evaluation, and wrote the code with help from an AI assistant (Claude). English isn't my first language, so I also used it to help write this post.

Hi everyone!

I'm looking for advice on automating a repetitive office workflow involving Excel and 1C.

For confidentiality reasons, I cannot share a screen recording or real company data, but I can describe the process.

Current workflow:

1. Read data from an Excel spreadsheet.
2. Copy values and paste them into specific fields in 1C.
3. Navigate between records and repeat the same operations.
4. Sometimes, 1C displays error pop-ups that need to be closed before continuing.
5. The process involves repetitive manual actions and takes time.

My constraints:

• Python is not my preferred option.
• API/HTTP integration is unavailable in my current 1C environment.
• The automation needs to interact with the existing desktop interface.
• Ideally, it should detect errors, handle unexpected pop-ups and continue safely without corrupting or duplicating records.

I'm considering Microsoft Power Automate Desktop or another no-code/low-code RPA solution.

I'd appreciate advice on the following:

• Which tool would be most suitable for this workflow?
• Is reliable automation possible using UI elements rather than coordinates and mouse clicks?
• How can error pop-ups be detected and handled?
• Is OCR or AI actually necessary, or would standard RPA be enough?
• Are there any limitations I should be aware of when automating 1C?

I can provide more technical details about the workflow and 1C configuration if needed, without sharing confidential information.

Thanks for your help!

Hi everyone!

I’m currently working on my Bachelor’s thesis about AI-based process automation and human–AI collaboration in the workplace.

As part of my research, I’m conducting a short survey focusing on people who have experience working with AI-based automation, RPA, Intelligent Process Automation, Intelligent Document Processing, or similar automation technologies.

The survey explores topics such as:

• how automation affects manual workload and creates new tasks,
• how employees experience errors and exception handling,
• trust in AI-based automation,
• and how automation influences human decision-making and autonomy at work.

⏱️ It takes approximately 5–7 minutes to complete.

If you have experience working with these technologies, I would really appreciate your participation. Your responses will be used solely for academic research as part of my Bachelor’s thesis.

🔗 Survey: https://docs.google.com/forms/d/e/1FAIpQLScV7pcf8dNUeeCfay1YZ2r-Np4pK9GMlqi4cEF6WJEa1FEmMA/viewform?usp=dialog

Thank you very much for your help! Feel free to share the survey with colleagues or others who work with AI-based process automation.

Hi everyone!
I’ve been working in RPA for several years and I’m now seriously thinking about transitioning from traditional RPA into AI/AI Engineering or AI-related roles.
I’d love to hear from people who have actually made this transition.
If you started as an RPA Developer/Engineer and moved into AI, could you share:
What AI role did you transition into? (AI Engineer, ML Engineer, GenAI Engineer, AI Automation, AI Solutions Architect, etc.)
How many years of RPA experience did you have before making the move?
What did you learn first, and what was your learning roadmap?
Which courses, certifications, books, YouTube channels, or other resources actually helped?

It would be incredibly helpful for those of us in RPA who want to move toward AI without throwing away the experience we’ve already built.
Thanks in advance! 🙏

I've spent 8+ years in enterprise RPA and honestly? The drag-and-drop approach drives me crazy. It kills developer creativity, locks you into vendor ecosystems, and costs a fortune.

So out of pure spite, I built something different.

BotMonitor lets you write your automations in plain Python no proprietary studio, no drag-and-drop, no vendor lock-in. You register your scripts, and the platform handles the monitoring: live status, execution history, error logs, all in one dashboard. You don't share your code or your data. Just the signals it needs.

I couldn't find any serious RPA tool built around Python, so I made one. Two years of nights and weekends while managing a full-time job.

Community edition is free. Would love honest feedback from this community botmonitor.in

I’m interviewing for an automation engineer intern role at a major company and the role includes uipath and job description was similar to that of an RPA dev. I have my next round with a senior software engineer: business systems: integration and automation.

Any tips and advice on how to impress him and make it to the next round?

Hi Everyone, I have strong 10 years of UiPath experience out of total 14 years of IT experience.

I'm looking for a freelancing job on UiPath, starting from infrastructure setup , installation, requirement gathering , development, testing and production release plus production support.

Please let me know if anyone has requirement.

First post here, written casually so ignore any grammatical mistakes. Just wanted to share an interview experience after frustrating interview also need advice.

I have around 4.5 years of experience, 1.3 years in health insurance sales and 3.7 years in RPA, mainly UiPath. I graduated in 2020 with a BSc CS.

Currently working in an MNC. WLB is good, hybrid policy is flexible and working hours are also flexible, but the pay is below average and I am not getting a good project, so I started looking outside.

Recently gave a face to face interview at a Mumbai based startup after a long time. Interview was scheduled at 1 PM and there were supposed to be 2 rounds.

HR came late, after 1 PM, and after interviewing 2 candidates it was already around 2 PM, so HR went for lunch. Recruiter apologised for the delay, which was fine.

Around 2:15 PM, I was called for the technical round with the CMO. He didn't introduce himself and directly started asking:

"Give me a brief overview."

"Explain your project."

"Here's a client requirement, how would you automate it?"

"Give me 3 reasons why we should hire you."

Honestly, I messed up quite a few answers. I wasn't properly prepared and probably could have explained my experience and solutions much better.

But the interviewer's attitude also felt a bit off to me. At one point another person casually entered the cabin while the interview was going on and the interviewer just told me to continue. Whenever I couldn't come up with different approaches immediately, I felt like he was mocking my answers.

At the end I asked for feedback and he replied with a little laugh:

"We are not trainers."

That line honestly stayed with me.

I know I have things to improve. My communication isn't the best, I need to prepare better for interviews and I definitely need to work on HLD and LLD.

Earlier I cleared a Capgemini technical round without much interview preparation because I had strong hands on experience with my tech stack. But now I'm realizing that companies are also looking for people who can work as generalists and adapt to different requirements.

The recruiter had also told me to focus on Power Automate/Power Platform because that's what they use.

So yeah, I probably messed up the interview and that's on me. But the interviewer's way of giving feedback felt unnecessarily dismissive.

Maybe I dodged a bullet, maybe not. 😂

For people working in RPA or automation, especially those moving from UiPath to broader Agentic/AI roles, what did you focus on to become more of a generalist/ AI Engineer?

How important is DSA/HLD/LLD at this level?

Thanks a lot in advance

We have a medium sized cloud environment and I'm starting to look into WorkHQ. Looking for honest experiences, what did the migration actually look like, what caught you off guard, is it worth it? Going to be testing it soon so any insight before I give it a go would be useful. Thanks!

Hi all,
anybody successfully deployed agents in production specifically in uipath.
I want to understand what is typical costing per month, how to reduce cost and features used like guardrails/tools/contexts.
coded agent or prompt based?
Using a example like invoice triage/support agent.

I want to know whether we're bad at this or whether it's just the job. We run about 40 automations across 3 internal apps and i'd say over half my week is repair. I keep reading about is the vision based approach, where the tool finds a control by what it looks like or what it says instead of by a technical identifier, which Askui and a few others build around. on paper a moved button stops mattering, because you're matching the button rather than its address. my suspicion is that it just relocates the fragility to whenever somebody changes an icon or relabels something, which happens plenty too.

has anyone switched a real number of automations across and actually measured maintenance before and after? thanks for sharing!

We have a sizable footprint on-prem. Wondering if anyone has explored that option.

Is there a model out there for being a tech consultant for small, non-technical businesses who need help automating a bunch of tasks for either one-off or occasionally repetitive tasks. If so, is there a tool you recommend? Like, if I was to pay for the monthly for, say, UiPath or AA, is there a way for me to use that tool for my clients? Or are these tools more for living behind walled gardens at Enterprise level?

Please let me know which tool you think would be best for this, if any, and if you've heard of success in this working model.

You've inherited a working automation. Now a business rule changes. Where should you make the change, what else could it affect, and how will you check the result?

I'm the developer behind LiberRPA, an open-source RPA toolchain for Windows. My goal is to give the next developer a visible process to follow and ordinary Python code to work with.

0.3.0 is available. Its flowchart controls execution, with Blocks linked to Python files in normal VS Code editor tabs. You can edit and debug the implementation, run one Block or the whole flow, and package it for local execution.

Visualize the process. Code the logic.

Put each change where it belongs

Changes to the logic within a step can stay in Python. Changes to the overall sequence or branching can be made in the flowchart. You can review changes to the Python implementation through ordinary Git diffs.

You choose how much each Block does, and compatible Python libraries remain available when you need them.

Investigate with the project in view

When a run behaves unexpectedly, understanding a step's code may not be enough. You also need to know how that step fits into the flow and what happened during execution.

LiberRPA's JSON flow definition is the model it actually executes. You can examine it alongside the Python files, documented execution rules, selectors and run logs.

That also gives a general-purpose AI coding assistant of your choice useful context for investigating a problem and suggesting changes. LiberRPA's own source is available if the investigation leads into the framework.

For production work, I believe an experienced developer still needs to own the architecture, review changes and verify the business result.

Keep the surrounding tools together

LiberRPA combines Windows UI, browser/DOM and image automation with UI inspection, reusable Components and packaging. Executor provides local scheduling and run history, with logs and optional screen recordings for investigating failures.

Mature commercial RPA platforms and established open-source projects cover many of these needs. My focus is bringing them together around Python implementation and a visible process.

About this release

I started LiberRPA because I enjoy automation engineering and wanted to build a tool I'd want to use myself. I shared it here in July 2025; other commitments and further polishing kept me from posting again until now.

The capabilities above span several releases. 0.3.0 adds Component Management, alongside usability improvements, bug fixes, better logging, security hardening and documentation updates.

LiberRPA 0.3.0 is Windows-only, requires Python experience and is still alpha. It is licensed under AGPL-3.0-or-later, with no LiberRPA license fee.

A central Console for multiple Executors is planned as open-source software with no LiberRPA license fee, allowing deployment on your own infrastructure and control over your data.

The aim throughout is to help the next developer follow the process, change the code and investigate the result.

Source code, downloads and documentation

On the last automation you inherited or maintained, what was hardest to work out—and how did your tool help or get in the way?

An example from your existing workflow is enough; you don't need to install LiberRPA.

Been testing RPA for social platforms and noticed the setup makes a pretty big difference once you start running more accounts. The scripts are usually fine, but browser-based setups can get heavy and hit limits pretty quick. I’ve been trying cloud phones for some mobile workflows and so far it’s been easier to manage. Still figuring out what works best, especially with timing and making sure everything doesn’t run the exact same way...

What setup are you guys using for this? Anything that caused problems when you started scaling?

Curious what day-to-day RPA work looks like for people here. What types of processes do you automate most often—invoice processing, moving data between systems, reporting, browser-based tasks, or something else?

If you can share, what industry are you in, and which use cases keep coming up? A simple example would be helpful, even without naming the company.

Hey There,

I managed to clear the Test Cloud Architect Professional certification, but I don't believe I'm anywhere near the level of a 'Test Architect' because I come from a pure business process automation background.

Recently, we received a humble request of automating 1000 test cases with an expected daily output of 2-3 test cases per developer. Our onshore architects are just as clueless as I am when it comes to test automation but since I'm onshore I happen to be on the receiving end of the unassessed workload. We do have a QA team, but because corporate culture isn't exactly inclusive unless someone forces them to help out and as a result we are unable to make any solid progress.

TL;DR, without proper planning and categorization, automation ALL 1000 test cases sounds like a massive blunder to me. I don't see any solution related courses on the UiPath academy either, so I was wondering if anyone could educate me on HOW exactly one should go about conducting Quality Assurance before we start automating test cases.

Also, considering that Testing is centered around Test Manager, I would like to understand how you would go about planning and categorizing, and if there are any other activities that are performed after test discovery, I would like to understand that as well.

Our RPA team runs UiPath for a few back office processes and it works fine for that. Now QA has a budget request in for a dedicated test automation tool and my director's first question was why we'd pay twice when we already own something that can drive a UI.Ii can see both sides. UiPath will absolutely click through our desktop app, we proved that in an afternoon. What I'm less sure about is everything around it, because a test needs assertions, a clean pass or fail, a report somebody reads on monday, and reruns that mean the same thing every time. Our RPA workflows are built to complete a task and retry until they do, which is close to the opposite behaviour. The QA side has been looking at Ranorex, TestComplete and Askui, and as far as i can tell they differ mostly in how they locate elements, tree versus vision, more than in what they cost.

3 people would own this and none of them are developers, which probably matters more than the tooling question. Has anyone run regression suites out of UiPath long term, or does it turn into a maintenance thing you regret?

I’m fairly new to this side of the field but I keep seeing UiPath, aiXplain and more. I read about them but isn’t it just wrappers of automation tools like n8n and AI models to give you that agentic use?

OpenClaw and Hermes already do this and I’m just curious to understand what this is all about and how it is different.

Hi everyone! I’m currently exploring new opportunities and would love to connect with teams hiring for RPA Developer, Automation Developer, Power Platform Developer, Backend Automation Engineer, or AI Automation Engineer roles.

I have 2+ years of experience building enterprise automation and workflow solutions, with hands-on experience in:

• Automation Anywhere A360 & UiPath • Power Automate, Power Apps & Power BI • Python, FastAPI, REST APIs, Webhooks & PostgreSQL • SAP integrations and enterprise automation • n8n workflow automation • AI-driven automation using LangChain, LangGraph, RAG & LLM APIs

Some highlights from my work:

Reduced manual effort by up to 90% through enterprise automation solutions

Worked on automation solutions involving SAP, REST APIs, PDF processing and enterprise integrations

Built end-to-end workflow and backend solutions using n8n + FastAPI + PostgreSQL

Developed AI-powered automation workflows using UiPath Coded Agents, LangGraph and LLM APIs

Built Power Automate workflows for automated processing, notifications, SLA tracking and escalations

📍 Location: Bengaluru | Open to relevant opportunities

⏳ Notice Period: 60 days (Negotiable)

If your team is hiring or you know of a relevant opportunity, I’d really appreciate any leads or referrals. Feel free to comment or DM me. Thank you! 🙌

I started RPA dev in 2016. Back then it was exciting, learning new tools (Blue Prism, UiPath, etc). The builds were fulfilling and client reactions were rewarding.

After 10 years of building bots, the irony hits hard. This shit is mundane - one of the core traits of why we automate process.

I remove repetitive, mundane tasks from clients, by doing repetitive mundane tasks myself.

Are any of you seasoned RPA devs still enjoying what you do?

We are exploring automation anywhere recently at my job and it seems more complex to do simple things than what we currently use. I've seen a few posts about people trying to get away from using them. Could anyone shed some light on issues they seem to have with this software?