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This is the LLM integration approach I was pitching last year to some companies. Though in my case it was strictly tied to self-hosted inference. Agents at the

by mhitza 6mo ago

This is the LLM integration approach I was pitching last year to some companies. Though in my case it was strictly tied to self-hosted inference. Agents at the edge of business where they can work independently, asynchronously, is an approach that I don't feel was explored enough in business environments. Sending your entire communication and documents to OpenAI would be a very bold choice.

linkjuice4all 6mo ago
Not only are businesses already doing that - they're not even cleaning up their source material so LLMs are generating garbage outputs from the old inconsistent trash that haunts Confluence, Google Drive, and all of the other dumping grounds for enterprise ephemera. Oftentimes "AI transformation" is just a slightly better search engine that regurgitates your old strategy (that didn't work the first time) and wraps it up in new sycophantic language that C-levels use to bulldoze the budgets and timelines of actual skilled front line employees. I do believe that LLMs and AI provide actual value, but the "workspace" is usually the passive aggressive CYA battleground for employees to appear productive in-spite of leadership's blind-spots, ossified business practices, and "aligned" decision-making that doesn't actually fix a broken org. Maybe this release will be the one that finally challenges nepo-hires, not-invented here, and all of the other corpo crap that defines "enterprise" business.
- pixl97 6mo ago
  Cleaning up source material is not easy work in companies that have massive piles of it and don't exactly know which parts of it are wrong. Quite often these documents are poorly versioned and do work for something but not exactly what you're looking for. With this said, you can use your incorrect AI answers to find and then purge or repair this old and/or poorly written documentation and improve the output.
  - linkjuice4all 6mo ago
    I agree - and I've noticed that these AI transformations tend to lay bare the many issues, inconsistencies, and other problems with workspace functions and data. Unfortunately the people that are usually in charge of these projects do not have the seniority or sway to actually change the broken processes or aren't on the right team to remove cruft. Usually you have to wait until a salesperson misquotes something from an AI summary before these issues get unblocked because they actually affected revenue.

by mhitza 6mo ago

linkjuice4all 6mo ago

Not only are businesses already doing that - they're not even cleaning up their source material so LLMs are generating garbage outputs from the old inconsistent trash that haunts Confluence, Google Drive, and all of the other dumping grounds for enterprise ephemera. Oftentimes "AI transformation" is just a slightly better search engine that regurgitates your old strategy (that didn't work the first time) and wraps it up in new sycophantic language that C-levels use to bulldoze the budgets and timelines of actual skilled front line employees. I do believe that LLMs and AI provide actual value, but the "workspace" is usually the passive aggressive CYA battleground for employees to appear productive in-spite of leadership's blind-spots, ossified business practices, and "aligned" decision-making that doesn't actually fix a broken org. Maybe this release will be the one that finally challenges nepo-hires, not-invented here, and all of the other corpo crap that defines "enterprise" business.

pixl97 6mo ago
Cleaning up source material is not easy work in companies that have massive piles of it and don't exactly know which parts of it are wrong. Quite often these documents are poorly versioned and do work for something but not exactly what you're looking for. With this said, you can use your incorrect AI answers to find and then purge or repair this old and/or poorly written documentation and improve the output.
- linkjuice4all 6mo ago
  I agree - and I've noticed that these AI transformations tend to lay bare the many issues, inconsistencies, and other problems with workspace functions and data. Unfortunately the people that are usually in charge of these projects do not have the seniority or sway to actually change the broken processes or aren't on the right team to remove cruft. Usually you have to wait until a salesperson misquotes something from an AI summary before these issues get unblocked because they actually affected revenue.