01[ infinite loop ]
DETECT
the agent is repeating itself and going nowhere.
MITIGATE
break the loop, summarize where it got to, start fresh.
LIVE · RUNTIME FAILURE RESOLUTION
make agents
failproof
the observability and policy layer for agents. find where they break, ship a policy that stops it, and keep them improving.
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+
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[ ● MONITORING ]
━━ trusted by developers from
> section_02 / failure_modes
agents run.
failproof keeps them running.
[ 01 / 05 ]
02[ hallucination ]
DETECT
the agent called a tool or file that doesn't exist.
MITIGATE
block the call, tell the agent what does exist nearby.
03[ context drift ]
DETECT
the agent has wandered away from the original goal.
MITIGATE
pull it back with a reminder of what it was supposed to do.
04[ intent completion ]
DETECT
the agent finished the task but kept going anyway.
MITIGATE
stop the run. surface the result. prevent the damage.
05[ dangerous action ]
DETECT
the agent is about to do something destructive.
MITIGATE
block it. ask a human first. log everything.
> section_03 / agenteye
understand millions of logs in realtime
the observability plane for agents. continuously surface failure modes, watch every event, alert on anything, and query it all through an agent that does the digging, end to end.
// the agent that runs it
one agent does the digging, end to end
ask in plain english. it writes the query, reads the trace, clusters the failure mode and tells you what broke, across every log you've ever ingested.
// observe
every event, the moment it fires
// failure modes
failures, clustered continuously
// alerts
alert the moment it breaks
// query
query millions of logs in milliseconds
sql or the visual builder over every event, session and eval. no indexing, no waiting. drop any result straight onto a dashboard.
// cli + mcp
pull it into your local claude
the agenteye cli ingests every run. pull it down, or wire the mcp straight into your local claude, so your coding agent learns from each failure and keeps improving.
> section_04 / failproofai
find the failure. fix it for good.
agenteye finds where your agents break.
failproofai stops it from happening again.
a policy layer that steers agents away from what they shouldn't do, and gives them specific instructions on what to do instead.
build the self-improving loop for your agent.
01agenteye
find failures in your agent sessions
replay the trace and see exactly where the run looped, drifted, or did something it shouldn't have.
02failproofai
fix them with failproofai
ship a policy to deny or warn agents across your favourite harness or custom setup.
// policies
39 built-in policies
// every agent
one install, every agent
// deep audits
deep audits that keep agents improving
// get started
one command. value in under 30 minutes.
$ npm install -g failproofai
★ open source on github →> section_05 / how_we_integrate
one line. no rewrites. local.
failproof plugs into the hooks the harness already exposes. nothing changes. except how reliable agents get.
$npm install -g failproofai
# install the cli
$failproofai policies --install
# enable 39 built-in policies
$failproofai
# launch the local dashboard
┌── failproof v1.0 ──────────────────────┐
│ ● 39 policies active │
│ ● claude code + codex hooks attached │
│ ● dashboard at http://localhost:8020 │
└────────────────────────────────────────┘
drop-in
piggybacks on the hooks your agent harness already exposes. nothing to change in your agent.
separate process
runs alongside your agent in a separate process, reads the trace.
local-only
no telemetry, no cloud round-trip. your agent's reasoning never leaves your machine.
> section_06 / failure_expertise
knows how every harness fails.
and every model.
claude code
anthropic cli + sdk
● first-class support
openai codex
cli + agent runtime
● first-class support
github copilot
copilot cli hooks
● first-class support
cursor agent
cursor cli hooks
● first-class support
opencode
opencode plugins
● first-class support
pi
pi-coding-agent
● first-class support
gemini cli
google gemini cli
● first-class support
[ coming soon ]
goosedeep agents
━━ CAN YOU KEEP THE AGENT ALIVE?
guiding the agent away from failure.
SNAKE= agentFRUIT= guiding policyGOAL= keep it off the pink
> section_07 / what_operators_say
trusted by teams shipping
real revenue on agents.
"We got deep understanding of how agents are failing and can be improved with Failproof. Was great working with Nivedit and making our agents resilient!"
- engineeringengineering team @ testsigma
"we now have fewer incidents, less compute waste, and faster shipping. Bonus: it is open source. Excited to scale more workloads with Failproof."
- Aravind Ranganathanco-founder & cto @ niti ai (ex-uber, microsoft)
━━ from the team that lives in agent failures
field notes from the lab
agent failures, architecture, and what it takes to ship agents in production with confidence.
the agent didn't fail. it was just told too much, too soon.
Why progressive disclosure is the most underrated concept in agent reliability.
read post →
stop praying in prompts. start enforcing with hooks.
Git figured this out decades ago. Agents are about to go further.
read post →
retry is not enough: the 3u framework for agentic reliability
In agents, failures are cognitive. Uncover, Understand, Utilize.
read post →
launching the aire principles
Five open standards for production AI systems, translated from SRE.
read post →