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DidWork
Verify agent outcomes, not just tool calls.
AI agents often report success because a tool call completed, even when the actual outcome is wrong or incomplete. DidWork independently verifies agent work against the expected result, gives agents clear pass/fail gates, and can trigger repair when verification fails. It works through MCP and an SDK, supports multiple providers, and produces shareable verification receipts so developers can see what was checked and whether the work was actually done.
I built DidWork because I kept running into the same problem while using agents inside Pulltrader: the tool call succeeded, the agent said the work was done, and the actual outcome was still wrong.
That happened enough times that I stopped treating it like an edge case and started researching it. I ended up documenting 38 failure claims across 8 providers, with the same pattern showing up over and over: agents are usually very good at knowing whether an action ran, but much worse at knowing whether the intended result actually happened.
DidWork started as an internal tool to solve that.
The idea is simple: give an agent an independent verification step before it moves on. Check the outcome, return a clear pass or fail, and give the agent a chance to repair the work when verification fails.
I initially built it for myself, then realized this problem is going to become more important as we give agents more autonomy.
Would love to hear how other people are handling this today, especially if you’ve had an agent confidently tell you something was finished when it definitely wasn’t.
About DidWork on Product Hunt
“Verify agent outcomes, not just tool calls.”
DidWork was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #117 on the daily leaderboard. AI agents often report success because a tool call completed, even when the actual outcome is wrong or incomplete. DidWork independently verifies agent work against the expected result, gives agents clear pass/fail gates, and can trigger repair when verification fails. It works through MCP and an SDK, supports multiple providers, and produces shareable verification receipts so developers can see what was checked and whether the work was actually done.
On the analytics side, DidWork competes within Developer Tools and Artificial Intelligence — topics that collectively have 999.5k followers on Product Hunt. The dashboard above tracks how DidWork performed against the three products that launched closest to it on the same day.
Who hunted DidWork?
DidWork was hunted by Ryan Gonzales. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of DidWork including community comment highlights and product details, visit the product overview.
Ryan Gonzales