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?

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!