Hey everyone! 👋 I've been using You.com for a few months now, mostly to research database tools, ETL pipelines, and cloud-native services as I plan migrations. While it's fantastic for pulling together technical docs and comparisons, I've hit a consistent and frustrating snag: **its tendency to hallucinate or present outdated pricing information for software.**
This isn't just a minor annoyance—it can derail a project's budget planning. I was researching a migration from a self-hosted MySQL cluster to a managed Postgres service in the cloud. I asked You.com for a cost comparison between a few popular providers. The features and technical specs were spot-on, but the quoted monthly prices for two of the services were completely wrong, referencing plans that were discontinued over a year ago! I almost based a recommendation on that.
Here’s what I’ve learned to do to fact-check and avoid this pitfall:
* **Always Corroborate with Primary Sources.** Treat any pricing info from You.com as a starting point, not the final answer. Immediately open the official pricing page of the vendor.
* **Use Specific, Time-Bound Queries.** Instead of "X pricing," try "X pricing as of 2024" or "X current pricing plans." This sometimes nudges the AI to look for fresher data.
* **Double-Check for "Beta" or "Legacy" Labels.** The AI might conflate beta program pricing (which is often free or discounted) with general availability pricing. Be skeptical of any unusually low numbers.
* **Leverage Its Strengths for the Legwork, Then Verify.** Where You.com shines is in compiling *what* to look for. Ask it: "What are the key pricing dimensions for managed MongoDB services?" You might get a great list like:
* Compute instance type & vCPUs
* Storage provisioned vs. IOPs
* Data transfer/egress fees
* Backup retention costs
* High-availability/replica set surcharges
Then, you take that excellent checklist and visit each vendor's site to fill in the *actual, current* numbers yourself.
It's a bit like managing data integrity during a database migration. You wouldn't trust a legacy script to accurately map data types without testing; don't trust an AI's pricing output without validation. The tool is incredibly useful, but for financial data, you absolutely need to go to the source.
Has anyone else run into this? What's your workflow for getting reliable cost info when evaluating tools?
—B
Backup first.
You've nailed the main defense, but I think the "specific, time-bound queries" advice has a flaw. These models aren't actually querying a live database, they're generating text based on patterns. Asking for "pricing as of 2024" might just make it confidently generate a 2024-style price table that's still pure fiction.
The only reliable method is your first point: primary sources. Any other query just changes the decoration on the hallucination.
This isn't unique to You.com by the way. I see the same issue when researching CRM add-ons or API cost changes. The sales tool landscape shifts too fast for these models to keep up.
Your CRM is lying to you.
Yeah, you're totally right about the time-bound query trick being a placebo. I've caught myself thinking "maybe if I ask for the 2024 pricing page..." and then realizing that's just me hoping for a different kind of hallucination. The model is aiming to please, not to fetch.
It really is a universal problem with these tools. I've burned time comparing Datadog's supposed reserved instance discounts against AWS's, only to find the numbers were plausible but entirely fabricated. The pattern recognition works great for architecture, but pricing is a moving target with too many variables.
Your point about the sales tool landscape shifting too fast is key. I'd add that even when the model lands on a correct price, there's no flag or confidence score to tell you it's accurate versus a lucky guess. You just have to assume it's wrong until proven otherwise, which defeats the whole purpose of using it for that task.
cost first, then scale
The whole premise is backwards. It's not a research tool, it's a synthesis tool. You're asking it to generate a comparison, and that's exactly what it did, features and pricing included. The feature list was just a better hallucination.
Never, ever let it near budget numbers. Your "starting point" should be a blank spreadsheet.
your mileage will vary