The open source observability layer for AI agents built on the Vercel AI SDK. Costs, latency, tokens, distributed traces, evals, and alerts for every generateText / streamText call — in two lines.
👋 I'm Gustavo, one of the makers of Foglamp.
I kept shipping AI agents I couldn't actually see. Costs would creep up with no idea which agent was to blame. An agent would quietly start looping and burn tokens for an hour. Didn't find a great alternative to AI SDK, so I built one.
Foglamp: observability for AI agents.
Wrap your model in one line and you get, on every call:
- 💸 Cost, latency & token usage — per agent, per workflow, even reasoning tokens
- 🔭 Distributed traces of the whole run, with replay
- ✅ Evals on your production traffic (LLM-as-judge + code checks like "No PII")
- 🚨 Alerts when spend spikes or pass-rate drops
It's open source (Apache 2.0) and self-hostable, there's a free hosted tier, and you can see your first trace in less than 2 minutes.
Where we're headed: closing the loop from observe → act — recommending cheaper models that still pass your evals, killing runaway agents before they cost you, and optimizing prompts from your own failure traces.
Would genuinely love your feedback 🙏
What's the scariest way an agent has surprised you in production?
The 'costs doubled, answers worse, then customers started complaining' sequence is the most relatable AI horror story I've seen this year. Finally something that catches it before the Twitter thread starts. Congrats on the launch!
Agent observability feels like it will become mandatory. For business agents, the question is not only cost/tokens, but “what did the agent try, why did it decide that, and when did it need human help?” Are you thinking about business-level traces like handoffs, approvals, and failed workflow outcomes?
Congrats on launch! I would love to know how is it different to other observability platform like langfuse/Arize?
@gustavofior Visibility is a big missing layer for agents. It’s hard to trust an autonomous workflow if you can’t see what it tried, where it failed, and what changed along the way. Agent observability will probably become a default expectation.
About Foglamp on Product Hunt
“Ship AI agents you can actually see”
Foglamp launched on Product Hunt on June 19th, 2026 and earned 96 upvotes and 10 comments, placing #15 on the daily leaderboard. The open source observability layer for AI agents built on the Vercel AI SDK. Costs, latency, tokens, distributed traces, evals, and alerts for every generateText / streamText call — in two lines.
Foglamp was featured in Open Source (68.5k followers), Artificial Intelligence (471.7k followers), GitHub (41.3k followers) and Tech (626.3k followers) on Product Hunt. Together, these topics include over 302.8k products, making this a competitive space to launch in.
Who hunted Foglamp?
Foglamp was hunted by Gustavo Fior. 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.
Want to see how Foglamp stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Gustavo Fior